WHEN COMPLEX IS AS SIMPLE AS IT GETS: Guide for Recasting Policy and Management in the Anthropocene (Revised, February 2023)

Emery Roe

I believe

. . .in a politics of complexity. One which you can’t homogenize or leave undifferentiated. A politics that reminds us of what works is often at the smaller scale, where the gatherers of information are its users. A politics that starts with cases to be analyzed in their own right. A politics that resists getting lost when scaled up but compels asking at each scale, What am I missing right in front me? A politics where no matter how tightly-coupled the world, people’s stories are not as connected. A politics that insists if you believe everything is connected to everything else, then nothing is reducible to anything else, and if you believe both, then the starting point is not interdependence or irreducibility, but the kaleidoscopic granularity in between. If everything is connected, then not everything adds up.

Table of Contents


Part I. Key concepts and terms

Part II. Cases of recasting


Section II.1     Recasting global climate change, locally

Section II.2     What, though, about climate justice?

Section II.3     Recasting labor-substituting automation

Section II.4     Recasting long-terms, short-terms and short-termism

Section II.5     New environmental counternarratives

Section II.6     Illustrating complexity’s counternarratives for racism, climate-action-from-below and AI ethics

                        Take-aways for Anthropocene analysis and management


Section II.7     New benchmark and metrics for risk and uncertainty

Section II.8     A typology for policy and management difficulties and implications for income inequality

Section II.9     Other typologies for the Anthropocene, Or making the best of linear thinking when it comes to “coordination”

Section II.10   Wake-up calls make linear crisis scenarios V-shaped

Section II.11     Chop-logics about risks, tradeoffs, priorities, and existential threats are not appropriate for the Anthropocene

Section II.12   Analytic sensibilities and their policy relevance: poets A.R. Ammons, Jorie Graham and Robert Lowell

                       Take-aways for Anthropocene analysis and management

Key Concepts

Section II.13     “What’s missing?” in this catastrophic earthquake scenario

Section II.14     Preknown-known-unknown and the implications for “unintended consequences”

Section II.15   The problem with adaptive learning and management in the Anthropocene

Section II.16    What to do when criticisms are spot-on, but the recommendations aren’t

Section II.17    Begin, rather than end, with the radical agenda

Section II.18   “Managing” risk and uncertainty, or coping better ahead with inexperience?

Take-aways for Anthropocene analysis and management


Section II.19    Policy palimpsest: concept, examples, and the violence

Section II.20    Heuristics as clues

Section II.21    The genre of wicked policy problems

Section II.22   Etcetera-isms as crisis kitsch

Section II.23  The analogy, “we are at sea,” remade for the Anthropocene

Section II.24   Thinking infrastructurally about 11 major policy and management issues

                        Take-aways for Anthropocene analysis and management

Conclusion  Human agency and power in the Anthropocene

Dedication. For Louise and our family


This is a short book with many examples for reanalyzing and managing policy issues of high complexity, uncertainty, conflict and unfinished business in the Anthropocene.

I will have failed if the reader isn’t convinced that many hard issues can be recast anew and usefully, even under (especially under) conditions of today and ahead. Policy and management have long been marshaled to face the unpredictable, but “Anthropocene” underscores the intensifying social, economic and environmental instabilities from human interventions, not least of which are in the form of policy and management. I’ve been told there’s an optimism to this guide. I would say it’s realism for the indispensable push ahead.

The guide’s readers are those who understand that the Anthropocene requires different ways of thinking through and analyzing big policy and big management. No more chop-logic about starting with risks, determine the tradeoffs, and establish priorities. No more about too-little too-late, there is no alternative but to [etcetera], and anyway, next is worse. Even where that might hold, it holds only so far, and those avowals certainly do not go far enough. The Anthropocene is too complex for that.

In fact, that its complexity enables recasting so-called intractable problems. To telegraph ahead, a complex policy or management issue certified as “intractable” is one that has yet to be recast more tractably without simplifying the complexity. Some policymakers, policy analysts and public managers already know complexity is the enemy of the intractable, not its definition or guarantor. More will understand so in the future, including social critics, policy and management academics, social scientists, and even pundits. This guide is for them.

I doubt anything like a formal manual is possible, let alone useful. Instead, this work is a guide—part primer with core constructs and part casebook with examples illustrating their application. There is no blueprint here. The guide’s framework has four pillars that differ from conventional analytical and management approaches:

  1. The guide is for major policy and management issues that are complex. Nothing here about “let’s first simplify and then scale up.” Equally important, the complexity is on the rise because the number of components (elements) in major issues, the functions (roles) each element has, and the interconnections between elements and functions are increasing in ways that challenge further measurement, monitoring and comprehension.
  2. The increased complexity does not, however, mean intractability. The more complex, the more opportunities to recast the issue tractably, as case examples exemplify.
  3. This means policy analysts and managers can usefully advise decisionmakers more frequently than might be supposed in a world of so-called wicked policy problems. “Even if what you say holds, you can go further. Here’s how and still be policy relevant. . .” None of this is easy or guaranteed.
  4. Difficulties, inexperience and not-knowing are to be encountered in recasting and pushing further. Fortunately, the more complex the issue, the greater chances in distinguishing between managing, controlling and coping ahead with respect to its complexity. Setbacks are expected but are also more likely to be positive setbacks.

These four pillars argue against thinking the Anthropocene can be universalized or reified or abstracted as it is already highly differentiated for the purposes of real-time policy and management. Here too many know this. For them, it has always been a complex, uncertain, interrupted and conflicted Anthropocene. For them, it’s always been a question of, So what? What’s the upshot for going ahead?

Part I defines and connects the pillars’ key terms and concepts. I’ve kept the points brief, signposting along the way case examples that are more fully expanded and sequenced together in Part II (the bulk of the guide). The guide concludes with a short chapter on different notions of human agency and power more suitable and accessible, I argue, in Anthropocene policy and management.

A last point before getting underway. A large section of any Anthropocene canvas for policy analysis and public management is missing in this guide: critiques of current approaches (including the disciplinary frames of economics, engineering and systems modeling) and alternatives already proposed or existing for dealing with unpredictable conditions, not least of which are participatory approaches, long-term planning, and calls for broad structural changes.

By not reviewing this literature I will seem immodest in promoting my framework while avoiding others. Had I the space I’d have had a section undertaking the literature review. Even so, you’d find much I agree with. Most of the agreement, however, would be of a qualified, “and yet. . .” The guide’s rationale for an Anthropocene “yes, but” or “yes, and” is developed in Part I and Part II’s sections. That said, I do not want to be taken by the reader—curious or distrustful—as dismissive of the critiques and alternatives already on record and the politics I share with them as expressed in the guide’s epigraph.

I have kept this work short but with many examples because the intended readers already know we are in the Anthropocene. Admittedly not a representative sample, the policy analysts and managers with whom I’ve worked by and large understand that one’s perceptions of a complex policy problem vary by one’s demographics (age, education, income/class, gender, and race/ethnicity, to name five only). They understand these categories, in today’s parlance, are historicized and socially constructed (e.g., some work in governments that prohibit gathering data by “race”). They are even now advocates of thinking long-term planning and structurally.

But they also understand that all this is meaningful precisely because complications matter. Other factors, like sexual orientation, language or “disability” are as important, if not more so, for really-existing contexts as differentiated as they are on the ground. This guide is for those who appreciate they are already marooned in the lands of “and-yet” and who recognize blaming politics, dollars and jerks gets policy and management only so far. In these days, we need to go further inland.

On one side is the tide race about how no one wants to hear policy and management issues are more complex than they know. Yes, but then again we have a duty of care to ensure decisionmakers understand the issues aren’t as simple as they’d like. On the other side is the tide race about why we analysts never know what we have to advise decisionmakers until we can make it a story or tell it succinctly. Yes, but then again analysts know there has been the dumbing from a five-page memo into a fifteen-minute PowerPoint presentation into the three-minute elevator speech and, lately, into the tweet. What next on the graduate school syllabus: Telepathy? “The knowing look” in 10 seconds or less? And yet—it remains true that we have to be able to sum up what’s going on and what can be done.

This guide charts ways inland to that. In particular, how do we buy time in order to better prepare for the present, let alone the future? “Recasting” is this guide’s answer, when it comes to those issues of “useful-for-whom-and-with-respect-to-what” so important in the calls for structural change and longer-term planning in and for the Anthropocene. While I recommend each recasting for further thinking, I will also have failed if, in aggregate, they do not make you more confident in searching out your own.

Part I. Key concepts and terms


In ordinary language, policy and management are considered intractable when complex, uncertain, unfinished and conflicted. As we shall see, these are often far more than controversies over science and technology.  For starters, a policy or management issue is uncertain when causal knowledge about it is found wanting by decisionmakers. Complex when the issue’s components or elements are more numerous, varied and interconnected. Incomplete, when efforts to address the issue are more and more interrupted and left unfinished. And conflicted, when individuals take very different (at times polarized) positions on the issue because of its uncertainty, complexity and incompleteness. To stop there would however be to end in the exaggeration of wicked problems.

The argument here is that problems in analysis and management of these issues arise when those relying on ordinary language do not differentiate terms, like uncertainty or intractability, as contexts change or already differ. Let me state the implication formally. When you qualify uncertain or complex or unfinished or conflicted by asking “with respect to what,” so-called risk ends up being differentiated from uncertainty, uncertainty with respect to consequences is not the same as uncertainty over the likelihoods of those consequences, and unknown-unknowns are another matter altogether. These differences are central to better policy and management.

In the same way, “highly complex” and “intractable,” which are easily conflated in ordinary language, are different even from the get-go. Complicated, let alone complex, does not mean intractable. In fact, the opposite holds when real people with real problems are operating in real time. Since some readers might take “complexity is the enemy of intractable” to be counter-intuitive, let’s be clear about the guide’s definition of complexity going forward.

Policy and management complexity.

The guide adopts what is arguably the best-known definition, that of po­litical scientist, Todd R. La Porte and his construct of organized system complexity: “The de­gree of complexity of organized social systems (Q) is a function of the number of system components (Ci), the relative differentiation or variety of the components (Di), and the de­gree of interdependence among these components (Ik). Then, by definition, the greater Ci, Di, and Ik, the greater the complexity of the organized system (Q)”.

This definition has the merit of highlighting four features of policy and management complexity often left ambiguous in ordinary language. Discussion of the key fourth feature—the increased opportunities to recast a complex issue—is left to the section that follows.

The first feature ensues from the definition: Complex is a comparative property of systems; that is, a system is more or less com­plex than another system in terms of the respective number of components, the differ­entiation of said components, and their interrelatedness. While it is common enough to say, “this or that is complex,” such statements beg the question of more or less complex with respect to what. Just what is the baseline used in this instance for establishing “complex”? In other words, the methodological point is not that you “scale up to complexity,” but rather the system of interest becomes more (or less) complex by way of comparison. The map smooths out the shoreline, which is anything but smooth when you’re on the shore. To put the point informally, although the guide’s discussion of complexity has its ambiguities—just what is a “system” that it is more complex?—the attempt throughout is to be less ambiguous than many ordinary language discussions.

Second, the definition illustrates how difficult it is to quantify complexity beyond numbers of compo­nents and functions of each component. For there is no broadly accepted quantitative measure of interconnectivity (which is a better term for our purposes, as some connections are unidirectional and not bidirectionally interdependent). The same could be said for identifying inter-related “functions.” Nevertheless, some ordinary language, such as “in­creasing resource scarcities,” can capture a sense of the interconnectivity at the global scale.

Third, to distinguish a system’s components from each other, the different functions or roles each component has, and the interconnections between and among the functions and compo­nents is its own methodological imperative: First, differentiate! The more you differentiate the case at hand, the more unlikely you are to find reduced-form crisis narratives such as the Global Financial Crisis (the most salient feature of the 2008 financial crisis was that it was not global) or the Tragedy of the Commons (its premise of a homogenous pasture open to like herders is what must not be assumed). Part II sections and case material return again and again to the imperative for the guide’s Anthropocene audience: First, differentiate!

Recasting the intractable.

The fourth feature following from the guide’s definition of policy and management complexity is by far the most major.

The chief feature of this complexity is surprise, as Demchak (1991) stated long ago, and surely the greatest surprise is how many recastings are possible for issues of many components, multiple differentiations, and high interconnectivity. The recastings of interest to this guide are those that keep the complexity for tractability purposes rather than conspire to reduce it in the name of Keep It Simple.

When an experienced county emergency manager tells us, “Floods are complex events, they have many variables,” it’s hardly helpful to pipe up, “Just remember: Whatever you do, keep it simple!” A more useful response to the emergency flood manager would be identifying other emergency response professionals who routinely manage equally complex events, and see how they do better than the rest in handling the inevitable surprises. Here surprises emerging from complexities are a solvent for producing better practices. To be clear, such recasting does not mean simplify; the former’s synonyms are: reframe, redescribe, recalibrate, revise, readjust.

But what if you, the reader, are not an emergency manager? For you to see this kind of complexity and its import means you can start analysis almost anywhere. You see the forest; I see a mountain of poison against insects. You switch off the light at bed-time; I switch on the darkness. I witness the birth of the family’s first child; you see the first child give birth to a family. I ask, when is biotechnology bestiality? You ask, are gardens zoos without the cruelty? Is burglary a kind of architectural criticism? Does burning down a lumber yard mean the forgone structures have been destroyed?

Doesn’t our continuing inability to safely store nuclear weapons waste reveal the Cold War to be the first war in modern times where the continental US took direct hits from an enemy? What does the US look like when it is a country where more men might be raped than women? (Think: prison male populations). What if those lengthy studies to model and validate the lifecycles of threatened species turn into their weapons of mass destruction?

Or consider recastings already familiar at the time of writing: General Motors—a pension system producing cars. McDonalds—a real estate multinational selling hamburgers. Uber—the world’s largest taxi company owning no vehicles and presumably having no cab drivers as employees. Facebook—the world’s most popular media owner creating none of its content. Alibaba—the most valuable retailer with no inventory. Airbnb—the planet’s largest provider of accommodation owning no real estate. The US government—a massive insurance conglomerate with an empire’s army.

Consider less familiar recastings. Your bad policy mess: It’s said today some 790 million people remain without access to electricity and 2.6 billion people depend on polluting fuels for cooking. At one point, three to four billion people—up to two-thirds of the world’s population—lived in regions without adequate water supplies or sanitation. More recently, it’s been estimated that 2.2 billion people on Earth live without safe drinking water.

My good policy mess: Truly those are very, very large numbers, right? In fact, even today the distribution of people worldwide without adequate water supplies and energy is so large that many of them must be doing better than the others. That means there are tens of millions—hundreds of millions?—of people who do not see themselves as victims and who have helpful things to say about how to better survive without adequate water to those millions more do see themselves victimized by similar inadequacies. But where then are the campaigns, e.g., in the World Bank or the IMF, to do just that?

His bad policy mess: It has been said that one out of every two young African-American men in major US urban areas is enmeshed in the criminal justice system. But that too is a very large number. Her good policy mess: Why are we not interviewing the other 50 percent of young urban African-American males outside the criminal justice system to find out what they are doing, and what the rest of us could learn from them?

Their bad policy mess: A reported 11 million people have been in the U.S. illegally. Our good policy mess: If those numbers are anywhere close to accurate, then there must be thousands—hundreds of thousands? far more? —who are already acting as if they were good US citizens. Or consider this: It’s estimated that of 280 million-plus migrants worldwide, some 82 million have been forcibly displaced. If that isn’t bad enough, what happens next? We look first to international and national organizations—and if not them, then philosophers and ethicists—to come up with answers that work better than others!

Examples are easily extended, but the point remains: The world is not one way only because the world’s complexity—repeat, its many components, each component with multiple functions (e.g., my simultaneous roles as husband, father, author…interacting with those of others), and the many interconnections between and among components and functions (towards what ordinary language calls “the wider context”)—enable all manner of seeing and parsing.

To summarize, a complex policy or management issue labelled “intractable” is one that has yet to be recast more tractably without simplifying the complexity. (More below on the difficulty, inexperience and not-knowing in all of this.) Whether or not the recasting is useful is another matter, to which we now turn.

How to usefully recast complex policy and management.

In addition to the key concepts developed in this section, the guide’s Part II cases focus on three additional ways to recast complexity: methods, analogies, and counternarratives. (Sometimes the only certain thing the policy analyst and manager have in a contested policy issue are the narratives for and against it.)

Recasting methods in new or different ways for the analysis and management of risk, uncertainty and with respect to ignorance is a major part of this guide. I also illustrate how a number of different analogies—palimpsest, clues, genre and “thinking infrastructurally”—reframe, in useful ways. complex policy and management at the issue or system level. In other cases, policy-relevant counternarratives are already available for recasting seemingly intractable features of issues like automation and global climate change. “Policy optics,” at times in the form of thought experiments, is a shorthand term for these different ways to recast.

But, “useful for whom?” Answer: for those who already act in ways that demonstrate they take complexity seriously. (Yes, that is not everybody.) I will have failed if the guide’s major recastings are not new or surprising to the reader. It is crucial you understand that the complexities and complications of Anthropocene problems do not mean recasting ends up showing just how intractable things “really” are for decisionmakers.

The guide’s policy optics are twists in the kaleidoscope that is any complex issue, illustrating the same shards can take on more than one configuration, and that some configurations are more helpful. (Remember: Reframings, revisions, redescriptions or recalibrations are not ipso facto simplifications.) We appear to be at our cognitive limits when confronting the intractable—we just seem unable to go further in thinking—until a new analogy or method or counternarrative shifts the focus. This guide does not pretend to cover the many other optics for treating complexity seriously (e.g. methodological triangulation and middle-range theories, which have been discussed at length elsewhere).

“Even if what you say is true as far as it goes, it needs to go further. . .”

Since recastings of complex issues—including “wickedly” intractable ones—are not only possible but to be expected, the most policy-relevant thing we can say to decisionmakers, analysts and managers is: “yes, but” or “yes, and.”

“Yes, it’s complex; but you need to push the matter further…” The part that is “yes” is affirmation that taking a decision does matter; the part that is “but” or “and” is the insistence that the follow-on matters also. “Yes, your recommendation holds, but it can be usefully amended in this way. . . “ To be able to say that one must first ask of themselves: What am I missing that is right in front of me? How can the issue be recast without losing complexity’s seriousness and timeliness? How do we move beyond the jargon of the day? (What is jargon anyway, but concepts that prematurely cease to go far enough?) There are, of course, policy analysts, managers and decisionmakers doing so already.

Note the point of “yes, but” or “yes, and” is not to stalemate or paralyze action but to turn complexity to its singular advantage, recasting. Yes, Planet Earth is a very complex, approximately closed system, but equally closed with respect to everything? The mess we’re in—and it’s a good set of affordances as Part II illustrates—is that the chronic climate crisis can’t be about the planet and science, all the way down.

Assertions of all-the-way-down take us quickly to all manner of “yes, but. . .” So too for other major policy and management issues: Differences matter, now. For if we can’t manage better in real time with all this complexity, why would we believe promises to manage them better later on in an ever more complex Anthropocene?

Here’s how taking complexity seriously matters. We know that policy and management are contin­gent on all manner of factors—societal, political, economic, historical, cultural, legal, sci­entific, geographical, philosophical, governmental, psychological, neurological, techno­logical, religious, and what-not. In fact, why close off analysis of policy and management complexity at “what-not,” when understanding and action are enriched with “yes, but” or “yes, and”? In contrast to those hobbled to the rhetoric about the right person with the right policy at the right time, complexity’s barrel is so full of fish it’s difficult to track anything like the one.

But what about the fact that policy analysis and management are socially-constructed? Yes, core concepts of risk and uncertainty, like others, are historicized. (Not only is your risk not mine; 19th century uncertainty looks very different from 21st century versions.) But to stop there is also to end in exaggeration. Acknowledgement of the historical, social, cultural, economic…roots of policy analysis and concepts for management has too rarely been pushed far enough.

For there is a major corollary to this social construction: Humans know only that which they create. (Such is the insight of Augustine let alone Nietzsche for philosophy, Giambattista Vico for history, Roy Bhaskar for science…) Humans know mathematics in a way they do not know the universe, because the former is a human creation about which more and more can be made to know. Mathematics uncertainties are socially constructed in a way that, for lack of a better word, “unknowledge” about the universe is not. This corollary means that to accept that “risk and uncertainty are socially constructed concepts easily historicized” is the start of analysis, not a conversation stopper foreclosing it.

What needs to be pushed further are the details of the interconnections among risk, uncertainty and associated terms that we make and the meanings we draw out for these connections, often under conditions of surprise and case-by-case. (Yes, it’s more complex than, Just recast!) How this happens or can happen is the task of the Part II case examples. Our creations are always surprising us and this guide takes to heart that humans often seek to explain the surprises by means of novel analogies, methods and counternarratives that extend the range of what they—we—call knowledge. (Yes, humans also revert to stereotypes and worse.)

That which we have created by way of risk, uncertainty and more—and continue to create—has become complex indeed. In fact: so complex as to continually provoke more differentiations in what we call useful knowledge. (Useful for whom? Again: for those whose actions demonstrate they take complexity seriously. Again: We know that’s not everybody.) One particularly important set of human distinctions is that related to “control” and in the Anthropocene.

Control, manage, or cope ahead.

It is common to conflate “manage” and “control” in ordinary language. That will not do when treating policy and management complexity seriously. Here, we need a richer set of terms and definitions. For when it comes to that complexity, people manage because they can’t control, and they try to cope better when they can’t manage.

Initially and formally, think of a system in terms of inputs, outputs, and the processes to convert those inputs into outputs. These inputs, outputs, and processes are differently variable rather than uniformly alike. For this guide, control is when the system’s input variance, process variance and output variance are rendered low and stable.

Think of the nuclear reactor plant: guns, guards and gates are used to ensure outside inputs are controlled; processes within the nuclear facility are highly regulated to ensure few or no mistakes are made (operations and procedures that have not been analyzed beforehand are not permissible); and the output of the plant – its electricity – is kept constant, with regulated low variance (nuclear power is often considered “baseload,” on top of which are added other types of electricity generation).

The problem, again formally, is that the number of critical systems having low input variance/low process variance/low output variance are fewer and fewer because of increasing political, economic, environmental and social unpredictabilities in the Anthropocene. By way of example, electric generation sources—and very important ones—now face high and higher input variability. Think again of climate change, more war and unrest, regulatory failures and other external impacts on the inputs to energy production (including that of solar and wind). Such pose the challenge of managing what can no longer be controlled. In response, operational processes inside a good number of power plants have had to become more varied (this reflecting the so-called law of requisite variety), with more options and strategies to process and produce what still must be low-variance output: electricity at the regulated frequency and voltage.

Coping in critical systems embraces cases where process variance can no longer be managed to match input variance and/or where output variance is no longer low and stable. That is what makes earthquakes and fires catastrophic. The best is to cope better, though attempts to command, control or manage will continue. But this isn’t coping reactively. Not only are we expected to be resilient as regards better absorbing the shocks, we are at the same time expected to try to better plan the next steps ahead. Coping here is coping ahead in the face of real-time unknown-unknowns and involves behavior above-and-beyond the reactive.

These distinctions are elaborated in the Part II case material and are very important to keep in mind throughout the guide. In particular, I discuss the policy and management relevance for the Anthropocene of control rooms of large critical systems in a number of Part II sections. “Control rooms,” however, is an ordinary language term. In actual fact, control room operators don’t control but often manage in the like ways as those in policymaking and politics who have learned that managing a mess (stopping a good mess from going bad or preventing a bad one from getting worse) is far better than trying to clean a complex mess up once and for all. Why? Because attempts at achieving “control” solutions over inputs, processes and outputs can and often do make major policy and management messes more difficult to cope ahead for, let alone manage.

In the field of critical infrastructures, you see this recognition that “management is not control but must be more than coping reactively” in the shift to more specialized terms like “operations centers” and the more accurate job titles of “dispatchers” and “schedulers” rather than control operators, full stop. In order to avoid any confusion, my research colleague, Paul Schulman, and I have equated the familiarly-known control operators and their real-time support staff as “reliability professionals.”

Centrality of inevitable difficulties, inexperience, not-knowing and setbacks.

Coping because we cannot manage, managing because we cannot control, and feigning control over that which proves uncontrollable or unmanageable signal a policy and management world full of difficulty and setbacks, where inexperience and not-knowing move front and center. Some people take this to be proof-positive of the intractable; for this guide, difficulty, inexperience and not-knowing are the persistent goad to recast—reframe, revise, refreshen, redescribe, recalibrate, readjust—the issue complexity at hand.

To anticipate later points, the more experience we have with complexity, the more we must resist behaving as if our inexperience and its difficulties are also decreasing. “Things getting easier” risks complacency in the Anthropocene. What matters the most in pushing and pulling us to recast policy and management problems is the continual experience that inexperience is always center in analysis and management and that, for wont of something better, inexperience is the best proxy we have for not-knowing.

So what? Setbacks—unanticipated, unwanted, and often sudden interruptions and checks on performance—are commonly treated as negative in policymaking, implementation, and operations. What you hoped to be a temporary setback looks to become a complete letdown. Less discussed are setbacks that prove to be positive. Long known is when a complex organization transitions from one stage of its so-called life cycle to another by overcoming obstacles at the stage in which the organization finds itself.

Other positive setbacks serve as a test bed for developing better practices (but no guarantees). Different ones are better thought of as design probes for whether that organization is “on track,” or if not, what track it could/should be on. In yet different circumstances, a common enough observation has been that setbacks serve to point operators and managers in the direction of things about which they had been unaware but which do matter.

In these and hybrid ways, positive setbacks end up as optics for rethinking major points of departure. Our track record in doing so—that is, coming to understand we didn’t know what we thought we did as well as finding out we knew more than we initially thought—becomes the pivotal point of focus in the Anthropocene. Track records of practitioners surmounting different setbacks look a good deal more useful when compared to, say, the irreproducibility of research findings in peer-reviewed publications for policy and management.  

Notably missing from the above discussion is the often-professed alternative to this guide’s call for recasting complex policy and management problems, namely: Learn and manage adaptively! Why recast, if we can learn and manage our way through adaptively? Of course, micro-learning and adaptation are critical; without them, we’d be dead.

But for the purposes of this guide, adaptive learning and management, writ large, are often not even an option, as I try to show in Part II sections and case material. In the first place, learning from failed operations versus from routine operations must be vastly different, if the large socio-technical system in failure differs so utterly from what it looked like during routine periods before or early on in the Anthropocene.

Basically, the Anthropocene problem is that learning from the past is difficult for the same reasons predicting the future is (both require stable objectives, institutional memory, positive redundancy and low environmental uncertainty, among other factors). Recasting becomes a very necessary focus in these circumstances.

Concluding remarks.

Where do I stand amidst all these key concepts and terms? Am I above the Anthropocene mess (a good mess, to repeat, when it comes recasting) and seeing it more objectively than you? Allow me to answer in the personal terms of the guide’s epigraph.

The notion that “everything is connected to everything else” is the fulcrum to better understanding and responding to the Anthropocene, as I understand it. The value added of the guide, I hope. is in differentiating how tightly or loosely coupled and how interactively or not are those interconnections in pushing further upshots that follow. This means not only that no matter how interconnected things are, they are not reducible or fully knowable to each other.

It also means that I too cannot know myself, because I cannot be everyone or everything else already in relationship to me. The guide, in short, is my best take on what is going on around you, me and others. It’s only validity, unsurprising for a policy analyst trained in pragmatism, is this: Can you use it in your own practice? Does it do so by illuminating what you’ve missed?

The over-arching analogy here for integrating the different key concepts is again that of a kaleidoscope: shake and then twist the scope, even slightly, and the different shards—these terms and concepts along with issue specifics—reconfigure, turn by turn, issue by issue. If the decisionmakers aren’t doing the twisting, you the analyst or manager (or their wannabees) are next in line to do that. What do the twists look like? We turn now to the case examples in Part II.

Part II. Cases of recasting


The case examples are grouped under four headings indicating the guide’s principal means for recasting: counternarratives, methods, key concepts and analogies. Each grouping has sections, each of which in turn is suggestive, not definitive.

I’ve aimed for brevity, a minimum of citations and even fewer footnotes, with a mix of formal and the informal in presentation. The tone has been kept brisk and conversational and some sections are shorter than others. Longer sections are meant to illustrate how much more could be said about the other recastings. No attempt has been made to survey the body of literature relevant to each topic, since the guide is long enough as it is. In case it needs saying, specific readers in specific context will find better ways to reframe. The guide’s examples, in other words, are best understood as softening up the way for your own search and recasting. The overarching context remains the unstable Anthropocene: now, later and indefinitely.

Organization and case material.

Part II begins with counternarratives, as it is crucial readers understand that complex but better alternatives already exist for recasting policy and management thought to be intractable. Alternative presents and futures needn’t be invented; they are there for those who comprehend that a planet of 8-plus billion people must have a great many counternarratives in operation (and complex ones at that). Counternarratives are their own stories or counter-arguments; they are not point-by-point rebuttals of the dominant storylines.

Indeed: A major policy and management issue is clearcut only in the (willful? Unintended?) absence of major counternarrative(s) already there. Counternarratives below devotes its six sections to recasting, respectively: global climate change, climate justice, so-called labor-saving automation, short-terms versus long-terms, environmental counternarratives, and illustrations of other counternarratives for the Anthropocene, including racism and ethics.

Methods covers topics related primarily to risk, uncertainty and unknowns. These three terms have become so naturalized in public policy and management that they are a matter of taken-for-granted knowledge. Methods to re-differentiate the terms is one way to defamiliarize the terms and see options anew or as if for the first time. The first section identifies new metrics and benchmarks for risk and uncertainty where not-knowing happens all the time. The second adopts a rough typology of different kinds of difficulties to matters of uncertainty and inequality. The third looks to other typologies already in use but in this case for defining what better “coordination” is to be in the Anthropocene.

The fourth examines how “wake-up calls” to looming emergencies usefully complicate many linear crisis scenarios. The fifth rethinks the chop-logic methodologies readers are familiar with, namely: priorities follow from risks and trade-offs. Last, in order to remind readers that science and social science do not have sole claim over defining and redefining major policy and management issues, the sixth section highlights how analytic sensibilities, here illustrated by the poetry of A.R. Ammons, Jorie Graham and Robert Lowell, can be seen as their own methodologies for opening up policy relevance.

Key Concepts takes us back to Part I by first fleshing out examples of this guide’s definition of complexity and of the importance, given to the need to differentiate, in asking ask from the get-go: “What am I missing that is right in front of me?” Six cases are discussed. The first asks what’s missing in the most important earthquake scenario for many in the United States. The second questions current understandings of “unintended consequences” in light of Part I. The third underscores the special problem of why adaptive learning and management are not an alternative to recasting.

The fourth focuses on the construct of “yes, but,” especially important in bridging what for many practitioners has long been a major gap in policy analysis and management: What to do when the analysis you are reading is spot-on but the recommendations said to follow are not? The example here is the growing problem of corporate greenwashing and what to do about it. The fift illustrates how the key concepts enable radical agendas to kick-start analysis and action in contrast to far too many discussions that can only end by calling for such an agenda. The sixth and last section under Key Concepts relies on two financial crises to illustrate how very important it is to distinguish “managing risk and uncertainty” from “coping better ahead with inexperience.”

Analogies, the last grouping of sections, centers on a set of six different analogies for recasting hard problems more tractably: policy palimpsest, clues, genre, crisis kitsch, “we are at sea” in the Anthropocene, and “thinking infrastructurally” under these conditions. The examples include failed states, carbon trading schemes, algorithmic decisionmaking, wicked policy problems, catastrophic disasters and the positive side of Be careful what you wish for! As the reader will find by the end of Part II, these policy optics are best used in combination with each other.

I’ve aimed for a very wide diversity of cases in Part II to nail home the point that recastings of difficult policy and management issues are not only possible, they are likely. A downside is that to read these 24 sections straight through feels like being in a tumble-dryer. As a pause button, each of the four groupings ends with a short set of Take-aways for Anthropocene analysis and management. To telegraph ahead, one particular take-away is crucial—that of interconnectivity not only within Anthropocene complexity but also within and among the four groupings.


Section II.1     Recasting global climate change, locally

Section II.2     What, though, about climate justice?

Section II.3     Recasting labor-substituting automation

Section II.4     Recasting long-terms, short-terms and short-termism

Section II.5     New environmental counternarratives

Section II.6     Illustrating complexity’s counternarratives for racism, climate-action-from-below and AI ethics

Take-aways for Anthropocene analysis and management

Section II.1     Recasting global climate change, locally

Thought experiment and case material.

Let’s assume the situation is one of “too little/too late” with respect to ameliorating global climate change globally. I undertake this thought experiment not because I insist it to be the case; rather, assume this is the worst-case scenario and see if we can, nevertheless, recast it in ways that make it more tractable to useful intervention.

Take as our point of departure a major review of the published research on the impacts of climate change (Mora et al. 2018). Here is what the review article concludes in its main text:

Our assessment of the literature yielded a small number of positive and neutral responses of human systems to climate hazard exposure (reviewed in Supplementary Note 2).We surmise that the reduced number of positive or neutral impacts may be real, but may also reflect a research bias towards the study of detrimental impacts (discussed under Caveats in the Methods). This small set of positive and neutral impacts, however, cannot counter-balance any of the many detrimental impacts that were uncovered in our literature search, particularly when many of these impacts are related to the loss of human lives, basic supplies such as food and water, and undesired states for human welfare such as access to jobs, revenue and security.

Now turn to the article’s Caveats subsection for details:

Although our survey of the literature yielded some case examples of adaptations, positive and differential impacts (Supplementary Note 2), these are unlikely to reflect the full scope of the adaptations, opportunities and trade-offs associated with climate hazards. The large array of cases that we uncovered with a systematic literature search on only climatic impacts suggests that a better understanding of those issues (adaptations, positive and differential impacts) will require their own comprehensive analyses.

If the reader’s curiosity is piqued, they turn to Supplementary Note 2, where the following passage is found. (As the passage is long, the temptation is to skim. However, the following recasting depends on close attention to the examples.)

Although the majority of reported impacts were deleterious to humanity, some climate hazards led to beneficial impacts and in other cases no observable responses. Reduction in malaria transmission in Senegal and Niger was attributed to loss of mosquito breeding habitats brought about by drought and habitat loss. Drought and storms occasionally increased nutrient content in surviving crops, whereas drought in neighboring countries increased availability of game animals in Namibia. Drought and natural land cover change were in some cases reported to improve water quality due to decreased nutrient runoff into streams. Warming reduced seasonal affective disorders, and mortality during winters, although the latter is controversial and unlikely to outnumber increases in heat-related mortality. Flood exposure increased social trust, and the likelihood of people to vote. Changes in ocean chemistry altered the distribution of marine organisms increasing availability in certain fisheries. Warmer temperatures have increased tourism flow toward colder destinations in the UK and the Alps. The Alaskan whale watching industry benefited from changes in ocean chemistry leading to changes in whale migration patterns, allowing for longer viewing seasons. Since the 1970s, there has been significant sea ice reduction in the Arctic providing increasingly navigable waters and shortening the shipping distances between ports. There were also cases where changes in climate hazards did not result in observable responses. For instance, societal impacts of floods and storms have not been found to contribute to the onset of civil conflict as changes in other hazards have.              

[For ease of reading, text footnotes to the findings have been deleted.]

A close reading of all the quotes reveals a narrative discrepancy in the reviewand we know from policy analysis that textual discrepancies can be the window through which we can re-see a problem differently. In my re-reading: how did the ‘large array of cases that we uncovered’ referenced in the Caveat and itemized in detail in Supplementary Note 2 become in the main text “[t]he small set of positive and neutral impacts” that “cannot counter-balance any of the many detrimental impacts that were uncovered in our literature search” (my italics)?

The question brings into focus the local in ways occluded by the term global. The first time you read through the list in Supplementary Note 2, what is itemized might look more like classic coping strategies (e.g., drought-induced hunger leaving people no choice but to do something). But now consider the list when seen through the lens of the more granular differentiation of operational strategies that are control, manage and cope ahead introduced in the guide’s Introduction. Many of the listed examples begin to look like opportunities for better coping-ahead (for next steps) and managing better (available options and strategies) at the local levels at which the responses were observed.


I would be the first to agree with the authors that more research is needed on the topic of local positive or neutral responses to global climate change. But therein lies the recasting. An uncontrollable climate change globally exhibits a “large array” of local coping and managing options currently under-researched or acknowledged, which admittedly would constitute a “small set” of positive or neutral responses globally. In this recasting, what is ‘too little, too late’ at the global level remains open with respect to how late and how little this is across a large array of local sites.

Am I implying that global climate change turns out to be a “good thing” locally? No. Am I saying that the Mora et al. is representative of climate change meta-analyses? No. Am I saying that all recasting is transformative at the local level? No. What I am saying is that the truth of the matter can be pushed further precisely because global climate change is complex, locally. Further, that large array of local cases form a distribution across which practices could emerge for local transformations, if not already for scaling up (the plural, “transformations,” is deliberate).

So what?

We’re told: The climate emergency requires extreme measures, including but not limited to global governance for GHG removal and remediation beyond anything the world has ever seen before. Only then can the long term and the green infrastructure get the priority they require.

It’s one thing to call for radical resistance against major polluting nations. It’s quite another thing to lay out how the next wave of environmental activism includes cadres of digital hackers ready to take on, say, Xi Jinping and the CCP. China is responsible for an estimated one-quarter of annual global GHG emissions, largely due to its massive fleet of coal-fired power stations. Where is the hacktivism ready and able to disable these plants? Or disable the real-time operations of, say, the “Big 3” credit rating agencies (S&P Global, Moody’s and Fitch) for their positive ratings of the economies fueling climate change?

In what world is unprecedented global governance of the consumption and production of the planet’s billions easier than, say, mobilizing the Chinese proletariat of some 220 million or disrupting the operations of the Big 3 CRAs, both for the planet’s survival?

I start instead from the proposition that the radical action talked about isn’t radical enough.

The radical action of interest here is in the preceding just identified. To repeat: Climate change globally exhibits already a large array of local coping and managing responses. To repeat: We know that global climate change is complex, because local responses continue to be so heterogenous and diverse. We know the large array of local cases form a distribution across which practices could emerge for local transformations, if not already for scaling up.

The proposal here is that the agenda for addressing the climate emergency establish as its benchmark the really-existing diversity of climate responses and related practices (including militancy) already underway. Now, that would be radical! Of course, more is needed by way of other-level policy and management, but the “more” would be evaluated against this benchmark and not some other far more imperfect one.

Section II.2     What, though, about climate justice?

Three decades ago, Jon Elster, the political philosopher, wrote Local Justice: How Institutions Allocate Scarce Goods and Necessary Burdens (1992, Russell Sage Foundation: New York). It’s of continued interest because one of the points is that not only can local justice systems lead to global injustice, global justice systems can lead to local injustices.

First, Elster’s definitions.

Local justice can be contrasted with global justice. Roughly speaking, globally redistributive policies are characterized by three features. First, they are designed centrally, at the level of the national government. Second, they are intended to compensate people for various sorts of bad luck, resulting from the possession of ’morally arbitrary properties.’ Third, they typically take the form of cash transfers [e.g., think reparations]. Principles of local justice differ on all three counts. They are designed by relatively autonomous institutions which, although they may be constrained by guidelines laid down by the center, have some autonomy to design and implement their preferred scheme. Also, they are not compensatory, or only partially so. A scheme for allocating scarce medical resources may compensate patients for bad medical luck, but not for other kinds of bad luck (including the bad luck of being turned down for another scarce good). Finally, local justice concerns allocation in kind of goods (and burdens), not of money.                                                                                                                                    

Elster (1992, p4)

The semi-autonomous institutions are local in three senses for Elster: arena, country and locality. Different arenas, such as organ transplantation, college admissions and job layoffs, follow different principles: “Need is central in allocating organs for transplantation, merit in admitting students to college and seniority in selecting workers for layoffs” in the US. Allocative principles vary by country as well: “In many European countries, need (as measured by number of family dependents) can be a factor in deciding which workers to lay off”. Finally, allocative principles can also vary by locality within the same country or arena, as with the case of local transplantation centers in the US. (In case it requires saying, these systems have changed since Elster’s writing!)

In short, complexity in local justice systems comes not just from the fact that the goods are scarce, heterogeneous and in kind and that the sites of allocation may well be local contingent. Local justice systems vary also because principles are tied to complex arrays of criteria, mechanisms, procedures, and schemes.

Implications, including for climate justice.

Not only are local justice systems not designed to compensate for global injustices, they can also lead to those injustices:

From childhood to old age, [the individual] encounters a succession of institutions, each of which has the power to give or deny him some scarce good. In some cases the cumulative impact of these decisions may be grossly unfair. We can easily imagine an individual who through sheer bad luck is chosen for all the necessary burdens and denied all the scarce goods, because in each case he is just below the cutoff point of selection. To my knowledge this source of injustice has not been recognized so far…. Those who are entrusted with the task of allocating a scarce good rarely if ever evaluate recipients in the light of their past successes or failures in receiving other goods. Local justice is largely noncompensatory. There is no mechanism of redress across allocative spheres….

[B]y the nature of chance events, some individuals will miss every train: they are turned down for medical school, chosen by the draft lottery, laid off by the firm in a recession, and refused scarce medical resources; in addition, their spouse develops cancer, their stocks become worthless, and their neighborhood is chosen for a toxic waste dump. It is neither desirable nor possible to create a mechanism of redress to compensate all forms of cumulative bad luck. For one thing, the problems of moral hazard would be immense [i.e. if people knew they were going to be compensated for whatever happened to them, they could take more risks and thereby incur more harm]. For another, the machinery of administering redress for bad luck would be hopelessly complex and costly.                     

(Ibid 133-4)

Where so, local justice clearly can lead to global injustice.

But just as clearly from a local justice perspective, the global justice promised in, say, climate justice (e.g., via reparations), leads to local injustices, when the former is implemented uniformly over an otherwise differentiated landscape. One thinks immediately of how to define an “extreme event” that triggers so-called automatic debt relief.

To expand, the more uniform the application of climate justice policies, the greater the local pressure for suitably heterogeneous applications, if not alternatives. But the more differentiated on the ground, the greater the chance of global injustice when considered as universal principles uniformly applicable at the micro-level.

In this way, just as it is not possible for local justice systems to compensate for the global injustices they create, so too it may well not be possible for global justice systems to compensate for the local injustices they create, at least in any timely way or coverage.

So what?

For one thing, the continued insistence that global climate justice involves money transfers (as distinct from in-kind compensation typical of local justice systems) ends up further monetarizing a global environment that local systems take to be quite otherwise.

In so doing, the insistence obscures the huge importance of in-kind compensations at the local level. Think here of the livestock sharing systems (e.g., khlata in Tunisia and mafisa in Botswana). These are local justice systems irrespective of the livestock involved being methane producers from a techno-managerial perspective on global climate. Indeed, I can’t think of a better example of global climate justice at odds with local justice systems, globally.

Section II.3     Recasting labor-substituting automation

The policy narrative.

Developments under the rubric of artificial intelligence (AI), including machine learning, Big Data, and algorithmic management/decisionmaking, are often deployed with respect to a longstanding policy narrative: Important forms of technological change, namely “automation,” are labor-substituting by displacing workers and their livelihoods. Given the issue has always been complex, evidence continues to be provided in favor or against the narrative. In fact, articles on the impacts of automation resolutely rehearse the same arguments for and against.

What is less recognized is that useful specifics are frequently erased or effaced by maintaining versions of the generalized narrative. This matters when the specifics of earlier debates—particularly, options and insights offered up but not followed on—can, if resurfaced, question and usefully reboot the current debate.

Here’s an illustration. Schlögl, Weiss and Prainsack (2021) undertook a review of relevant literature from 2013 – 2018 on the topic, “Future of Work,” concluding in part:

Our findings show the dominance of a specific narrative within the grey policy literature on [Future of Work]. It starts with the assumption of unprecedented, rapid technological advance that, embedded in demographic and ecological transformations as well as globalisation, creates opportunities and risks. The main opportunities are gains in productivity, new jobs and higher living standards. The risks are new inequalities, pressures on social security systems, and the costs of transition and disruption for various groups. The answer to these challenges lies in the re- or upskilling of the workforce and adjustments to social and labour market policies [according to their document review].


Assume this storyline is correct as far as the authors take it. Importantly then, there is a narrative discrepancy, “unprecedented,” in the preceding quote. This technological change is not unprecedented.

The unprecedented is happening all the time when it comes to the narrative’s ambit. The authors themselves point out that “U.S. president Lyndon B. Johnson even set up, in 1964, a ‘National Commission on Technology, Automation, and Economic Progress’. Transformations and crises of work as a result of technological progress are a recurring theme throughout modernity.”

Therein, I submit, lies one clue to rethinking the policy narrative. If you go to their referenced report of that National Commission on Technology, Automation, and Economic Progress, Technology and the American Economy, you will find the labor-substituting narrative in terms that still resonate, e.g., “technological change would in the near future not only cause increasing unemployment, but that eventually it would eliminate all but a few jobs, with the major portion of what we now call work being performed automatically by machine.” (If in doubt about the continuing salience of the latter, search the web for “fully automated luxury communism” at the time of writing.)

Yet it is not the report’s resonances, but specifics that are useful for the recasting. On the downside, the report is full of terms and references to no longer existing programs. On the upside—and this is the counternarrative I want to highlight—it offers up specific proposals that read more like “lost modernities,” i.e., pathways to addressing the narrative in ways we no longer think about today:

We recommend that each Federal Reserve bank provide the leadership for economic development activities in its region. The development program in each Federal Reserve District should include: (1) A regular program of economic analysis; (2) an advisory council for economic growth composed of representatives from each of the major interested groups within the district; (3) a capital bank to provide venture capital and long-term financing for new and growing companies; (4) regional technical institutes to serve as centers for disseminating scientific and technical knowledge relevant to the region’s development; and  (5) a Federal executive in each district to provide regional coordination of the various Federal programs related to economic development.

Nothing came of this recommendation as far as I can determine (a few commission members, from the then right and left, objected to it). But just think about the “what if’s”!


What if the recommendation had been adopted and implemented then? What if it were enacted today, in light of the Fed’s now longstanding mandate for promoting price stability and maximum employment? (The US Fed was legislated to promote maximum employment in 1977.) Even with inevitable caveats about politics, dollars and jerks, the question still compels: What if, indeed!

The point is that one consequence of keeping the dominant policy narrative in general terms is to disconnect already-existing counterexamples and with them, already-existing counternarratives. The starting assumption must be: For any complex policy and management issue, counterexamples are to be expected. The duty of care—the same “care” as in Be careful what you wish for!—is to read closely and find them—in fact, still in front of you. “When the picture is not good enough, go closer,” said the photographer Robert Capa.

Section II.4     Recasting long-terms, short-terms and short-termism

Short-termism and long-termism.

Much of what we hear today and read sounds like short-termism. Why aren’t people taking the long-term far more seriously? What’s with all this willfully ignoring Anthropocene crises?

Think of short-termism as the preoccupation with a present differentiated as in: right now, now this hour, now today, or some such nearer term. Long-termism is the preoccupation with a past or future outside the confines of that presentism. Just as minutes, hours, days and weeks are conventionalized units, so too past and futures are denominated into decades, centuries, millennia and so on.    

For example, British historians are apt to talk about the long 19th century as a unit running roughly from the Glorious Revolution of 1688 to the Battle of Waterloo in 1815. (There’s also the Long Sixties from mid-1950s to mid-1970s.) Some Western historians talk about the short 20th century running from 1914 (the start of World War I) to 1989 (the fall of the Berlin Wall). In brief, whether broad generalizations based in any versions of the 19th or 20th centuries are a kind of short-termism or long-termism depends on the trends or patterns taken from varied periodizations. Let’s turn to some specific examples.

The argument.

For me, short-termism is captured by: “Our inability to forecast the future is the mess we are in right now.” Long-termism for me is captured by: “In the long-run there is just another short-run.” Both are consistent with much of this guide’s understanding of today and ahead.           

You, the reader, however come to the Anthropocene having different “preoccupations-with” and your own counternarratives of the short term. Yours may be more akin to: “There is every reason to believe the present can’t continue this way indefinitely.” Or your longer term is more in line with: “It isn’t a question of if it will happen but when it happens later on.” Other orientations are more than possible (e.g., those “middle-range theories”), but the four just identified are sufficiently illustrative to make the following case.

For this guide, the crux of the matter is not the “long term versus short term,” but rather complex policy and management crises are pegged to or differentiated by more than one of the orientations. 

Illustration: “the healthcare crisis”.

Start with “the present rise in healthcare costs in the US can’t continue this way indefinitely.” Rescript the healthcare crisis now through the other three orientations: “The current crisis in healthcare is that we can’t predict healthcare requirements with the specificity we need for taking action now”; “Healthcare continues to be characterized by seriatim technology and digital upheavals, one after another”; and “It’s not if, but when the next worldwide pandemic will happen.”

In this rescripting, “the healthcare crisis” reflects not only multiple but different orientations are at work, but their sequencing is a major way for differentiating and tracking time (i.e., “the COVID pandemic has emerged as its own healthcare crisis”). In this recasting, different crises no longer unfold at different times; rather, crises unfold our time.

Two upshots.

Another implication is far more important for rethinking the complaint about short-termism with respect to crises: In all four orientations, the future is a hypothesis we have yet to finish with. Hypothesis? A core urgency moves to the fore when we focus on the nature of the present in any long/short orientation: First, where specifically does “not-knowing the present” come into play in each?

Whatever the answer, one point is clear: Conventional short-termism—the present matters more than the future, period—requires more certainty and confidence than warrantable for the hypothesis. That there are more orientations—and competing preoccupations—than my four serves only to nail home this point further.

The virtue of center-staging not-knowing is to remind those preoccupied with various short-terms and long-terms that predicting the future is difficult for the very same reasons learning from the past is difficult: Both, to repeat, require stability in objectives, institutional memory, fallback reserves in case something goes wrong, and low environmental uncertainty. But we are in the Anthropocene: These conditions do not prevail.

For many, the absence of preconditions for predicting the future and learning from the past is the problem. For me, it is positive to start from the fact that not-knowing, inexperience and difficulty are each variable. Why becomes clear when we move to the more granular case level, the second upshot here.

Some regional climate change modeling is of such a high resolution today that climate model results can be and are in some cases disaggregated in ways of use to critical infrastructures. It’s now possible to project estimates for rising sea-levels, storm surges and inland flooding in, say, 20-year increments to better reflect already existing near- and longer-term cycles for infrastructure depreciation and forward investments, among others. The latter can be updated in light of the projections from the former.

Do such modeling results reduce other pre-existing uncertainties related to depreciation and investment cycles? Let’s say: no. Do modeling results increase confidence that action with respect to these cycles can be taken, nevertheless? Let’s say: yes, possibly.

Section II.5    New environmental counternarratives

The challenge.

When it comes to the Anthropocene, the long-term and the planetary are deployed to staple home the interconnectivity of it all. We need to push that truth further, however. Everything connected to everything else means nothing is reducible—at least, completely or importantly—to anything else. We can no more ignore irreducible particularity than the interrelatedness. Fortunately, such differentiating promotes policy and management relevance in the face of high(er) complexity.

To put it differently, specifics matter more because we are in the Anthropocene. In fact, the specifics that matter take us far from current priorities and practices for setting percentages and amounts for greenhouse gas reductions.

The specifics I have studied discriminate more granular foci in environmental scenarios. Here the guide focuses on real-time operations of societies’ key critical infrastructures within a regional context—infrastructures that drive, for bad and good, the Anthropocene:

  • Granular because risk, uncertainty and not-knowing are always with-respect-to specific failure or accident scenarios;
  • Real-time operations because the measure of effectiveness is to manage effectively now as we are in the Anthropocene;
  • Operations of key infrastructures because the reliability and safety of these large sociotechnical systems—think widespread energy and water supplies—are not only vital to society, but are often based in ecosystem services mandated for restoration or sustainability; and
  • Within a regional context because global climate change modeling and other types of environmental simulation increasingly accept the region as the unit of analysis for near-term risk and uncertainty management.

Where are we to find new or under-acknowledged environmental scenarios?

If the challenge is to identify specifics—that more granular focus on real-time operations of institutions within a regional context now that we are in the Anthropocene—it pays studying those whose current jobs are to do just that. To that end, four (4) groups are identified and sketched below who are actually working on counternarratives.

  1. One group is found in the control rooms and surrounding support staff of large critical infrastructures

Yes, these are the villains in many environmental crisis narratives. Because some infrastructures, particularly water and energy, are based in ecosystem processes and services, many of them, in actuality, operate under the dual mandate of maintaining service reliability while at the same time safeguarding, if not actually restoring, associated ecosystems.

The more I studied control room operators, the more I learned they are far from environment’s enemy. Turn to four neglected storylines based on the really-existing practices of reliability professionals in highly complex socio-technical systems:

Practice 1: Bring real-time ecologists, biologists and renewable energy specialists directly onto the floor of the infrastructure control rooms.

This is already being done to varying extent. If environmental specialists cannot now reliably advise on real-time ecosystem-based infrastructure operations, why would we believe that those promising to do so later on will actually know by then? Complex large systems are only reliable as the next failure ahead. Why then is preventing the next case of failure any less important than those in the later future?

Not all ecologists are temperamentally suitable or trained for real-time advice. In March 1999, a colleague and I interviewed a well-known ecologist who insisted the Delta smelt would not “go extinct even if we try to wipe them out”. Then came the articles with titles like “the collapse of pelagic fishes in the upper San Francisco Bay-Delta”.

Practice 2: Redefine system boundaries.

Wetlands have been an iconic ecosystem in ecologists’ stories. Yet wetlands are “ecoinfrastructures” in other large system definitions. Those that moderate the effects of wind and waves on the adjacent levee structures are part of the levee system definition just as the levees provide an ecosystem service by protecting these wetlands at other times.

In a storm, a single stretch of road may become an essential part of repair access for electricity lines as well as the means of access for levee flood-fighting crews. In this case, the stretch of roadway becomes part of the emergency response of two infrastructures. A roadway between wildlands on one side and the electricity lines on the other side can serve as a firebreak in the emergency response system for the approaching wildland fire.

From one perspective, it looks like three separate systems in competition with each other: a forest next to grazing land next to arable fields, no one of which can expand without loss to the other. From a perspective that treats them as subsystems to a larger ecosystem, the grazing land serves as a firebreak between the forest and arable holdings. So too the California Delta can be seen not just as its own system but also as a buffer against encroaching urbanization from the east (Sacramento and Stockton) and west (Greater Bay Area), much as agriculture in South Florida and Western Netherlands have buffered against urbanization moving into the regions’ “green” areas.

It follows that a core empirical issue is where that extra investment would produce the greatest positive impact on the ecosystem and landscape: adding trees and green-scapes in Sacramento or Stockton (urban ecosystems); reducing chemical agriculture on Delta islands (agricultural ecosystem); and/or constructing more wetlands around Delta islands (the environmental ecosystem). Since contexts are so varied (politically, culturally, geographically. . .as well), the devil is in detailing the scenarios.

Practice 3: Act on the full implications of the infrastructure control room as a key institutional and organizational formation for ensuring the high reliability mandate of improved ecosystem services and processes.

Control rooms in large critical infrastructures are one of the few institutional formations that have evolved over time and across multiple contexts to promote high reliability repetitively in the management of complex socio-technical systems.

The implications are considerable. We keep hearing that global problems must have global solutions. If true, those solutions will never be highly reliable at that scale. There is no global cadre of its real-time managers in the foreseeable future. All of which explains why the shift away from global climate change models to regional ones is so significant. It is far more plausible to imagine water and energy control rooms coordinating far better for ecosystem services at the regional level when it comes to collaborating.

Practice 4: A great deal of environmental anxiety is understandably directed to identifying better and more timely warnings for what are called, Big System Collapses.

To the extent that these large socio-ecological systems (climate, forestry, agro-ecosystems) depend upon critical infrastructures for their survival, it’s important that environmentalists and other concerned groups recognize the early warning signals that indicate to control room staff and support staff they are operating at, or beyond, their performance edges:

  • The infrastructure’s control room is in prolonged just-for-now performance. This means operators find it more difficult to maneuver out of a corner in which they find themselves. (“Yes, yes, I know this is risky, but just keep that generator online for now!”)
  • Real-time control operators are working outside their official or unofficial bandwidths for performance—in effect having to work outside their unique domain of competence.
  • Decision rules operators reliably followed before are turned inside out: “Prove we can do that” becomes “Prove we can’t;” “Ensure a capital cushion to protect against unexpected losses” becomes “From now on, manage for expected losses.” (More in a Section II.24.)
  • Real-time operational redesigns (“workarounds”) by control room operators of inevitably defective equipment, premature software, and understandably incomplete procedures are not effective.
  • Control room skills as professionals in identifying systemwide patterns and undertaking what-if scenario become attenuated or no longer register.
  • Instead of being driven by societal dread of the next major failure, control room professionals are told their track record up to now is to be benchmark for system reliability ahead.

In case it needs saying, such under-recognized early warning signals and narratives should be expected to change over time and context, regardless of how rebarbative terms like “ecoinfrastructure” seem.

2. If our models and narratives must become more granular with respect to time and scale for the systems, then we also have a way of recasting the debate in ecosystem management and restoration. In so doing, we identify a second group sourcing future environmental narratives—and one fitting with global and regional complexity.

Two ideal types, the carvers and the molders, can be interpreted as driving narratives about site-specific ecosystem restoration. In idealized form, carvers see their task as one to release the true ecosystem from the surplusage around it. Chip away at all that population, chisel off the far-too-built environment, get rid of the non-native species and banish pollution—and then only does the ecosystem as it was meant to be have a chance of being revealed. In the carving orientation, the ecosystem manager or restorer assumes the landscape has within its remit the good form and function created for it as nature, not by us.

The second ideal type is found in ecosystem managers and restorers who see themselves essentially as modelers of clay (often literally). They mold the landscape by trying to press onto it contemporary versions of complexities it once had. Here there is no prospect of repristinating nature. Ecosystems have to be designed and maintained, albeit their resulting complexity may be little like the pre-disturbance or pre-settlement states. (Indeed, the grievance that ecosystems are continually degraded signals landscapes are moldable.)

Unsurprisingly, really-existing ecosystem managers and restorers fall somewhere between the two playbook orientations—they are ideal types, after all—making do with what’s at hand and with what is possible.

What is clearer now than before is that this good-enough improviser is itself a third ideal type for ecosystem management and restoration.

Think of this third ideal as its own narrative. The newly credentialed environmental professional starts with the expectation that the “ecosystem” or “risk” or “trade-offs” are out there to be identified, only to realize in the field that each has to be specified in more detail, namely: Risks or uncertainties with respect to what failure scenario? Under what conditions does this hold? To what end or ends? This situation as opposed to what? Just what is this a case of? What are you and I missing right in front of us?

As practice and field work unfold in light of addressing these questions, the professional gradually recognizes that his or her challenges arise because what is out there depends on how “it” is defined or managed or improvised in the first place by really existing human beings in the really-existing organizations and the really-existing systems they find them in. (As with all ideal types, the ideal storyline isn’t case-by-case.)

This improvisation has its own idealized and practical benchmarks and practices.

You see this, most prominently, in “urban ecosystems.” Cities are highly differentiated systems with their own improvised sets of species and processes that have in some cases considerably more biodiversity than commonly supposed. From this perspective, not only will there be multiple benchmarks (which actual improvisation inevitably falls short of ideal improvisation), but the scenarios of success or failure will also be with respect to different real-time uncertainties than those that perplex carver and molder. We should expect from this crucible of granularity will come new, more case-specific environmental narratives.


What might some case-specific narratives look like for improvisation and how would their granularity matter? Permit me one example. The widely-identified pollution in China has been credited in significant part to its coal-powered electricity plants and other hazardous facilities. That may be true as far as it goes, but the case needs to be pushed further.

I, for one, want to know more about the real-time conditions under which middle-level operators and managers are operating these large-scale infrastructures. Are the reliability professionals not there or are they present but operating under ever more prolonged “just-for-now” conditions waiting from more options and better practices? Or would it be better to describe a good number of the managers as improvising under just-in-time conditions? We need to hear from Chinese scholars researching regional high reliability infrastructures (including its massively significant high-speed rail and hydropower systems).

3. Environmental policymakers and academics have always been a heterogenous group and they too are a source of new environmental narratives.

One example is offered here, this returning us to the importance of the region as the unit of environmental analysis and action. An influential policy and management arena in the US and abroad has revolved around “environmental governance.” Here I focus on an early formulation. Delmas and Young (2009) present a simplified schematic for understanding environment governance in terms of multi-level interactions (local, regional, national, international) among three main actors (public sector, private sector, and civil society).

They plot some interventions into Figure 1, drawing from case studies and associated literature reviews in their edited volume, Governance for the Environment: New Perspectives. For our purposes, note environmental arenas where multiple spheres overlap, particularly those related to eco-labelling, placed at the center of Figure 1 (the shared area of the three intersecting sectors).

A volume chapter (Auld et al 2009) gives considerable attention to eco-labelling interventions in terms of third-party certification schemes that ensure goods and services are sustainably sourced. For example, we have programs that certify that produce is organically grown, that coffee is fair-trade, and that timber comes from forests sustainably managed. Such certification programs work on two fronts typically, first by incenting consumers to buy certified products, while discouraging them from purchasing non-certified products or services.

Now, a new environmental narrative

Recast the role of eco-labelling. As seen elsewhere in this guide, a major, persisting problem in the California Delta is deep concern over the high reliability and safety of the levee system protecting island agricultural activities there.

Imagine a third-party program (i.e., not mythically “neutral” or “objective”). Along the lines of sustainability councils, this organization would certify whether or not any given Delta agricultural land (broadly writ to include livestock, aquaculture and non-traditional crops) was protected by levees that meet a standard of high reliability in design and maintenance. Imagine consumers would be encouraged to buy “levee-certified” goods and services and discouraged from buying those that were not so certified. Imagine, in short, the same element—the levee—but now having a different function than “keeping water out” only.

The wider buying public in California and beyond would be encouraged to purchase only those goods and services from adjacent country entities that had supported levee certification in and around Delta water. In like fashion, the wider buying public would be discouraged in purchasing from those entities whose goods had been transported on the deep-water shipping channels passing through the Delta to Sacramento and Stockton, if those firms did not support levee improvements up to third-party certification standards along those shipping channels. In parallel, the wider buying public would be encouraged to buy agricultural products only from those Delta islands that had been levee certified and discouraged from buying levee uncertified.

4. The fourth group from whom to expect new environmental narratives (not just regional but “big picture” ones) are practicing ecologists and environmentalist themselves. This group is far more differentiated than the reader might suppose. Indeed, that differentiation has been there from the beginning, with its under-acknowledged counternarrative for the rest of us.

The term, “ecosystem,” comes to us through A.G. Tansley’s 1935 article, “The Use and Abuse of Vegetational Concepts and Terms.” Tansley has been criticized for his role in colonial British ecology, but here he has salience for two different reasons.

First, ecosystems for Tansley make no sense without taking humans and their interactions with the landscape into account. “We cannot confine ourselves to the so-called ‘natural’ entities and ignore the processes and expressions of vegetation now so abundantly provided us by the activities of man. Such a course is not scientifically sound, because scientific analysis must penetrate beneath the forms of the ‘natural’ entities, and it is not practically useful because ecology must be applied to conditions brought about by human activity,” he wrote.

This might seem to be pushing at an open door today, but Tansley deployed a discourse quite different than his contemporaries in the US. The latter offered just-so stories about “climax communities” evolving on their own—only if free from human beings mucking things up. Two commentators on Tansley’s work (Laura Cameron and John Forrester, 2017) argue that his “principal contributions were, in contradistinction to American ecology, to emphasize the systemic interrelations of human activity and botanical phenomena—he sees no real difference between those ecosystems which are natural and those which are ‘anthropogenic’ (nature ‘produced by man’, as he glossed in 1923).” “A well-defined localized human community is the kernel of an ecosystem,” Tansley reiterated in addressing the British Ecological Society in 1939.

But Tansley is important to us for a second reason. Not only was he a founder of the British Ecological Society (the precursor to such societies in many other countries) and the Nature Conservancy, he was also well-known and respected member of the British Psycho-Analytic Society, having been analyzed by Freud for nine months in 1922 and 1924. For Tansley, humans and their desires (“energy”) were and are never far away from ecosystems in profound way.

Whatever the reader thinks of Tansley’s dated terms, many ecologists today still consider human desires The Enemy. Such, I’d like to think, would have appalled a Tansley who took desire and ecosystem to be inseparable. He’d be the last person, I suspect, surprised or shocked by the fact that large critical infrastructures, created to satisfy desires and wants, have impacts not just bad but good.

There’s also a fifth group to generate and modify new environmental counternarratives—you.

Start with what many would consider unexceptional: “Given the obvious contingency of much of our lives—we do not in any meaningful sense intend or choose our birth, our parents, our bodies, our language, our culture, our thoughts, our dreams…and so on—it might be worth considering not only our relationships to ourselves and our relationships to objects, but (as the third of the pair, so to speak) our relationship to accidents,” writes Adam Phillips, the psychoanalyst.

So, we could say the same about our relations to Nature’s contingencies. Fair enough, were it not for many others, including Agnes Heller, the philosopher, concluding the opposite and with respect to the very same contingencies Phillips mentions:

In choosing themselves, men and women choose exactly what they are, as they are. They choose their best talents as much as their physical handicaps, they choose their parents, their childhood, their country, their historical age. They choose their poverty if they happen to be born poor, and their riches if they happen to be born rich. They choose their accidental features. That which they are by accident they become by choice.

Put that radically, Heller’s counternarrative stirs us to ask under what conditions is her point the case. And I think those reading her passage can see what she’s driving at: In the same fashion, we have yet to make what we can of the Anthropocene’s risks, uncertainties and unknowns. We make of inevitable contingencies what our experience of inexperience will in the circumstances we find ourselves. In trying to do better by positioning yourself somewhere between the Phillips and Heller extremes, you end up recasting these contingencies and events for your own Anthropocene.

Section II.6     Illustrating complexity’s counternarratives for racism, climate-change-from-below and AI ethics

It’s evident to many that “these are uncertain times” (and like phrases) are too-often used by elites to divert attention from the certainties of their exercising power.

This guide pushes that truth further: Complexities—again: societal, political, economic, historical, cultural, legal, geographical, governmental, psychological, neurological, technological, religious, and more—ensure that counternarratives are in the making or already exist with which to oppose, directly or indirectly, those dominant policy and management narratives. They don’t have to be invented by some megalomaniacal vanguard or techno-managerial elite who know better than the unwashed billions. Let’s briefly examine some of the counternarratives already there for three complex policy and management issues.


The Anthropocene is also a time of deeper thinking about the roots of racism (e.g., settler colonialism) and racism’s role in other isms. Yet we have to ask: What are still missing that is already there by way of counternarratives with respect to “racism” or “anti-racism”? A great deal, I would answer, and precisely because of the complexities.

Go back to the late 1990s to the mid-2000’s. It’s not so far past that some readers won’t remember it, but far enough away for added perspective, as they say. Start with statistics reported then about African-Americans:

**Black Americans, a mere 13 percent of the population, constitute half of this country’s prisoners. A tenth of all black men between ages 20 and 35 are in jail or prison… (cited 2007)

**Something like one third of our young African American men between 18 and 25 are now connected to the juvenile justice system or the federal justice system. They’re on probation, they’re in jail, they’re under indictment or they’re incarcerated. (cited 2002)

**…the most striking thing is the high portion of black men with zero reported income: about 18 percent of black men, compared to about 7 percent for whites and Hispanics. (cited 2007)

**After declining throughout the 1980s, employment rates of young, less-educated white and Latino men remained flat during the 1990s. Among black men aged 16 through 24, employment rates actually dropped. In fact, this group’s employment declined more during the 1990s (which fell from 59 percent to 52 percent) than during the preceding decade [of lower economic growth]… (cited 2004)

**The most dramatic, the most unfortunate of the several disastrous outcomes is the high rate of paternal abandonment of children: 60% of Afro-American children are being brought up without the emotional, economic or social support of their fathers. (cited 2002)

Even then, however, you’d have had to ask: Why ever were we not interviewing those nine-tenths of young black men who were not in prison, those two-thirds who were not enmeshed in the criminal justice system, those four-fifths who did not have zero income, that half who were employed, and those four out of ten who had not “abandoned” their children—all in order to find out what they are doing right?

Racism, of course, was one systemic reason why the questions weren’t asked, or at least more frequently and prominently. But that too falls short of the point. What were those counternarratives, and for that matter, what are they now? The answer to that is the less sanguine “the opposite of good is all too often good intentions.”

A well-meaning observer at that time said that, if a magic wand were available, he’d wave it so that every Black would have a master’s degree, as degree holders were more likely to have higher incomes, better health and more positive outcomes. Before I waved any such wand, then or now, I’d want to know what different educations were to be made missing.

Climate-action-from-below as emergency response

The crux

It’s striking how similar responses-from-below regarding climate change are to immediate emergency response witnessed in recent large-scale disasters. (The similarity would have been more obvious if climate change is called for what it is, the climate emergency.) For example, a Mozambican scholar-activist has

outlined three major differences between these climate actions ‘from below’ and top-down solutions: (i) participation of local actors from planning design and implementation of projects; (ii) horizontal relations and equal access to information; and (iii) non-extractivist initiatives that retain benefits within communities for local consumption, without extractions and expropriations.                                                                                                          

A summary of the plenary points made by Natacha Bruna, director of Observatório do Meio Rural, Mozambique, on September 27 2022 at the Climate Change and Agrarian Justice Conference, Johannesburg, South Africa

Immediate emergency response to earthquakes, tsunamis, floods, large wildfires and the like also feature collective action by people involved (and not just in search and rescue); so too are featured the importance and centrality of horizontal and lateral communications (the work of Louise Comfort on emergency response in major earthquakes is exemplary in this regard). More, the collective action and joint improvisations are geared to restoring rather than depleting key services any further during the emergencies.

Pushing the point further

The similarities—I argue, equivalencies—go further. The local site and communities are the pivot-point in emergency response as in climate action-from-below. Food sovereignty is mentioned as a priority in responses-from-below, and indeed localized food and water around the site also become a priority during emergency response and into initial recovery.

Speaking of which, local forms of resistance to climate change responses directed from above look a great deal like conflict over longer-term disaster recovery: Both involve many different or changing stakeholders with conflicting agendas and interests.

So what?

What’s the added value to policy and management that comes with seeing the immediate emergency response features of climate action-from-below? Some of the recasting you might like; other parts not so.

Let me stay with the US setting and focus on one primary emergency response mechanism: namely, where a city or county activates its emergency operations center (EOC) and/or incident management teams (IMT) at the department level to manage immediate response. This happens when high winds, ice storms, fires, flooding and their combinations take down essential services, particularly backbone infrastructures of water, electricity, roads and telecoms. It should go without saying that many of these events are related to climate change.

Now the recasting: Activate the EOCs and IMTs, or at least the ones which know they are in the Climate Emergency. And just who exactly are the distressed peoples and sites? It’s up to the EOCs and IMTs to decide, e.g., with respect to where spaces are being made uninhabitable, jobs are being lost, and malnutrition is on the increase because of the Climate Emergency.


In thinking such impacts through, much of what outsiders recommend by way of emergency response clearly belongs more under longer-term recovery than initial rapid response, e.g., timely construction of those altogether different, more resilient infrastructure systems.

Note also that admonitions of “stop-this-and-that-immediately” hit a major obstacle from the get-go. In really-existing emergency response, fossil fuel is needed to evacuate people, ship goods and services to distressed areas, keep the generators running when electricity fails, and so on. Fuel subsidies in fact might be the order of day here, albeit not there.

Indeed, push the point further: Years and years of R&D have gone into prototyping and distributing more sustainable alternatives to some of these goods and services. Shouldn’t we also then expect and want their increased use in immediate emergency response as well, especially when (not: “even if”) expediting them to the distressed sites and peoples means using more petroleum-based products?

AI ethics.

A good friend wasn’t trying to be provocative in saying a clear sign a field has lost its energy is when it was everywhere overtaken by discussions of ethics. If it’s energy you’re looking for, he added, look to the boundaries with other fields in competition with it. His example of the latter was Herbert Simon’s move into artificial intelligence.

In case it needs saying, that loss of energy isn’t a bad thing where much-touted innovations have far from benign consequences (consequences being a big thing in policy analysis). Still, as a thought experiment, let’s ask in the spirit of his comment: With all this attention to AI ethics—especially transparency and fairness—is AI a moribund field in ways not commonly supposed?

As ethicists are also talking about sub-fields like machine learning (ML) and algorithmic decisionmaking (ADM), are these moribund in ways we—that is, those of us who become instant experts in AI by reading the secondary literature—do not (yet) comprehend?

For example, rapid obsolescence of software and equipment used in ML and ADM is a topic that, at least to this point (and I stand to be corrected), hasn’t been given as much attention as readers might expect. To my mind, this topic is more important that transparency or fairness, since obsolescence changes the “with-respect-to-what’s” of the latter.

So what?

Just what analytic purchase do we get parsing AI ethics through the lens of obsolescence? Well, one thing you get is a track record. Here is W. Daniel Hillis, computer scientist and inventor, writing in 2010:

I want to be clear that I am not complaining about technical ignorance. In an Internet-connected world, it is almost impossible to keep track of how systems actually function. Your telephone conversation may be delivered over analog lines one day and by the Internet the next. Your airplane route may be chosen by a computer or a human being, or (most likely) some combination of both. Don’t bother asking, because any answer you get is likely to be wrong.

Soon, no human will know the answer. 


In short, the kind of not-knowing AI portends has been going on for years.

What then is the record of all this and other such software being replaced or upgraded? Is it that the software is no longer working or that something better comes along, or both or something else altogether? How would studying this track record not contribute to really-existing AI ethics?

These are even more important questions, given the Anthropocene will make obsolete many other things that now matter, including current understandings of not just “AI ethics” but also “AI” and “ethics” more specifically. Not just a track record, obsolescence is also better understood as its own policy palimpsest, in terms discussed more fully in Section II.19.

Counternarratives: Take-aways for Anthropocene analysis and management

But, you insist, what’s happening today are global crises for which we do not have counternarratives grounded in deep knowledge, proven skills and potent remediation practices. Quite the opposite, you press: Exceptional circumstances give rise to extraordinary threats and thus to emergency measures which necessarily end up as precedents for first-ever policies and practices. We have no alternative but to. . . [fill in the blank].

This guide suggests you might want to think more about the italicized terms, as each puts you (and us) at the very limits of human comprehension, infrastructure reliability and hazard management. Why? Because any conclusion that these are unprecedented times in altogether uncharted waters is itself the artefact of having no default option when already at the limits of thinking and comprehending. That is why this guide spends a good deal of time on different methods and analogies that take “limits” and recast them otherwise. (Again, no guarantees!)

A different response to the italicized terms is the under-acknowledged background condition for taking action when conventional analysis and management are at current limits. Humans have always been many-sided, where that background condition of having many sides inherently frames the action we take. Humans are intractable only in being intractably many-sided. Another way to put this is that human and social complexity ensures counternarratives are already there or in the making—and how could you think otherwise for this planet, our most complex ecosystem, already 8 billion different persons?

This means it is never good enough to critique a dominant narrative and leave it at that. Nor is it good enough to treat a critique as if its point-by-point rebuttal has a “therefore there,” leading syllogistically to “there is no alternative but to. . .stop cutting down trees, stop using fossil fuels, stop inequalities.” Useful critiques are pushed further by the counternarratives that offer details (more formally, are granularized with respect to elements, functions and interconnections). This means it’s hardly ethical to insist your “stop” counternarrative is the best without canvassing other better, really-existing ones on this very diverse planet.

Conventional risk analysts and crisis managers are quick, nevertheless, to counter: “What do you mean we are one-sided and not on the look-out? Good managers and analysts always look at the many sides of an issue and, in fact, we pride ourselves in seeking to bridge incompatible positions—and never more so than when the prospect of disaster raises the stakes.”

But there is no “middle” to bridge or compromise over when we are at or beyond the limits of comprehension; you have to default to something other than analysis or management as usually understood, in this case the background condition or this guide’s different policy optics to recast what are currently only understood as intractable limits in order to re-engage analyzing and managing. And even then you are on the look-out for counternarratives; in this way, bearing witness or permanent critique can only be part of the answer, if that.


Section II.7     New benchmark and metrics for risk and uncertainty

Section II.8     A typology for policy and management difficulties and implications for income inequality

Section II.9     Other typologies for the Anthropocene, Or making the best of linear thinking when it comes to “coordination”

Section II.10   Wake-up calls make linear crisis scenarios V-shaped

Section II.11     Chop-logics about risks, tradeoffs, priorities, and existential threats are not appropriate for the Anthropocene

Section II.12   Analytic sensibilities and their policy relevance: poets A.R. Ammons, Jorie Graham and Robert Lowell

                        Take-aways for Anthropocene policy and management

Section II.7     New benchmark and metrics for risk and uncertainty.

Methodologically, there is no such thing as risk or uncertainty on its own; it is risk or uncertainty with respect to something. There are many ways to think about risk and uncertainty (e.g., in terms of threats and vulnerabilities), but for the present assume risk of a failure is the product of the probability and the consequences of failure. For its part, uncertainty exists when you know probability or consequences but not both; not-knowing is when neither are known.

Why are the distinctions important? For reasons already mentioned, the language of risk and uncertainty has become so naturalized it’s taken to the obvious point of departure, like filing alphabetically or chronologically.

So too in the Anthropocene. We’re told: “The first thing we have to do is assess the risks of increased flooding here…” Actually, no. First, you differentiate. The first step is detailing the with-respect-to scenarios of concern.

You identify the boundaries of the flood system as it is actually managed and then the standards of reliability to which it is being managed (namely, what events must be precluded or avoided by way of reliable and safe flood management). The risks follow from the standard to be met for the system as bounded for real time for management.

Introductory example.

Focus on an island in the western California Delta—Sherman Island—and consider criteria that engineers rely on for establishing priorities for reducing levee fragility there (the island’s levees are needed because its productive areas are considerably below the encircling water level):

  • Criterion 1. Levee fragility priority can be set with respect to the weakest stretch of levee around the island, i.e., that which has the highest probability of failure (Pf). This has obvious implications for collocated elements from different infrastructures, e.g., a very high levee Pf counsels against plans to place, say, an agro-chemical tank facility next to it. (You’d assume commonsense would commend this as well.)
  • Criterion 2. Levee fragility priority can be set with respect to the stretch having the highest expected loss of life (and/or other assets) arising from levee failure. If the levee breaches where most island residents live, then there is less time for evacuation. Consequences of failure (Cf) are important here, and this criterion is about the levee stretch that has the greatest risk of failure, not only probability of failure.

Sherman Island’s weakest levee stretch was said to be on the southwest part of the island; the stretch with the greatest loss of life appeared to be on the eastern and south-east side with more residences. From the perspective of Criterion 2 and other factors constant, it’s good that the weakest stretch of levee (according to Criterion 1) is on the other side of the island, so as to ensure more time for evacuation.

–There is a third criterion. It reflects the extent to which the levee infrastructure of the island is itself part and parcel of a wider interconnected critical infrastructure system (ICIS):

  • Criterion 3. Priority for addressing levee fragility is with respect to the levee stretch that has the greatest risk to the entailed ICIS. ICIS risk of failure is not the same as risk of levee failure only, as stretches of Sherman Island levees are in fact not just elements in the levee flood system there, but also elements in other critical infrastructures. For Sherman Island, there is the levee stretch with Hwy 160 on top; there are also other stretches serving as the waterside banks to adjacent deepwater shipping channels; another levee stretch serves to protect a large wetland berm (as fishing and bird habitat). If those stretches of levee fail, so too do elements fail in the deepwater shipping channel, Hwy 160, or the Delta’s threatened habitat.

Criterion 3 asks: What is the effect on the road system or shipping system or wetlands ecosystem, when that shared ICIS element on Sherman Island fails? If a stretch of Hwy 160 fails, road traffic in the Delta would be detoured; if a stretch of the deepwater shipping channel fails, shipping traffic would be rerouted to other ports; and so on. In some cases, the service cannot continue because there is no default option, e.g., the Sherman Island wetlands berm in terms of its habitat and fish can’t be “rerouted” in the same way, were its protective levee to fail.         

The follow-on question then is: What infrastructure system sharing one or more ICIS elements on Sherman Island would be affected the most in terms of increasing the probability and consequences of its failing as a system, were Sherman Island levee stretches to fail?

Answer: A levee breach anywhere on Sherman Island would increase the probability of having to close the major pumps for the State Water Project, with huge consequences. That is, the Pf of the state and federal water projects would increase were Sherman Island to flood, because saltwater would be pulled further up from the San Francisco Bay into the freshwater Delta. Indeed, the standard of reliability and safety being managed to by the owner of Sherman Island (the California Department of Water Resources) is that levee failure anywhere there must be prevented from happening.

–To summarize so far, the three with-respect-to levee assessment criteria—hybrids and others are possible—differ appreciably as to where risk analysts focus attention in terms of levee fragility: the weakest stretch (Pf) may not be the same stretch whose failure would have the greatest loss of life and property (Cf), while any stretch that failed would pose the greatest ICIS risk (namely, the probability that an ICIS element failing has the consequential effect of increasing the probability of failure of one or more systems sharing that element).

You would expect that calls for more and more “inter-organizational coordination” would have to be prioritized in light of these criteria. You’d be wrong. At the time of research, the third criterion was altogether outside remit for conventional risk assessment and management at the time of the research. (Major problems with the ritualized calling for “more coordination” are discussed in Section II.9, which offers a very different recasting of coordination.)

Broader methodological implications of with-respect-to scenarios.

Before proceeding to better benchmark and metric for Anthropocene risk and uncertainty, it is important to tease out what is meant and entailed by “with respect to”:

  1. If risk of failure is defined as the product of the probability of failure (Pf) times the consequences of failure (Cf), then Pf and Cf are NOT independent of each other, as conventional risk analysis insists.

It’s Pf and Cf with-respect-to the same failure scenario. Both are connected indirectly by the intervening variable of a shared failure scenario. More, the failure scenario details the operative:

  • reliability standard (are you seeking to preclude specific events or avoid them if possible? are some events inevitable or compensable after the fact?);
  • evaluative criteria (are you managing Pf [probability] or both Pf and Cf [risk]?); and
  • system being managed (are you managing, e.g., the within or across different infrastructures?)

Understandably then, the more granular the failure scenario (the greater the details about the standard, criteria and system), the more likely that Pfs and Cfs are interconnected. In the most obvious (but as we shall see misleading) case of interinfrastructural cascades, one consequence of Infrastructure1 failing (Cf1) may be to increase Infrastructure2’s probability of failure (Pf2).

This is why a risk estimate must not be confused with being a prediction, as in: “if risk is left unattended, failure is only a matter of time.” That can’t be assumed.

Even were Pf and Cf not interconnected, the function of the failure scenario is to identify and detail conditions for cause and effect upon which prediction is or is not made possible. Many “large system failure scenarios,” a.k.a. today’s crisis narratives, are devoid of just such detail when it comes to the operative reliability standards, evaluative criteria and (sub)systems to be managed or for which coping-ahead is directed. (The opposite of system failure isn’t “success”; it’s the more granular: achievement of reliable operations.)

  1. Identifying risk(s) in the absence of first defining the operational system and the reliability standard(s) being managed to ends up in having no stopping rule for possible failure scenarios and types of risks/uncertainties.

By not defining initial conditions, all manner of factors end up purportedly posing risks and uncertainties, to wit:

different assets; multiple lines of business; system capacity and marketing factors; in terms of the risks’ time-dependence versus independence; in terms of the risks associated with emergency work as distinct from planned work; investment risks versus operational ones; risks with respect not only to system safety and reliability, but also organizationally in terms of financial risk and in terms of risks of regulatory non-compliance….ad infinitum

After a point in this list, it becomes an open question as to how managing all these (and more) contributes to the infrastructure system operating reliably in real time. It is not surprising then that conventional root cause analysis of infrastructure failure is highly vexed in the absence of one or more beforehand-specified failure scenarios.

The lack of a stopping rule for failure scenarios to be worried about represents its own failure scenario when it discourages thinking through and acting on failure scenarios about which more is already known and can be managed. When we asked infrastructure interviewees what were the “nightmares that keep them awake at night,” they identified not only measurable risks and nonmeasurable uncertainties with respect to specific failure scenarios, but also the fact that scenarios for what could go hazardously wrong seemed limitless.

In other words, the probabilities and consequences of large system failure can be misleadingly estimated not only because (1) the measured estimates of Pf do not adequately address key nonmeasurable uncertainties (e.g., where either Pf or Cf cannot be measured in the time required), but also because (2) there are so many more failure modes than the conventional scenarios (e.g., earthquake or flooding) assume. Or to put the point positively, the level of granularity in a failure scenario becomes more useful when it entails a stopping rule.

  1. Misleading estimation of probabilities and consequences also occurs because the failure scenarios themselves have not been specific enough with respect to the boundaries of the system being managed and the reliability standard(s) that govern what is taken to be relevant risks and uncertainties to be managed or otherwise avoided.

This means that the infrastructure’s already-existing risk mitigation programs and controls, if any, become a priority source of indicators and metrics reflecting how seriously catastrophic failure scenarios are treated by infrastructure managers.

The existing controls and mitigations may provide the only evidence, outside the real-time management of the infrastructure control room (if present), of what works well in real time with respect to improving systemwide reliability and safety when pegged to major or catastrophic system failure. Such mitigations may also confirm the utility of the stopping rule or its need for change as new failure. modes emerge.

To put it another way, the fact that risk is not calculated through formal risk analysis and management protocols must not be taken to mean risk is not formally appraised and evaluated by other means, most prominently (1) through the skills in systemwide pattern recognition and localized scenario formulation of real-time control room operators and support staff and (2) via evaluation of existing risk mitigation programs and risk “controls.”

What do #1 – #3 add up to for the purposes of identifying new, more appropriate benchmarks or metrics for today’s large system risk and uncertainty and ahead?

At least three deserve mention.

A new risk benchmark.

When control operators and their managers in large critical infrastructures know that some events must never happen—the nuclear reactor must not lose containment, the urban supply must not be contaminated by cryptosporidium, the electricity grid must not separate and island, then better practices emerge for ensuring that. (Again, this is why we look to evaluating existing risk mitigation programs and measures.)

Mandates to reliably preclude certain events put enormous pressure to focus on and modify practices that are actually working to meet the mandates (including evaluative criteria for measuring how effectively the mandates are met). Where better practices have emerged across a variety of different cases, you know that others too face political, economic, and social constraints—basically, that trinity of politics, money and egos—and still have jumped a bar higher than we yourselves are currently facing under like conditions.

Where so, conventional risk analysis gets its questions only half way by stopping short of the other questions to be asked beforehand. The conventional risk analysis questions—“What could go wrong?,” “How likely is that?,” and “What are the consequences if that were to happen?”—are to be preceded by: “What’s working?” “What’s even better?” “How can we get there?” Only then do we ask: “What could go wrong in trying to get there?” “How likely is that?” and “What are the consequences if that were to happen?

Many things follow from this benchmark (e.g., should it need saying, the complexities are to be addressed interactively rather than sequentially.) The most important for our purposes however is the implication for implementing the recommendations from such expanded risk analyses. The first issue to be addressed isn’t, “Who’s going to adopt the recommendations and, if so, with what modifications?” but rather: “Who would implement the finalized recommendations and what are implementers’ scenarios for not failing to do so?”

A new metric for ranking crisis scenarios

First-half of thought experiment

Start with a more familiar prediction of Martin Rees, former British science advisor, who assigned no better than a 50/50 chance that humanity survives the current century because of catastrophes of our making. Think Anthropocene, in other words. How might we evaluate and rank his prediction in terms of risk and uncertainty as understood in this guide?

By way of answer, turn to another famous prediction, that of US President, Woodrow Wilson (in his time expert in public administration), who predicted with “absolute certainty” in September 1919 that there would be another world war if the US did not join the League of Nations. Assume a unit of measurement called the Wilson. It is equal to the confidence today’s experts have that Woodrow Wilson foresaw the start of World War II.

Obviously, “the start of World War II” is inexact. Wilson did not predict the rise of Hitler, the Shoah, or carnage on the Eastern Front. But crisis scenarios for financial cascades, global cyber-attacks, climate apocalypse, and fast-spreading pandemics of as-yet unknown viruses lack comparable specificity by way of their specifics, including risks and uncertainties.

The question is this: How confident are experts in their crisis scenarios when that confidence is measured out in Wilsons? When it comes to nuclear terrorism, are the experts, say, 30 times more confident that such terrorism will happen than they are that Woodrow Wilson foresaw World War II? For that matter, what would be the consensus view of specialists when it comes to denominating other catastrophe scenarios into fractions or multiples of Wilsons?

The temptation is to dismiss outright that Woodrow Wilson did foresee the future. Were that dismissal scientific consensus, it would be quite significant, wouldn’t it? Here at least is one scenario that is Just-Not-Plausible. To render any such finding means, however, the criteria used for concluding so apply to the other scenarios.

In short, we’re back to baseline confidence measures and the hard work of developing multiple ways of triangulating on and estimating specialist confidence, scenario by scenario, in the face of difficulties and inexperience over what and about which we know and do not know.

Several key points, however, become clear in this way. To ask how confident specialists are specifically about nuclear terrorism quickly becomes just what is meant by “an act of nuclear terrorism.” What are the pertinent with-respect-to scenarios?

Second-half of thought experiment

This devil-in-the-details leads to a second half of this thought experiment. Assume now we face a specific crisis scenario. It could be that act of nuclear terrorism, or that computer glitch sending global markets into free-fall, or that bioengineered pathogen destroying Anthropocene life near and far.

Assume a visualization of the widening scenario is simulated and presented so as to pressure decisionmakers to prevent that scenario from unfolding, once they see how the catastrophe metastasizes. Assume also a running tally in the visualization shows the estimated monetary value of the disaster’s costs—lives, property, whatever—burgeoning into the millions, then billions, now trillions. The tally in quick order reinforces how imperative it is to take urgent preventive action in the midst of all this.

But hold on. Assume the visualization and tally remain as described, but the simulation’s goal is recast to estimate the cost of a catastrophe that can’t or won’t be prevented. The tally then becomes an unofficial price tag of the emergency prevention and management system put into place after this disaster, so that a like one “will never happen again” (the precluded event standard of reliability). The commonplace here is that, sadly, it takes a disaster to bring about better disaster prevention and management afterward.

The temptation with this part of the thought experiment is to assert that, absent outright prevention, a world won’t be left from which to mount an effective crisis management infrastructure later on. That, though, surely depends on the specific scenario and the extenuations of implementing an emergency response infrastructure that its losses trigger. Again: The devil is in the details of the with-respect-to scenarios.

Note just how difficult it is for anyone, subject matter experts let alone others, to come up with plausible details about the crisis response structure to be in place after the losses incurred. To do that requires deep knowledge and realism—far more than the much-touted “imagination” on its own. Determination of whether the literature on “expert judgment under uncertainty” differentiate anything like conditions for effective imagination is left to the reader.

In brief, we are asked to treat possible crisis scenarios seriously until proven otherwise, when those offering the scenarios are unable to specify what it takes to disprove the scenarios or prevent their actual recurrence. Or to put the point positively, what deserves ranking are those crises whose details have already been triangulated upon, if at all.

A new metric for estimating societal risk acceptance

Retrospective versus prospective orientations to societal risk

It is generally understood that “acceptable-risk” standards, based on past failure frequencies and commitments of “never again,” can be fleeting and ephemeral. Worse, the Anthropocene promises never-seen-before calamities. There are limits in other words to any retrospective orientation to failure, as in: “Well, it hasn’t happened before, so what’s the problem now…”

It’s worth asking then, what can be offered by way of a prospective orientation—“we are no more reliable than the next failure ahead”—to identifying standards of (un)acceptable societal risk. What does “societal risk acceptance” look like if instead of based in past (in)frequencies, it is grounded in the expectation that major system accidents and failure lie ahead unless actively managed against (manage as defined in Part I)?

Consider the following thought experiment, the aim of which identifies a proxy for “acceptable societal risk.” To telegraph ahead, the proxy proposed is the aggregate curve of the major real-time control room risks of society’s key critical infrastructures.

Extended thought experiment

–Assume that society has identified critical infrastructures indispensable to its survival; that the infrastructures have central control rooms for operating their systems in real time; and that the respective control operators and support staff have a set of chief risks that they must manage in order to maintain that real-time systemwide reliability. (Here, high reliability is identified as the safe and continuous provision of the critical service, even during periods of high turbulence.)

While major assumptions, their virtue is in seeking to operationalize more granularly what current retrospective risk approaches do not. Notably, the ALARP (“as low as reasonably practicable”) method  assumes “society sets acceptable and unacceptable risks,” often leaving the implied somehow-this-happens devoid of any of the necessary specifics. But there have been few alternatives to (versions of) ALARP. Below is one such ALARP graphic:

The figure shows estimated probabilities of facilities failure based in frequencies of past failures by activity and estimated lives lost (and their cost) in the past. Above the two ALARP (accepted and marginally accepted) lines are industries with unacceptable risks (at least in part), in this case merchant shipping and mobile drilling rigs

–In contrast, a prospective approach starts with the precluded-event standard of reliability (i.e., the event or a set of conditions to be prevented must never happen, given the society-wide dread associated with system failure). Research found that infrastructure control operators need to be able to maneuver across four performance modes so as to maintain normal operations. Most important, each performance mode was found to have its own chief risk.

The four modes range from anticipatory exploration of options (just in case) when infrastructure operations are routine and many management strategies and options are available, to a real-time improvisation of options and strategies (just in time) when task conditions are more volatile. Control room professionals and their support staff may have to operate temporarily in a high-hazard mode (just for now) when system volatility is high but options few. They may also be able, in circumstances when options have dwindled, to impose onto their service users a single action scenario (just this way) in order to keep the situation as stable as possible.

The chief risk in just-in-case performance is that professionals are not paying attention and become complacent—reliability professionals have let their guard down and are no longer vigilant to sudden changes in system volatility (think of system volatility as the degree to which the task environment is unpredictable and/or uncontrollable). As for just-in-time performance, the risk is misjudgment by control operators with so many balls in the air to think about at one time. The great risk in just-this-way performance is that not everyone who must comply does.

Last, just-for-now performance is the mode managers want most to avoid or exit as soon as they can. Here the risk of “just keep doing that right now!” is tunneling into a course of action without escape options. What you feel compelled to do now may well increase the risks in the next step or steps ahead (in effect, options and volatility are no longer independent).

Note that the commonplace admonitions for being reliable—don’t get complacent; avoid overconfidence; once you’ve backed yourself into a corner, quick fixes may well work only just for now, if that; and don’t expect everyone to comply with command and control—all recognize these chief performance mode risks on time-critical, highly-consequential occupations. Contemporary examples abound, e.g., these performance modes and risks were evident in the public health infrastructures over the COVID-19 pandemic surges.

–Back to our thought experiment. Further assume now that estimates have been computed by control room operators in consultation with subject matter experts for the risks of complacency, misjudgment, non-compliance and closing off alternatives for the infrastructure system. Such is then done for (a stratified sample of) society’s key infrastructures with control rooms.

There is no reason to believe the estimates of any one of the four key risks are the same for the same performance mode across all sampled infrastructures during their respective normal operations. Different precluded events standards are operationalized differently in terms of the thresholds under which they are not to operate. Complacency or misjudgment could empirically be more a problem in some infrastructure control rooms than others.

Assume the performance-mode risk estimates (a stratified/weighted sample of them) have been rank ordered, highest to lowest, for these infrastructures operating to their precluded-event standard by the respective control rooms. A plot of points measured in terms of their respective Pf and Cf coordinates is generated in the form of a downward sloping function (i.e., logarithmic or regression). Imagine it to be an empirically estimated version of the downward “acceptable risk” line in the preceding ALARP figure. This time, though, the descending line would reflect the revealed allocation of acceptable infrastructure risks at the time of calculation for societally critical services in really-existing normal operations to prevent their respective precluded events from happening.


The downward sloping function would, by definition, be a prospectively-oriented standard of acceptable risk for society’s (sampled) critical infrastructures. It is prospective because the unit of analysis isn’t the risk of system failure—again, typically calculated retrospectively on the basis of the past record, if any—but rather the current risks of real-time control operators failing in systemwide management during normal operations, now and in the next operations ahead. Note the two-dimensionality prospective “next steps ahead:” It refers not only to the near future but also the future that has to be made—prefigured—by the control operators for the present.

Concluding implications.

Even though all this is difficult to detail, let alone operationalize—but less so than an a typical ALARP—three implications are immediate.

First, because control rooms manage latent risks (uncertainties with respect to probabilities or consequences of system failure) as well as manifest risks (with known Pf and Cf), any such downward-sloping function will necessarily have a bandwidth around it. That bandwidth, however, is not one that can be chalked up to “differences in societal values and politics.” Rather the bandwidths reflect more so the control room uncertainties (often technical and procedural but related also to managing against unstudied or unstudiable conditions).

It is true that some real-time uncertainties to be managed are linked directly to societal values, where politics—think here of those new or revised compliance regulations that followed from the last disaster—have their greatest real-time impacts. Even then, the challenge is to show how the application at this time and for this case of any compliance procedure follows from said societal values. That is no easy task because analysis would also drive down to the granular case or event level and not just up to the policy or regulatory level where societal values are (or so it is hoped) easier to identify.

A second, related implication is noteworthy. The bandwidth around a societal risk acceptance function as defined above varies because not every critical infrastructure manages to a precluded-event standard. Other standards (and associated evaluative criteria) are managed to. Even so, note how remote this acknowledgement is from any argument that societal values determine directly (or even primarily) the operative standards managed to.

An example is helpful. A primary reason why critical infrastructures manage to an avoided-events standard today—these events should be avoided, albeit they cannot always be in practice—is because their inter-infrastructural connectivity does not allow individual control rooms to preclude failures or disruptions in the other infrastructures upon which they depend or which depend on them. It is better to say that in these interconnected cases the shift from one (precluded-event) to another (avoided-event) reliability standard reveals societal preferences for interconnected critical infrastructures before it demonstrates any first-order derivation from more generalized or abstracted “societal values” per se.

Third, it is likely that that policy and regulatory leaders who do not understand the uniquely prospective orientation of reliability professionals and their four performance modes and associated risks will commit a very important error. They are apt not only to confuse their own values and views about the future for those of control room reliability professionals, but they—the policymakers and regulators—will also err because they don’t appreciate the distinctive prospective orientation of these professionals. It’s far too easy to lose sight of these sociotechnical errors under the conventional wisdom that it’s all about “the politics of risk management” anyway.

Section II.8     A typology for policy and management difficulties and implications for income inequality


If inexperience is a proxy for not-knowing (see the guide’s Part I), so then is difficulty. There may be more bulletproof typologies for difficulty than that of late literary critic, George Steiner, but it’s sufficient here. At a quick trot, four types of difficulty stand out in making sense of a text (“text” now construed broadly to include narrativized selves and situations): contingent, tactical, modal, and ontological. Our example throughout is income inequality.

Contingent Difficulties

Here the text or situation poses obscure terms or notions that you have to “go and look up.” With a little work—you read more or talk to those in the know—you figure out what the term or notion means for the case at hand.

As contingent difficulties, “Just what does uncertainty and its assessment or management really mean?” has answers that can be looked up in handbooks, manuals or statutes. What does this or that regulation say about the term in question? The same too for what qualifies legally or officially as “inequality,” income or otherwise.

Tactical Difficulties 

Here the text or situation poses obscurities that are deliberately difficult and not meant to be settled by looking up an answer. Legal ambiguities may be intentionally introduced to make it difficult for any decisionmaker to engineer or cookie-cutter a single answer across cases.

Purposive ambiguity ensures that no single answer exists for “What is risk?” or “What is inequality?” Just what “market prices” are being talked about when figuring incomes or risks core to inequality: transaction prices, offered prices, prices thought to prevail if there were a trade, prices modeled on the prices of inputs in that model, or with respect to something else? Case in point: When it comes to inequality, as philosopher Harry Frankfurt asked, what information are we losing “when treating everyone equally”?

Modal Difficulties

Here “mode” refers not to numerical average or middle value but to “modes of experience.” The text or situation poses difficulties because of the differing experiences of those reading or interpreting it. “Today I am less experienced, less able to adapt to this harsh selfish environment than the average twenty-year-old,” writes essayist Phillip Lopate, “who has grown up without my New Deal/Great Society set of expectations.”

As modal difficulties, uncertainty and inequality center on the experience of being unequal or in different chancy circumstances, and how that experience changes relationally. “To grow up is to discover what it is one is unequal to,” writes psychoanalyst, Adam Phillips. As modal difficulties, being unequal or “at risk” does not and cannot equate to official classifications of material inequality or legally-designated “risky behavior.”

Ontological Difficulties

The text poses situations so in extremis that they cannot be comprehended whatever one’s experience. These difficulties have no “answer” because no question is being asked that is answerable.

Few examples remain in media ready to domesticate every fresh obscenity. Sometimes, though, we glimpse the scorches. Leslie Hardman, Jewish military chaplain with the British during World War II, tried to describe what he saw when entering the concentration camp at Belsen: “If all the trees in the world turned into pens, all the waters in the oceans turned into ink and the heavens turned into paper, it would still be insufficient material to describe the horrors those people suffered under the SS.” As ontological difficulties, inequality and uncertainty radically alter our humanity. They make us indescribable and beyond the limits of cognition, knowledge and feeling.

First-order implications.

While the four types of difficulty come brewed together in policy and management, initial differences are evident. One, the numerical majority of inequality and uncertainty difficulties are contingent, tactical and modal, i.e., they can be addressed, if only over time or at times provisionally only.

Two, those who handle these difficulties are often to be found in teams, groups and networks rather than individually, since the difficulties are so knowledge-intensive they require varied experiences with heterodox contingencies in heterodox contexts. We should expect the same for the Anthropocene.

Three, what are taken to be significant inequality or risk and uncertainty difficulties are more likely to be modal than ontological. Modal difficulties recognize complexity but insist on the importance of different types of (in)experience in addressing them; ontological difficulties are not differentiated, at least by definition and in those ways.

The upshot is profound

There are costs in addressing one type of difficulty and not others. It’s scarcely sufficient to insist the opposite of complexity is simplicity, when the costs of dealing with ontological difficulties are set by not dealing with contingent, tactical and modal ones instead. It’s very difficult indeed to be simple about complexity. (“A maximum of simplicity goes with a maximum of difficulty. . .Being simple is not simple; it is attempting the impossible,” wrote French author, Georges Perros.)

More specifically, the difficulty with “a more equal or less risky society” isn’t that society is idealized or reified. Rather the ideal of a more equal and less risky society is not as variably difficult as are inequalities and risks in practice. It’s too easy to say the obvious—no one should starve when there is food, no one should die of thirst when there is water, no one should bleed to death when medical help could ensure otherwise—and leave it at that. Where’s the actionable granularity?

This is another way of saying that if reduction in poverty and inequality means making “the playing field level for everyone,” those involved must be skilled enough to survive and persist when that doesn’t work or counterproductive. There also is that broader caveat: The more experience with complexity and not-knowing, the more we must resist behaving as if our inexperience and its difficulties are also decreasing. Accumulating modal experiences under the impression that events are getting less difficult is to be tempered by a countervailing sense that we are as artless and craftless as ever in our inexperience with unknowns.

Where, though, in all of this is politics? Let’s turn by way of an answer to the typology’s implications for income inequality .

Major implications for income inequality.

I take a central point of the preceding typology to be this: Income inequality is not just difficult; that inequality is and has always been the result of difficulties, inexperience and not-knowing. Yes, income inequality is “political”—though why stop there and not add cultural, historical, economic, geographical, demographic and more?—but here too such labels are insufficiently differentiated to be helpful when it comes to grappling with the many and diverse complications in income inequality.

At least ten complications come to my mind immediately. To be clear, each is patently contestable, no single one is dispositive, a good many are correlated while the underlying numbers keep changing. Yet together these difficulties (and others that may have come immediately to the reader) remind us that in the Anthropocene….. Well, let me save the positive upshot for recasting income inequality to the end of this section.

In no order of priority and at a quick trot

First, as we are to worry about wealth inequality, why then isn’t it more common to point out that consumption inequality has been less skewed than income inequality in a good number of places? Many Western households have long had refrigerators, ovens, cell-phones and the TV, whatever differences in income. (And yes, consumption is also complicated.)

Second, even as the top fraction of 1 percent has vastly more income than the lowest 20 percent, that still must mean, numerically, far more happy poor people than happy ultra-rich. True, percentages matter. But the absolute number of people who are by and large happy must also matter in any felicity calculus for public policy and management. (If “happiness” seems a stretch here, go to the literature on “happiness economics”).

Third, it is patently true income inequality has increased in the US, but such has happened in other economies over roughly the same period, albeit arguably not to the extent in the US. (Or consider the issue in another way: At what point is rising income inequality accelerating so fast that we might want to talk about economies being decoupled—internally differentiated—contrary to the narrative of a coupling and coupled globalization?)

Fourth, who can be sure inequality would have been less had we done otherwise? Here what you take to be the counterfactual is decisive. If John Kerry had been elected instead of George W. Bush, do you really believe inequality would have been less?

Fifth, return to the 1960’s when income inequality was less skewed in parts of the West. Now, contrast the 60s’ injunction to drop out of the middle-class rat-race to the more recent preoccupation on income inequality (the 99% versus the 1%), as if now it’s really all about moneyed interests. (For that matter, today’s shrinking of the middle class diminishes the deadweight of bourgeois values from a 60s’ perspective, right?)

Sixth, if we were to redistribute income, what does this mean for redistributing income generation? It is often said that, say, cattle-holdings in Africa have been highly skewed and unequal, as if that is an argument for a more equal distribution of livestock. But to imagine the latter is to imagine quite other production systems in place. So too in the West. If, as critics point out, we are in a massive experiment with the radical skewing of incomes, substantial de-skewing would have to be implemented in ways far less experimental (i.e., negative), correct?

Seventh, discussions about income inequality pivot frequently on a syllogism: There is not enough money for the poor, there is more than enough money for the rich, therefore more people could be comfortably off if incomes were more equalized. But what about where there is too much money, unequal or not, at least in some places? As seen in that 2008 financial crisis, credit default swaps along with sovereign and corporate debt exceeded by many multiples the total estimated annual global GDP, an imbalance of bad money blasting away the good.

Eighth, we have all seen graphics showing how the cost of one military super-plane cashes out into so many more classrooms or social services. But the opportunity cost of that mega-plane is not set by forgone social and health services. The money saved by not building that plane would in the US—counterfactually would, not could or might—be set by post-tax wages and income no longer forgone, not by a better-funded discretionary government budget.

Ninth, an anomalous feature of income inequality discussions has been their narrow view on what a more equal distribution of income would achieve. We hear about better health and dental care among the poor, were incomes less skewed. What we don’t hear enough are arguments that more income for the poor means that they too can buy more media, take more trips, get an iPad, and eat at better restaurants—precisely things the modern puritans deny the poor when it comes government income transfers.

Which leads to a tenth reservation about today’s inequality discussions: the all-too-narrow focus on government income transfers as the primary redistributive mechanism. Private remittances, to pick one alternative, are more important than government aid to many poor countries. Why aren’t we then focusing more on increasing wage remittances as a way of addressing inequality? Or from the other direction: Since US incomes are that unequal and healthcare that inefficiently provided, then surely these inequalities and inefficiencies are a source of positive slack and reserves for future revenues and funding of better programs and economic growth?

The list could easily be extended, but stop here for the present

So far I have been itemizing complications (to which I’m sure you have had your own rebuttals); but where are the recastings? Indeed, complications on their own may give the appearance of intractability, when in fact that complexity means more opportunities to recast and rethink inequality. An illustration of the latter is suggestive.

In May 1968 more than a thousand academic economists—Paul Samuelson, John Kenneth Galbraith, James Tobin, to name a few—endorsed a “national system of income guarantees and supplements” for the US. Milton Friedman, as well, supported an equivalent negative income tax. But how would we today respond to this assertion?

As long ago as 1968 over a thousand economists endorsed a national system of basic income guarantees—so it behooves us now to consider that an option as well to address growing poverty and income inequality in the US.

Objections rush forward: So much has changed since then! Congress is more polarized, the American public more fissiparous; we know more now, these days we have to be far more realistic; and the like. Or: We need to do better than old-time income transfers: a Universal Basic Income! Or: We sort of ended up with a patchwork of income guarantees, anyway. We may have been positioned to realize a (better) national income guarantee initiative during the War on Poverty, but not now. . .

Such feints may be hold as far as they go, but farther we must go. Why? Precisely because of the complications just listed. For these difficulties and like complications imply that, rather than not being positioned now to produce a national income guarantee, we may actually be in that position—it’s just that we don’t (yet) know it. In this view, those who don’t know are at their cognitive limits of thinking about complex and difficult matters, like income inequality, in the absence of better ways to recast “it.”

Which means: Even if we are positioned to implement an effective national income guarantee, we no longer know it to be so other than through the surprise that comes with having acted to that end. The just-so story—“It’d take a miracle for anything like this now to work here!”—becomes instead the surprise, “Who would have thought we were actually able to do this now!”

The latter response we associate with A.O. Hirschman’s Hiding Hand principle: Only by not-knowing in advance how very difficult some things are to achieve do we achieve them or something even better. Yes, here too there are no guarantees; yes, there are many recorded instances when the Hiding Hand has not worked. But either way, the central point for policy and management remains, to reiterate: Income inequality is not just difficult; income inequality is and has always been the result of difficulties, inexperience and not-knowing.


What does this add up to, methodologically? The challenge is not so much drawing implications at the level of that country’s income support program contrasted to this country’s income support program. The comparison is more across many really-existing income support programs, all operating under their own constraints of politics, money and egos.

Which ones perform better under similar constraints (or worse) that you face? That kind of pattern recognition is also needed for approaching income inequality, with a decidedly small-i in the Anthropocene.

Section II.9    Other typologies for the Anthropocene, Or making the best of linear thinking when it comes to “coordination”


I come from a policy analysis and management training that has little good to say about calls for “more coordination.” When having nothing else to say but feeling compelled to recommend more, then comes the “what we need is more effective coordination.” And who can be against effective coordination? Though too-often called for without a tincture of what to do, step by step and in real time. Like gold in seawater, coordination is impressive, but pointing that out is of scant use.

When I read criticisms that blame deaths or injuries in a disaster on the “lack of coordination,” I expect to see answers to two immediate questions: (1) can it be demonstrated that the lack of coordination did not arise because the responders knew—or thought so at the time—that they were undertaking activities just as urgent; and (2) can we conclude that the event in question would (not could, should, might or perhaps) have been better responded to had it not been handled the way it was (the classic counterfactual)? Rarely, in my experience at least, are answers attempted, let alone provided. (Note the counterfactual has a twofold would. The sociologist, Raymond Aron, asks critics of decisionmakers: “What would you do, in their place, and how would you do it?”)

Such details are of course difficult to summon, but that doing so is too rarely mustered leaves us to wonder just whose inexperience is revealed—the responders criticized or the clarion callers for more coordination.

And yet, the Anthropocene. . .

It borders on truism that the Anthropocene requires unparalleled coordination among the disparate populations and nations of the world. In light of these calls, coordination, this guide argues, is best understood as the chief limiting factor in policymaking and management under the conditions of high uncertainty, complexity, conflict and incompleteness. From this vantage point, “better coordination” is not the aim, but the limiting factor on being reliable and safe under Anthropocene conditions. Coordination is not an explanation, or a cause, or a rationale of better management and policymaking, but rather a test of the validity of that management and policymaking.

Coordination is limiting because no one knows how to coordinate when generalized across very diverse cases. It is chief because, even when better management has been undertaken, pertinent issues remain causally unclear (uncertain), variably numerous, different and interconnected (complex), interrupted and unfinished (incomplete), and under dispute (conflict). Yet calls for more coordination are unavoidable when the remaining uncertainty, complexity, incompleteness and conflict are treated as needing to be reduced but are not at that point reducible: “Thus,” it goes, “we need better coordination.”

Where so, then thus-coordination can be viewed as an empty signifier for our having not yet recast the issues. From the guide’s perspective, the call for more effective coordination is to determine whether we can better utilize the recast versions’ remaining uncertainty, complexity, incompleteness and conflict. That is: Recast the issue to see if the change in the amalgam of complex, uncertain, unfinished, and disputed is useful to you.

Recasting the coordinates.

How do we recast issues so as to alter their complexities more usefully without simplifying them for the purposes of coordination? One answer: Recasting issues so as to coordinate them better requires even more linear thinking under dynamic conditions (as thinking in terms of chief limiting factors is itself linear).

There is great irony in taking complexity seriously via linear thinking. This guide must quickly qualify: …when that linear thinking is in the form of multiple typologies considered together for analyzing uncertainty, incompleteness and conflict as well.

A two-by-two typology is easily criticized for simplifying reality. That, however, misses what has always been the latent methodological function of typologies (plural): to remind us that reality is indeed more complex than lines, boxes and lists can portray.

Multiple typologies are the norm in policy analysis and management, and to use them in sequence—one after another, different terms following upon different terms—is to render a major policy or management issue diversely granular for differing implications. Multiple typologies are not the pieces that complete a picture puzzle; they take a puzzle to see a different puzzle or puzzles already there.

–The typologies in my policy-analytic work come largely from sociology, political science, and organization theory. In the most practical sense, you can begin with any typology, the point being there is no free-standing macro, meso or micro start when it comes to reframing what is uncertain, complex, unfinished and disputed at the same time. The typologies I rely on include:

  • Different types of unpredictability, including measurable probabilities, unmeasurable uncertainties and unknown-unknowns (adapted from Andrew Stirling’s typology of incertitudes);
  • Different types of organizations, where production agencies for example differ significantly from coping agencies in terms of their observable/unobservable outputs and outcomes (J.Q. Wilson’s typology of agencies)
  • Different types of cases, e.g., “cases out there in reality” as distinct from, say, “the case emerging from your interaction with issues of concern” (Charles Ragin’s typology of cases)
  • Different types of large-scale technological systems whose centralized or decentralized operations vary as a result of component coupling and interactivity (Charles Perrow’s typology of high-risk technologies)
  • Different types of cultures for differentiating ways of life and policy/management orientations (the four cultures of Mary Douglas, Aaron Wildavsky and their colleagues)
  • Different performance modes—just-in-case, just-in-time, just-this-way and just-for-now—for the real-time high reliability management of large-scale socio-technical systems (a typology developed with my colleagues)

You may of course have different typologies, but even then the point remains: No major issue emerges unchanged from the seriatim application of these granularizing formats. So too for Anthropocene issues—be they inequality, poverty, war, the climate emergency, pandemics, healthcare or more.

In all this, though, remember the cardinal virtue in the application of multiple typologies. It is to move you from the myriad types of contingent (adventitious, idiosyncratic) factors at work affecting a major policy and management issue—again, societal, political, economic, historical, cultural, legal, scientific, geographical, philosophical, governmental, psychological, neurological, technological, religious, and whatnot. In the same move, it is to push and pull you to the many criteria with which to identify and describe the factors that are pertinent. These reframing criteria are the dimensions (the horizontal and vertical gradients used in differentiating the cells) of each typology.


It should be clear that no recasting resolves the amalgam of uncertainty, complexity, incompleteness and conflict that remains after (re)framing a complex policy and management issue. The question, again, is: Are we prepared to sacrifice one amalgam of uncertainty, complexity, incompleteness and conflict for another?

Which do we prefer, the one for today’s major mess or the one that remains after having shown “we can reframe or recast that in the following way. . .”? Are we prepared to over-sample the Anthropocene’s unpredictabilities and many different drivers in this comparison, given the fixation of so many others on the measurable and calculable as a way of generalizing away case differences? Note: we—the politically, culturally, geographically, economically, legally. . .diverse we.

This means that readers are best wary of conversation stoppers like “It is obviously a highly complex phenomenon that needs global coordination and cooperation as well as a holistic approach because the myriad interrelationships.” Even where true as far as it goes, it has to be pushed and pulled further. Each word is written as if it were solid, resolute, placed there to resist being pushed around or over, when in fact each is a cowpat to be stepped into so as to distract us from another fact, namely, different paths, as muddy as they are, actually have stiles for climbing over.

Section II.10     Wake-up calls make linear crisis scenarios V-shaped

The methodological issue.

It’s easy enough to take “right, center and left” and make a linear continuum: as when politics move from the right through the center into the left.

But the straight line becomes V-shaped, when the center is stretched and pulled away from the other two ends, as when the sequence, beginning-middle-end of a story, is made to sag, like a hammock.

Think here of the time-consuming catch-up to the contingencies that come our way in medias res, rendering beginnings long gone (or always disputed) and ends further off than our then-stories assumed at the start. This is what happens when wake-up calls identify intervening crises that stretch time and space out of shape between thought-to-be beginnings and thought-to-be endings.

The example of COVID.

By way of illustration, the COVID-19 pandemic was reported to us by several emergency managers as “a wake-up call” with respect to the interconnectivities and vulnerabilities among water, electricity, roads and other backbone infrastructures in Oregon and Washington State. In the view of a very experienced emergency management expert, “the one thing that the pandemic is bringing out is a higher definition of how these things are interconnected and they’re not totally visible”.

COVID-19 response made clearer that backbone infrastructures, especially electricity, are “extremely dated and fragile” in the view of other interviewees. Shortages in road staff in the aftermath of a vaccine mandate were mentioned by a state emergency manager for transportation as making it harder to undertake operations. COVID-19 responses also put a brake on infrastructure and emergency management initiatives already in the pipeline (e.g., preventative maintenance), according to multiple respondents.

The pandemic combined at the same time with other emergencies. A heat dome episode required a treatment plant’s staff not to work outside, but in so doing created COVID-19 distancing issues inside. The intersection of lockdowns and winter ice storms increased restoration times of some electrical crews, reported a state director of emergency management for energy. A vaccination mandate on city staff added uncertainty over personnel available for line services. Who gets to work at home and who gets to work in the plant also created issues.

“We struggled with working with contractors and vendors” over the vaccine mandate, said a state emergency manager for roads: “If we had a catastrophic disaster three months ago that would have been a challenge for us to work through.”

“All [COVID-19] planning happened on the fly, we were building the plane as it moved, we’d never seen anything like this,” said a state logistics manager of their early response. The interviewee added: “COVID is so unique and out of the box that we’ve developed rules and processes that we’re only going to use during COVID because they don’t make sense in any other disaster”.

In other words, the COVID-19 pandemic was a wake-up call to front-line managers about interconnectivities, but did not serve even as a dress rehearsal for what is to come their way in terms of other crises (including the much-predicted catastrophe of the magnitude 9.0 earthquake off the two states’ coastline).


Many crises are, this guide submits, V-shaped, notwithstanding their linear scenarios. So what?

Minimally, it means that table-top exercises based on beginning-middle-end crisis scenarios will inevitably be less V-shaped than needed. This is not to say the former are not useful. It is to say that the most useful table-tops are likely to be wake-up calls to more crises or different ones than thought pre-tabletop—and requiring now-attention as well.

The point is that we are again back to a key narrative discrepancy in crisis scenarios—between the stated urgency to DO SOMETHING on the one side, and the stated requirement to do so safely with respect to the ends in sight on the other side—while all the time recognizing that both requirements are urged and underwritten by the very same unpredictability at the very same methodological level of analysis, the system.

On one hand, it is argued we have to experiment even if it risks the limits of survival; on the other hand, being safe means no error should ever be the last trial. This is a discrepancy because it can’t be written off or talked out of; it has to be managed as one of the Anthropocene messes we are in. That indeed is the Anthropocene’s biggest wake-up call.

Section II.11   Chop-logics about risks, tradeoffs, priorities, and existential threats are not appropriate for the Anthropocene

When thinking in terms of risks, tradeoff and priorities is problematic.

As the Anthropocene is about many different large disasters, emergencies and failures, let’s start with responses to ones we’ve had. Professional emergency responders tell you each major disaster is different. While admitting commonalities, they insist the emergencies they have experienced differ because of each’s unique features.

This commonality-but-uniqueness tells us something significant about cookie-cutter thinking in terms of risks, tradeoffs and priorities when it comes to societal survival. (We will deal with the methodological dead-end of existential threats in a moment.)

Take a major policy issue—particularly as an emergency—and start analyzing it. Immediately, the talk becomes one about the risks involved, tradeoffs reflected, and the priorities call for when both are taken into account. Even trained professionals take for granted that risks, tradeoffs and priorities (RTPs) are the natural place to start analysis in a world of scarce resources and multiple urgencies. You certainly see this for the Anthropocene.

This guide, on the other hand, can’t imagine a more misleading and misguided way to analyze complex policy and management now and ahead. Risks, tradeoffs and priorities have a role to play as demonstrated in the guide’s preceding and following sections, but not as chop-logics that erase rather than highlight differentiations that matter for policy and management.


It’s because risks, tradeoffs and priorities are empirically far less in play for society’s critical services up to, during, and immediately after a major disaster. Three sets of empirical reasons for this being the case come forward.

Empirically yes, it’s obvious that major critical infrastructures—like those for electricity, water and telecoms—operate under budget and personnel constraints. Obviously, RTPs surface and at times take center-stage when path dependencies are as long as in society’s critical infrastructures.

Even so, there is a point at which infrastructure centralized control rooms (if present) will not tradeoff systemwide reliability for, say, for cost reductions in real time. Why? Because when the electricity grid islands, people die and the foundational economy seizes up. Preventing disasters, more routinely than not, is what highly reliable infrastructures do. (This is true whether the infrastructures are sustainable or not.) It is in real-time routine operations where “emergency management” starts, not in designated emergency planning and preparedness or pre-disaster mitigation programs.

Empirically, when a sudden catastrophe does happen, the pressing logic and urgency of immediate emergency response have been repeatedly demonstrated, namely: Restore the backbone infrastructures of electricity, water supplies, telecoms, and roads, right now when it matters the most. The tradeoffs, if any, are all secondary to that mandate. This is one commonality that very much matters and will continue to do so in the sudden and abrupt emergencies coming ahead in the Anthropocene.

In fact, there is no better acknowledgement of the importance and centrality of vital-service infrastructures that don’t tradeoff high reliability at critical junctures in their normal operations than the self-evident necessity of restoring backbone infrastructures as soon as possible when their normal operations fail.

Empirically, it is true that RTP-logic moves center-stage in longer term recovery after infrastructures fail, but only to the extent high reliability in service provision has yet to be restored to (a new) normal for the (sometimes altogether new) infrastructures.

Even so, really-existing analysis and deliberation during recovery are far messier than, e.g., “the risks, tradeoffs and priorities with respect to flood recovery are the obvious center of attention.” Entailed in the RTP chop-logic is the frequent assumption that the real problems in recovery are due to politics, dollars, and jerks undermining good work. The real problem, this guide argues, is that the chop-logic of “priorities follow from risks and tradeoffs” isn’t anywhere near reality of longer-term recovery. As such, being anti-empirical gets RTP logic only so far.

Methodologically, this empiricism means that the first-order differentiation in policies and management that are critically society-wide is not presumptively—or if you wish, not primarily—around RTPs only. Rather, it is differentiating that starting-point complexity in terms of the number of issue components, the different functions and roles of each component, and the interconnections between and among them. If afterwards, risks, tradeoffs and priorities are found center-staged, at least they will be unavoidably policy relevant by virtue of being contingently path-dependent, where not case specific.

Which leads to that other over-arching chop-logic: What about the Anthropocene’s “existential threats” that eclipse everything else?


The core methodological problem with existential threats are other existential threats.

At least two types of existential threats require attention in the Anthropocene: those with society-wide dread seeking to prevent them and those without that dread. As for the former, corporate greed and lies have yet to convince most people that it’s alright for: jumbo jets to drop from the air, cryptosporidium to poison urban water supplies, electric grids and lines to explode, and our huge dams to breach catastrophically.

It is notable, then, that the climate emergency has yet to elicit this type of social dread to prevent the precursors of climate change from occurring. This current failure to preclude the causes of chronic climate failure is reminiscent of the widespread and endemic threat posed by deadly medical errors in hospitals and clinics: While to be avoided, they are clearly tolerated in ways that blowing up a nuclear reactor is not.


To better highlight the competition for attention between these two types of existential threats, consider a case more fully discussed in later: the massive destruction of Oregon’s Central Energy Infrastructure (CEI) located in Portland, were the much-predicted magnitude 9.0 earthquake to occur in the Cascadia subduction zone off its coastline.

As a thought experiment, let’s say everyone in Portland understands the CEI is a concatenation of massive ticking bombs. Let’s also assume everyone there, as elsewhere, demands that planes in the air and water from the tap don’t kill them and that electricity lines don’t routinely collapse and electrocute people. Why does social dread work with respect to the latter in ways that it doesn’t for ticking bombs on Portland’s riverside? (Again, it would be difficult in this case to blame it all on politics, dollars and jerks for what is and is not socially dreaded.)

One answer is found in psychology: People are less in the grip of the Real with respect to the CEI. They aren’t caught up (as yet) in the same existential dread as when, say, a car careens towards them, or when they are screaming inside the plane hurtling downwards, or retching to death over the kitchen sink, or caught in power lines whipping and sizzling about.

Where, though, is hope for better policy and management in all this for the Anthropocene?

The notion that hope is rooted in neurology in ways that existential threats aren’t would itself be an existential threat, if many readers already didn’t know better.

For this guide, existential threats are better thought of, methodologically, as what’s left when hopes are bargained away to nothing. Hope, as philosopher Ernst Bloch said, is something not to bargained down. Hope is not traded off. It is disappointed; it doesn’t fail. In this guide, hopes are to existential threats as high reliability is to a critical infrastructure’s real time. Neither always work, obviously, but when that happens pressures for each increase.  

Section II.12    Analytic sensibilities and their policy relevance: poets A.R. Ammons, Jorie Graham and Robert Lowell

It would be a grotesque exaggeration to leave you, the reader, with the impression that “method” is the purview alone of policy analysis, let alone science and the social sciences. “There is no method but to be very intelligent,” poet and essayist T.S. Eliot wrote, by which I take him to mean “intelligence” being those unique analytic sensibilities we find in the humanities and fine arts. These too have policy relevance.

Read the better essays of George Steiner, John Berger, Adam Phillips—or if you will, Helen Vendler, Marguerite Yourcenar, Jane Hirschfield, Lydia Davis—and you encounter in each an analytic sensibility, sui generis. No need here for a collective or shared point of departure to understanding complexity’s implications for public and private!

There are times when the very different analytic sensibilities posed by the poetry of A.R. Ammons, Jorie Graham and Robert Lowell achieve actual policy relevance. I say this knowing it is outrageous to demand policy relevance from poets, let alone others in the humanities, but I am suggesting this is how you can read them as well.

Ammons and regulation.

–Policy types typically fasten to knowledge as a Good Thing in the sense that, on net, more information is better in a world where information is power. Over an array of accounts, A.R. Ammons insists that the less information I have, the better off I am—not all the time, but when so, then importantly so. (To be clear, he is not talking about “ignorance is bliss.”)

For those working in policy and management, how could it be that “the less we know, the more we gain”? More, in order to make our exercise more interesting, what would that mean when it comes to the heavy machinery called official regulation? Is there something here about the value of foregrounding inexperience—having less “knowledge”—as a way of adding purchase to rethinking government regulation?

–By way of an answer, let’s jump into the hard part—Ammons’s poem, “Offset,” in its entirety:

Losing information he
rose gaining
till at total
loss gain was
extreme & invisible:
the eye
seeing nothing
lost its
(that is a mere motion)
fanned out
into failing swirls
slowed &
became continuum.

You may want to reread the poem once more.

Part of what Ammons seems to be saying is that by losing information—the bits and pieces that make up “you”—you gain by becoming less separate, your bits and pieces slow down, fan out, spread into a vital whole. We empty our minds so as to attend to what matters—emptying the eye to have the I.

How, though, is this different from ignorance is bliss or, less pejoratively, seeking to know only what you need to know?

–When pressed by an interviewer, Ammons’s answer illuminates much about how knowing less is gaining more: “I’m always feeling, whatever I’m saying, that I don’t really believe it, and that maybe in the next sentence I’ll get it right, but I never do”.

Imagine policymakers and regulators, when pressed, recognizing that not getting it right today places them at the start of tomorrow’s policymaking—not its end but its revision of even the categories of “policymaking” and “regulation.”

Ammons, if I understand him, is insisting that in the compulsion to “get it right the next time around” there is more importantly a next time to make it better. Again, not just to make a specific regulation better, but to revise what we mean by “regulating.”

To recast (revise, redescribe, rescript, recalibrate) the categories of knowing and not-knowing is to make room for—empty your mind for—resituating the cognitive limits of “regulation.” The eye is no longer fixed on where it had settled before, but with a new focal point in sight/site. If you will, it is where the knowledgeable gives way to a freshened inexperience.

Jorie Graham and the climate emergency.

–No one would accuse Jorie Graham of being hopeful about the climate emergency. There is not a scintilla, not a homeopathic whiff, of environmental optimism, techno-social-otherwise, in the poetry I’ve read of hers.

Which poses my challenge: Can we readers nevertheless find something to move forward with from her recent poetry? Is there some thing that I can see of possible use in my own response to the climate emergency?

–In answer, consider the following lines from her book, Sea Change:

                                                                                   . . .the last river we know loses its
form, widens, as if a foot were lifted from the dancefloor but not put down again, ever,
                                                        so that it's not a
dance-step, no, more like an amputation where the step just disappears, midair, although
                                                        also the rest of the body is 
missing, beware of your past, there is a fiery apple in the orchard, the coal in the under-
                                                        ground is bursting with
                                                        sunlight, inquire no further it says. . . 

There’s that tumbling out and after of words and the turns of phrase that deepen the rush. Witness though how the rush of phrases bounces off and back from, in this case, the hard left-side margins and that right-side enjambment.

Some might call her rush of words a compulsion to continue but for someone with my background and training, it’s difficult not to see this as resilience-being-performed in light of the dark messages delivered.

Robert Lowell and alertness.

–“Design” is a trigger-word for this guide, as it often assumes one can macro-design the micro. Anyone who has tried to implement as planned knows how plug-and-play designs don’t work in complex policy and management, as contingency and context invariably get in the way. (It’s difficult to imagine two words scarier in English than business schools’ “designing leadership.”)

To see how this matters for policy and management, consider a late poem of Robert Lowell, “Notice,” and a gloss on it by Helen Vendler, the literary critic. Here’s the poem in its entirety, centering as it does around Lowell’s leaving an asylum after a manic-depressive episode:


The resident doctor said,
“We are not deep in ideas, imagination or enthusiasm –
how can we help you?”
I asked,
“These days of only poems and depression –
what can I do with them?
Will they help me to notice
what I cannot bear to look at?”
The doctor is forgotten now
like a friend’s wife’s maiden-name.
I am free
to ride elbow to elbow on the rush-hour train
and copy on the back of a letter,
as if alone:
“When the trees close branches and redden,
their winter skeletons are hard to find—”
to know after long rest
and twenty miles of outlying city
that the much-heralded spring is here,
and say,
“Is this what you would call a blossom?”
Then home – I can walk it blindfold.
But we must notice –
we are designed for the moment.

–I take up Vendler’s gloss when she turns to Lowell’s last line:

In becoming conscious of his recovery by becoming aware, literally moment by moment, of his new capacities for the most ordinary actions of life, the poet sees that ‘we are designed for the moment’—that our consciousness chiefly functions moment by moment, action by action, realization by realization. Biologically, ‘we are designed for the moment’ of noticing.

–What Lowell is doing in the last two lines is also revisiting, I believe, the second line, “We are not deep in ideas, imagination or enthusiasm” and making this point: The designs put upon us by ideas and enthusiasms differ from the noticing designed into us in at least one major respect: We notice the ideas-that-design because noticing is not an idea. It’s an alertness.

Knee deep in noticing is not being knee deep in ideas or enthusiasms because noticing is a kind of momentary watchfulness—“Is this what you would call a blossom?” Alertness in policymaking and management is, methodologically, first and foremost an analytic sensibility. Dutch bluntness is one such sensibility and has been a very good methodological tool in my research and interviewing. No apologies for the abrupt “I don’t understand” or “Why do you say that?”—and then keeping straight-faced and silent, waiting the interviewees out for responses.

Methods: Take-aways for Anthropocene analysis and management

Methods, like Counternarratives before it and Key Concepts and Analogies following, underscore how much of recasting complex issues depends on (re)focusing the granularity of the issues in question.

In this way, the methodological imperative, First, differentiate!, applies foremost to that admonition, Keep it simple! To adapt complications highlighted by the critic Michael Wood (2005):

  • When someone commends, “Keep it simple!,” you might respond by taking it more as sounding out what you think rather than affirming you don’t have to think.
  • “Keep it simple!” is one of those instructions that seems to know us without having to know each of us. The demand is to decide—Keep it simple!—without knowing if the demand is decidable.
  • When “Keep it simple!” is responded to with “Keep what simple?,” the former doesn’t begin to approximate a closed argument.
  • There is also a sense in which we can respond to “Keep it simple!” as if it were a parable about how to act. But the upshot is that, while it makes seeking out exemplars irresistible, exemplars are always easy for someone else to criticize.

More generally, this reflects the recognition that the level of granularity you see in a complex issue is not the only level or levels of use.

By way of another illustration, what could be more granular than retrofitting bridge-by-bridge against, say, future flooding or earthquakes? But methodologically, how do you choose which bridges to retrofit now or just ahead, when so many major ones could fail in the next Big One?

That question assumes the level and unit of granularity to be bridge-by-bridge. Change the granularity and answers change.

Retrofitting a bridge pre-disaster needn’t be a chancy wager on what might or might not happen to this or that bridge. Retrofitting is also managing latent interconnectivities between bridges and other infrastructures that become manifest during and immediately after the disaster. That inter-infrastructural connections will shift is far more predictable than this or that bridge will fail, unless retrofitted.

This means attention is crucial to the track record in retrofitting bridges before and after disasters, here and elsewhere. (Note the implication: Retrofitting bridges has to occur in order to have a track record to monitor and learn from.) Since there are real material and cognitive limits on controlling inter-infrastructural connectivity, doing more by way of managing the pre-disaster latency of interconnectivities buys you more time, if only during disaster response.

For instance, an interviewee with engineering and management experience told us their city water infrastructure was behind the electricity utility in the adoption of automatic shut-off valves. Bringing water systems up to power’s better practices, both systems connected to each other, is a way of managing latent interconnectivity in advance of disaster and what happens to the transportation network (including bridges) both depend upon.

This reframing from one element only—bridges—to multiple elements, including bridges, and their interconnections—is not a goal or end in itself, but a way of analytically arriving at granularities more tractable for policy and management.

Key Concepts

Section II.13    “What’s missing?” in this catastrophic earthquake scenario

Section II.14     Preknown-known-unknown and the implications for “unintended consequences”

Section II.15   The problem with adaptive learning and management in the Anthropocene

Section II.16    What to do when criticisms are spot-on, but the recommendations aren’t

Section II.17    Begin, rather than end, with the radical agenda

Section II.18   “Managing” risk and uncertainty, or coping better ahead with inexperience?

Take-aways for Anthropocene policy and management

Section II.13     “What’s missing?” in this catastrophic earthquake scenario

In answer, the imperative is not, “First, simplify!,” but “First, differentiate!” When it comes to a complex issue, what components? What functions? What interconnections? Equally important: Complex with respect to what? Complex under what conditions?

The chief follow-on question then becomes, as we saw in Part I: “What am I missing in front of me?” that could help in initially differentiating the issue, right off? This guide means “what’s missing right in front of me” quite literally.

Two illustrative examples from outside policy and management and their upshot.

What I’m missing right in front of me is coming to see in the lines from a George Meredith poem

In tragic hints here see what evermore
Moves dark as yonder midnight ocean's force,
Thundering like ramping hosts of warrior horse,
To throw that faint thin line upon the shore!

that “horse” and “shore” are anagrams, and then ask: To what effect or difference does this make for my reading? (E.g., as if “ramping hosts of warrior” reversed into a “faint thin line”.)

It’s also coming to see in the Hiroshige print–

that the waves of water and night-light are produced by the underlying grain of the woodblock, and then ask: To what effect or difference does this make for my viewing? (E.g., as if the female image is slipping side-ways out from the grain-waves.)

The vast majority of us, of course, are inexperienced and untrained in reading for anagrams or seeing the technique of kimetsubushi at work. We must instead be distracted to take at least a second look. For the inexperienced, the way to be sidetracked or distracted is by surprise—in this case, the surprise of finding the grain-wave pattern on your own or an oddity in the “ocean’s force” being contraposed by “horse” to “shore.” Even if afterwards Meredith’s lines remain mediocre and Hiroshige’s print astonishing, overlooking complexity is that simplification taken for granted which robs us of surprises that inform.

Note the most plausible reason for not seeing what is unseen—“Well, the reality is that it’s just not there at all”—turns out to be least plausible when living in a complex world of many components, functions and interconnections. In this world, new connections can and are to be uncovered all the time where not-knowing, inexperience and difficulty are ever present.

A thought experiment for better policy and management via What am I missing?

But just how do such surprises move us from looking onto unknown-unknowns (without knowing it) to seeing the unknown and knowing that? What conditions for or about surprise need to be in place to answer, What am I missing right in front of me?

The following thought experiment will seem silly in light of all the advances in neuroscience about how the brain works. But its virtue is in pinpointing the key condition for answering our question.

Assume you know nothing of the brain’s structure or neuroscience. Assume then your brain is a chamber initially holding two kinds of spaces: filled spaces of what you know and empty spaces for what you do not know. Suppose, also, that at times each filled space emanates a beam of bright light that, when combined with beams of light from the other filled spaces, produce a brilliance so intense in the brain that the only shapes left visible are the dark cavities that this concentrated light did not reach.

Suppose the reverse also happens (this famously proposed by psychoanalyst, W.R. Bion): Each empty space emanates at other times a penetrating beam of darkness so absorbing that, when combined with the blackening beams from other empty spaces, the only shapes left visible are the lighted cavities the dense blackness did not reach.

Now, think of the dark cavities that persist even in the lighted glare of what your brain knows as what it really doesn’t know, while the lighted cavities that persist in the blackness of what your brain doesn’t know are what it actually does know.

Compare now the two sets: initially, filled/empty and afterwards, lighted/darkened. The archipelago of densely lighted and densely dark need not correspond to the original filled and empty spaces. That is, your brain thought it knew some things which it now sees it didn’t know; and some of what it thought it didn’t know is shown now to be what it knew all along.

This thought experiment suggests that our brains, in order to move from “not-knowing” to “seeing the unknown” requires at least moving from what we thought we knew or didn’t (those filled and empty spaces) closer to what we actually do and do not know (its cluster of lighted and darkened cavities).

If so, then this is the question: Why would anyone believe that you can shift from looking onto unknowns without knowing they are there (the notorious unknown-unknowns) to seeing unknowns in the Anthropocene and knowing it, if you have not demonstrated beforehand the realization that you didn’t know what you thought you knew, you did know more than you initially thought, or both? A track record in doing so, combined with the risk/uncertainty discriminations in earlier sections, are key to developing new policy optics for the Anthropocene.


Now turn to an illustration of how this not-knowing and knowing what’s missing work in policy and management. So as not to make this easy, consider what many call the most catastrophic natural disaster in the US: were it to happen, a magnitude 9.0 earthquake or greater in the 800-mile long off-shore Cascadia subduction zone in the Pacific Northwest. Here, I focus on research and work at one site and its affected infrastructures: Portland, Oregon.


A great deal of seismic attention and concern has been directed to the state’s Central Energy Infrastructure (CEI) hub in Portland. (The CEI hub is instrumental to Oregon and not just the city.) It is “a six-mile stretch of the lower Willamette River where key liquid fuel and natural gas storage and transmission facilities and electricity transmission facilities are concentrated.” It is an area, however, subject to lateral spreading, ground shaking, and liquefaction, among other physical vulnerabilities (pace tsunamis, hazardous liquids explosions and fires, high voltage line collapse). Much of the infrastructure has not been brought up to seismic standards and instead was built with what are today very major seismic deficiencies.

The CEI hub is, in other words, chronically vulnerable were earthquakes to occur and it is recognized that “to minimize extensive direct earthquake damage, indirect losses, and possible ripple effects, substantial improvements to the critical energy infrastructure are necessary.” “We know the earthquake is coming. We know we have to take steps to address this,” policymakers and legislators admit and studies agree.

Much attention has been directed to mitigating the severity of the vulnerabilities. New seismic standards have been brought into effect as have prohibitions on expanding CEI hub tank farms, better containment barriers have been studied, retrofitting is underway, automatic shut-off valves are being adopted, alternative supply chains and better emergency responses are actively modeled or prototyped, and proposals have been offered for increasing/relocating the storage capacities elsewhere and closer to communities affected. Not enough has been done, but then again it is important to recognize that a magnitude 9.0 earthquake would test any “built-to-last” scenario.

At which point comes the surprising realization

It’s easier to imagine a M9 earthquake scenario both obliterating a hardened CEI hub and unleashing catastrophic fuel spills, fires, landslides, death and destruction than it is to get rid of these structures before it’s too late.

It’s easier to imagine that a Presidential Disaster Declaration would be immediately issued, that competent personnel would be identified and transferred into the state to take over from infrastructure staff who don’t show up because they are trying to save their families, that local people will only figure out what to do after they see what’s left to work with, and that interconnected infrastructures, just like the communities, would be islanded off from each other indefinitely—it’s easier to imagine that and imagine far worse than it is to get rid of the CEI hub and imagine ramifications of the alternatives.

So much for the benefits of imagination in answer to “What are we missing?”

In other words, think a bit more about what they don’t—can’t?—see right in front of them, namely:

What better way, save war and the plague, to bring governments in the Pacific Northwest to their collective knees than ‘‘solutions,’’ like those pre-disaster mitigations and better preparedness plans? It’s as if the existing economies are so taken for granted that their believers see no choice—no alternative—but to be catastrophic now on unprecedented scales.

This may be knowledge of sorts, but it is not realism for the Anthropocene.

Section II.14     Preknown-known-unknown and the implications for “unintended consequences”

If we start with the commonplace that analysis and deliberation center around what is known or not, then the boundaries of the known blur not just into the unknown, but also into the preknown.

The latter is the preexisting knowledge that one is born into and “takes for granted.” In his essay, “The Well-Informed Citizen,” Alfred Schütz, the sociologist, described it this way:

The zone of things taken for granted may be defined as that sector of the world which, in connection with the theoretical or the practical problem we are concerned with at a given time, does not seem to need further inquiry, although we do not have clear and distinct insight into and understanding of its structure. What is taken for granted is, until invalidation, believed to be simply “given” and “given-as-it-appears-to-me”–that is, as I or others whom I trust have experienced and interpreted it. It is this zone of things taken for granted within which we have to find our bearings. All our possible questioning for the unknown arises only within such a world of supposedly preknown things, and presupposes its existence.

One consequence of ignoring the blurred borders of preknown, known and unknown is: We end up acting as if it does not matter that it takes preknowing and knowing-enough to avoid entering into the unstudied conditions of the unknown. If Schütz is right, the preknown is where we “find our bearings” with respect to the known and unknown.

So what?

It turns out that all the talk about “unintended consequences of human action” is itself unintentionally simplistic:

  • “Unintended?”: When the preknown is the platform that has nothing to do with intentions but that enables us to take our bearings so that other factors in the known and unknown carry the weight of argument about “unintended consequences.”
  • “Consequences?”: Rather than that blurred borders of knowing, preknowing, and not-knowing we chalk up also to contingency and exigency.
  • “Unintended” + “consequences”?: When too often what we are really dealing with are contingencies with disproportionate effects about which we have little or no causal understanding.

To rephrase the point, “unintended consequences of human action” is a coherent phrase only by missing the rest of that overwritten palimpsest called “human action,” off of which the phrase is cobbled together for the purposes of policy and management. More positively, it is that policy palimpsests and related ones we should be studying, not some floating signifier call “unintended consequences” (more on policy palimpsests in Section II.19).

Section II.15    The problem with adaptive learning and management in the Anthropocene

When I started in rural development in the early 1970s, one challenge was to manage for optimal ignorance:

Professionals should manage to the point where what they are learning is not worth knowing. Managing for optimal ignorance got a good deal of press from a range of writers at that time, notably social scientists Warren Ilchmann and Norman Uphoff, development scholar Robert Chambers, and Peter Berger the sociologist. (Read Chambers who remains evergreen!)

The appeal of optimal ignorance waned when I implemented projects that I had helped plan. I’d find myself mulling over what my first boss, the district commissioner, told me on arrival in Botswana: “A piece of advice, my dear boy. Either stay in the kitchen all the time or never go in.” Nothing major gets implemented as planned, and only by staying in implementation–later, management–did I appreciate how little I knew with my masters education in public policy analysis.

My view now is that “optimize” should be banned, as a term, from policymaking and management.

Like the dog returning to its vomit, optimality criteria are never satisfied with the uncontrollability of contingency. But I didn’t fully understand that until later when I started researching large critical infrastructures, their control rooms and control operators.

These large sociotechnical systems are so complex that their managers cannot really “know” what are inevitably unstudied conditions and their real-time inexperience and difficulties are permanent reminders of this. On the other hand, optimizers with whom I’ve worked seem to think it’s better they burn the building down to save the rest of us the trouble of repairing it.

Yes, of course, studying and adapting to unknown-unknowns are important and that’s why the idea of “chipping away at ignorance” is not all hubris.

But control room operators are attuned to stay out of unstudied conditions not because some things are not worth knowing but for the opposite reason: No way can these professionals afford to be in prolonged ignorance when the safe and continuous provision of critical services, like water and electricity, is paramount. “[I]f the grid fails and there are blackouts, people die,” one infrastructure executive told us. Control rooms put up with uncertainties they can live with in order to avoid unknown unknowns they can’t or mustn’t tolerate.

But you press: What could be more respectful of complexity than managing and learning adaptively?

Change course as uncertainties are reduced and more is learned. No one can be against learning, right? Even when that is true as far as it goes, it surely doesn’t go far enough.

A story from my time as an advisor in Kenya helps clarify. I had oversight responsibilities for a handful of integrated rural development projects in that country’s arid and semi-arid districts. One of the worst projects, in my view, was fixed around soil and water conservation measures.

You asked villagers there what their three most important development priorities were and they’d say: water, water, water. Water for drinking, water for cooking, water for their livestock, water for everything that mattered. Here instead the donor was spending a fortune on ditches and bunds to prevent dryland erosion on the hillsides primarily for crop purposes, without any direct increase in water supply for the households and livestock.

Villagers just wouldn’t “participate” in the project: Food-for-work schemes didn’t work, giving them hoes or such didn’t work, nothing worked. Later on, I tracked down one of the project’s designer and asked: “Why ever was the project designed that way? Absolutely no one there was for soil and water conservation.” It was like he’d been waiting years for someone to ask him just that. He leaned forward, “But who can be against soil and water conservation?”

So too for managing adaptively: Who, really, can be against it?

That would be like arguing against norms of rationality, the scientific method or evidence-based policymaking, worse yet, against trial-and-error learning. And yet, as with soil and water conservation and other projects, we must press: managing adaptively for what? With respect to what scenario granular enough for its details to be evaluated?

Furthermore, what is often desired is its own scenario of high reliability water, water, water—reliable water for urban use, for agricultural use, for ecosystem restoration and the environment; for ports, for shipping lanes, for recreation, for hydropower, for. . .you name it, reliable water is needed. And a very great deal of that provision depends on large-scale water supplies, electricity supplies and other infrastructures—which is why I kept coming back to their importance in this guide.

This mandate for system reliability and safety will not go away in the Anthropocene nor could it.

Even where systems must be—repeat, must be—smaller, more decentralized and more sustainable, those systems too will be managed as if peoples’ lives and livelihoods depend on it—because they do.

Obviously, operators of large or small infrastructures (again, not all infrastructures have control rooms) are from time to time pushed into the unknown-unknowns by contingent events. It turns out, however, that to ask really-existing infrastructure operators—“What if the unimaginable happened?”—is not to ask something new or unusual. They are always asking themselves what-if scenarios, where the details matter.

This contrasts with the faith-based “Failure is not an option” that is to get us out of the Anthropocene crises we’re in. What-if scenarios that specify the “with-respect-to’s” require deep knowledge and realism—far more than, say, the much-touted “imagination” or other admonitions like “innovate or evaporate”.

More, is toleration of error adaptive capacity? Indeed, the kind of complexity discussed in this guide implies that some kinds of accidents and errors—including sabotage—are going on that are not noted by anyone. We are already tolerating a level of “mistakes” for which we are not managing, which raises the issue of just what accident level we are putting up with unknowingly as part of routine operations.

Only later in my career did I understand that the test of efficacy here is not ‘‘Have we designed a system that can be managed?,’’ but rather: ‘‘Is this a system we can manage to redesign as we go along?’’ Management is in excess of design and technology.

For control operators, real time is too important to experiment in when their first error ends up being our final system trial. The last thing we want is our airplane pilots “to embrace failure” mid-flight, notwithstanding all the anodyne business and management articles on the virtues of error and failure in unstudied conditions. Too much of that privileging borders on priestcraft and miracle-mongering for the Anthropocene.

Section II.16   What to do when criticisms are spot-on, but the recommendations aren’t

The problem.

Most readers, I think, have had this experience: You’re reading an utterly convincing analysis of a major policy issue—when suddenly you are blindsided by the recommendations section. “Where did these come from?” you wonder.

Yes, it’s a major contribution to detail and document, say, the very real land problems in Kenya; but when did “massive land reform” follow as a nuanced solution? Yes, the greenwashing Big Polluters continue to damage and harm the environment; but when did banning fossil fuel, immediately, supersede case-specific realism? How did “We just need the political will to do so” become even an option, when it’s self-evident that too much political will—”we need to do this! that! those! these!—and you, you especially need to do more!”—sources so many of the difficulties in falling short of the needful?

A realization and proposed way forward.

Convincing criticisms that led nowhere once exasperated me. It took too long for me to realize that my “These critics should know better” mirrored their “We should have the political will to do better” No amount of my own “they should know” will change their policy advocacy. Nor do I have standing in saying policy advocates must not undertake critiques grounded first and foremost in their moral and ethical principles.

Rather, drawing recommendations from their analyses is the readers’ responsibility. I’m the policy analyst here, whatever else the authors are doing. I may not be smarter, but my framework—this guide’s framework—differentiate matters differently than they do. I also like to think I have something to add, both by way of advice to the policy advocates and with respect to the same issues about which I am as worried as they and for the very reasons they have established.

How so? First, I’d ask policy advocates to push each recommendation further with, “Yes, but…?” Yes, even if your recommendation holds, does it “hold” because it doesn’t go far enough?

An example.

Return to Big Polluters with their smoke-and-mirror commitments. I’m talking here about their “net-zero emission” schemes, where their emissions in one place are to be offset—promise!—by their securing equal emission reductions in other places. Think of the medley of carbon offsets, carbon capture-and-storage, direct air capture of carbon dioxide, and carbon markets, among others, whose adoption enables the polluters to continue to pollute ever more here while not, supposedly, there.

Who these Big Polluters are and how their obfuscating schemes is documented in The Big Con: How Big Polluters are advancing a ‘net zero’ climate agenda to delay, deceive and deny (2021, by Jesse Bragg, Rachel Rose Jackson, and Souparna Lahiri for Corporate Accountability at: https://www.corporateaccountability.org/wp-content/uploads/2021/06/The-Big-Con_EN.pdf).

The policy analyst’s problem starts with report’s recommendations, not with the spot-on analysis preceding them. “The cross-sectoral solutions we need already exist, are proven, and are scalable now (see “Real Solutions, Real Zero” in the resources Box),” presses the report. Going to box’s link leads to another document with examples of climate change solutions—its term. “Many of these are already implemented at local and national levels. Several of these measures can be easily implemented directly, while others require international cooperation.”

Fair enough, but then come the listed recommendations, including:

  • Drastically target the excessive and wasteful consumption of corporations and wealthy elites.
  • Ensure just transitions across all sectors that ensure workers are able to move into new, secure green jobs.
  • Create an immediate moratorium on all new fossil fuel extraction.
  • Leave the ecological integrity of natural ecosystems unharmed and conserve biodiversity.
  • Vastly scale up ecological restoration to recover natural forests, peatlands, and other degraded ecosystems for both climate and biodiversity. .  .
  • Immediately ban expansion of airports, particularly in developed countries. . . .

Now, argument by adjective and adverb is not confined to policy advocacy (I’ve done my share). But no number of “immediate,” “drastically,” “vastly” and such will stop the policy analyst and actual-living others from pushing further to “Yes, but”: Just how drastic or vast is this drastically and vastly? Immediately means immediately, but you can’t mean immediately?


Note again the point of “Yes, but” is not to stalemate action but rather to locate the policy or management relevant granularity.

In this example, that level of granularity reflects the where and under what conditions moratoria on new fossil fuel extraction, bans on airport expansions, and the efficacies of different “targets” on wealth consumption have worked as really-existing practices to be modified and improved upon by others—and under constraints of politics, money and egos similar to or even worse than your own case.

More, the second you differentiate is the second you begin treating seriously the unintended aftermaths of implementing blanket recommendations and macro-design “solutions. Which leads us back to the “more political will” the authors call for, the question now becoming: Have we already wasted finite political will when it comes to stopping Big Polluters from destroying even more? Or from the other side, Are we in a position to do something major but not know it?

To ask the latter is to take us back full circle back to uncertainty and complexity, but as in: “the varieties of revolution do not know the secrets of the futures, but proceed as the varieties of capitalism do, exploiting every opening that presents itself”—to paraphrase political philosopher, Georges Sorel. To revert to the earlier major point: Where is there a track record in people seeing they didn’t know all that they thought they knew and actually knew more than they had thought about, in this case, net-zero emissions or some such?

Section II.17    Begin, rather than end, with the radical agenda

A usual ending.

The Yale Law Journal has published a significant article, “Building a Law-and-Political-Economy Framework: Beyond the Twentieth-Century Synthesis,” by Jedediah Britton-Purdy, David Singh Grewal, Amy Kapczynski and K. Sabeel Rahman (2020, 129: 1784 – 1835). It concludes with a call for action (here quoting without the embedded footnotes):

If it is to succeed, law and political economy [i.e., the framework in the article’s title] will also require something beyond mere critique. It will require a positive agenda. Many new and energized voices, from the legal academy to political candidates to movement activists, are already building in this direction, calling for and giving shape to programs for more genuine democracy that also takes seriously questions of economic power and racial subordination; more equal distribution of resources and life chances; more public and shared resources and infrastructures; the displacement of concentrated corporate power and rooting of new forms of worker power; the end of mass incarceration and broader contestation of the long history of the criminalization and control of poor people and people of color in building capitalism; the recognition of finance and money as public infra- structures; the challenges posed by emerging forms of power and control arising from new technologies; and the need for a radical new emphasis on ecology. These are the materials from which a positive agenda, over time, will be built.

I agree and ask you to do the same for the following thought experiment.

Assume I start my own article with the above quote.

Where do my subsequent paragraphs lead? In what directions do I drive what is now my quoted agenda? To make this interesting, I sketch five extensions of this guide that most contrast, I believe, with what readers take away from the original article:

  1. Instead of feeling overwhelmed by the enormity of the implementation challenges, I’d ask: Where are the agenda activities already underway? What are the better practices there that can be modified and applied here, or if not here, then elsewhere? The point is that the agenda is too good to be restricted to the US only.
  2. Instead of thinking the agenda stands or falls on how key terms (capitalism, power, democracy. . .) are defined, the better practices identified in #1 do just that, i.e., entail the ends sought by the means used. Here, behaving democratically is with respect to these practices to achieve those outcomes. There, power is supposed to be controlled by these means for those ends; elsewhere, power is having to manage or cope ahead in these rather than those ways as control is not possible (if it ever was).
  3. Instead of starting by prioritizing what do first, second and so on, I’d stay with the mess of interconnections and see where they lead. Think of the agenda as a composite argument read off a very layered and overwritten palimpsest of earlier arguments about power, capitalism, democracy and the rest. Each new argument is assembled from older effaced ones; even when each argument seems connected and integrated, it is in fact an unstable composite. Resurfacing earlier erasures is a way to signal where my paragraphs can go instead. As in: toward those avoided cases where capitalism looks less like control and more like negotiation and bargaining among, yes, unequals.
  4. Instead of trying to reduce the agenda’s uncertainties and complexities, I’d see if there were analogies that recast the tasks ahead usefully. Return to that longstanding analogy of “being at sea,” as in challenges likened to: keeping your balance while mucking across a shoal, treading water with no bottom to touch, tacking into unpredictable winds, repairing the ship at sea only with what is at hand, no safe harbor to return to in the storm, or keeping your head above the rushing tide-race. That to my mind is the view-scape within which or on which the positive agenda, over time, will be based.
  5. Instead of seeking to integrate the agenda into a single reduced-form narrative, I’d look for narrative discrepancies that indicate where other more useful narratives may be complicating matters. For instance, it’s not surprising as someone who writes on critical infrastructures that I’d trip over the conflation of stock (e.g., facilities) and flow (e.g., money to run the facilities) in the quote’s reference to “infrastructures.”

Such, in short, would be the gist of Results section in my proposed article.

But what follows from the Result section?

I’m in no position to sketch the article’s Conclusion, but the first point in the Discussion section following the Results is obvious to me: Why accept anything less radical than the starting agenda?

The standard retort of gradualism and incrementalism—“Well, here we want something more modest having greater chances of being achievable”—makes sense only if other really-existing practices in like situations weren’t more successful. Are we expected in the Anthropocene to be the experts in global interconnectivity before undertaking that canvassing of specifics? I don’t think so and this guide most certainly hopes not so. To act otherwise is to invite in the modern-day versions circle-squarers, angle-trisectors, and calendar reformers.

In other words, the question remains as it has been for a very long time: What are the really-existing better practices across a wide spectrum of really-existing cases that work to achieve betterment? Another virtue in reviewing actual practices as widely as possible is demonstrating those cases where that the latest universalized fix—Stop this! Do that!—is the last thing people there are worrying about.

Section II.18  “Managing” risk and uncertainty, or coping better ahead with inexperience?

Let’s deal with each topic separately.

“Risk management” and Alan Greenspan’s tenure at the US Federal Reserve.

Given the uncertainties the Fed was tackling, Mr Powell [chair of the US Federal Reserve] argued in favour of caution on rates policy and a ‘risk-management’ approach, praising Mr Greenspan’s 1990s approach of waiting for clear evidence of higher inflation before moving rates higher.

(accessed online on August 21 2021 at https://www.ft.com/content/e492d82e-a7a4-11e8-926a-7342fe5e173f)

For this guide, inexperience has to be managed because it is often a proxy for not-knowing. How this matters is illustrated by the example of Alan Greenspan as chair of the Federal Reserve and his risk management approach. The implications are unsettling in ways not usually supposed and not just with respect to central banks.

Starting point and background

Greenspan presented a major paper, “Risk and Uncertainty in Monetary Policy,” to the American Economics Association and published in the Association’s Papers and Proceedings of May 2004. As he and his confrères held, the pre-eminent focus of the Fed was the maintenance of price stability in the face of turbulent events and uncertainty:

The Federal Reserve’s experiences over the past two decades make it clear that uncertainty is not just a pervasive feature of the monetary policy landscape; it is the defining characteristic of that landscape. The term, ‘uncertainty,’ is meant here to encompass both ‘Knightian uncertainty,’ in which the probability distribution of outcomes in unknown, and ‘risk,’ in which uncertainty of outcomes is delimited by a known probability distribution. In practice, one is never quite sure what type of uncertainty one is dealing with in real time, and it may be best to think of a continuum ranging from well-defined risks to the truly unknown.

One expects risk and uncertainty because the “economic world in which we function is best described as a structure whose parameters are continuously changing”. Greenspan took this uncertainty, coupled with the demand to ensure price stability in the face of it, to mean that the Fed could not rely on a fixed approach:

Some critics have argued that [our] approach to policy is too undisciplined—judgmental, seemingly discretionary, and difficult to explain. The Federal Reserve, they conclude, should attempt to be more formal in its operations by tying its actions solely, or in the weaker paradigm, largely, to the prescriptions of a simple policy rule. . .But at crucial points, like those in our recent policy history (the stock market crash of 1987, the crises of 1997-1998, and the events that followed September 2001), simple rules will be inadequate as either descriptions or prescriptions for policy.

Action, accordingly, must be developed with and within context, as no single or simple rule “could possibly describe the policy action to be taken in every contingency”. “The world economy has become too complex and interlinked,” he amplified in his 2007 memoirs.

Upshot and implications

All the above makes sense—and eminent sense for the Anthropocene—were it not for the blisteringly obvious fact that THE APPROACH DID NOT WORK when it came to events leading up to and during the 2008 financial crisis. The financial crisis’s estimated $19 trillion in household wealth destruction hugely damaged Greenspan’s reputation and the approach he fostered as Fed chair.

And yet….

When you peel away the pre-crisis hagiography and post-crisis demonology around Greenspan and his Fed tenure, that management approach still looks reasonable for accommodating risk and uncertainty: That is, as many others have summarized, don’t get caught in analytic rigidity, remain flexible, prepare for surprise, and avoid theory in favor of tested practice when managing risk.

What’s wrong is that the approach failed, utterly, to demonstrate that they were actually managing risk in the sense of having a track record of experience in responding to, if not actually realizing beforehand, that they didn’t know what they thought they knew. Further, they may have known more than they thought, but we will never know that from the existing record. Any such track record was nowhere evident in the self-regard Fed risk managers held themselves when “managing” risk and uncertainty.

Only well after the financial crisis did Greenspan admit publicly anything like having had to cope in the face of unknowns. In a 2013 interview he conceded, “when I was sitting there at the Fed, I would say, ‘Does anyone know what is going on?’ The answer was, ‘Only in part’ I would ask someone about synthetic derivatives, say, and I would get detailed analysis. But I couldn’t tell what was really happening”.

This implies that future histories of the 2008 financial crisis must extend the domain of inexperience considerably beyond that much-reported dearth of sophisticated mortgage buyers. (Anyone, for that matter, would be inexperienced when finding themselves in unstudied financial bubbles at that cognitive edge of knowledge and unknowledge.) I am suggesting policy and management will have to credit more of the 2008 financial crisis to inexperience than to the low, mean cunning of overpaid banksters aided and abetted by thralldom to Efficient Markets and Value at Risk.

In fact—and this is the sobering part—if inexperience was a very real and active agent then, we should be doubly worried now. It is exactly the lack of experience with quantitative easing, unprecedented bailouts, and sovereign debt negotiations along with their uncertain, if not unknowable consequences, that drives post-2008 responses and now (post-) pandemic responses by the central banks of the world’s major nations.

But to what to do now, as you read this?

As the reader should expect by this point, the guide’s answer to the preceding is: First differentiate! Differentiate, for example, the sovereign debt crisis since 2008. Start by way of illustration with a quote:

Zambia defaulted on interest payments to some of its private lenders in November 2020 when private creditors refused to suspend debt payments. In February 2021, Zambia applied for a debt restructuring through the Common Framework, but little progress has been made on the negotiations as large private creditors, such as BlackRock, have so far refused to reach an agreement on debt relief. BlackRock, headed up by Larry Fink, is the largest of a number of bondholders who are refusing to cancel Zambia’s debt, despite lending to the country with interest rates as high as 9% (in comparison to wealthy countries like Germany, UK and USA who were given loans at 0-2% interest in the same time period) potentially making huge profits. Debt Justice estimates that BlackRock could make up to 110% profit if repaid in full. Meanwhile, Zambia is experiencing devastating impacts of the climate crisis such as flooding, extreme temperatures and droughts, which are causing significant disruption to livelihoods and severe food insecurity. Unsustainable debt levels mean the country lacks many of the resources required to address these impacts. This decade, Zambia is due to spend over four times more on debt payments than on addressing the impacts of the climate crisis.                                                                                     


It’s also been reported that only two nations, the USA and PRC, have GDPs greater than the wealth managed by BlackRock, whose assets at the time of writing have been around $10 trillion. It’s also said that the ten largest asset-management firms together manage some $44 trillion, roughly equivalent to the annual GDPs of the USA, PRC, Japan and Germany.

Now, it’s always good to check the numbers, be they for Zambia, the globe or points in between. But let’s assume the orders of magnitude are correct. It would then be more accurate to say that BlackRock could be managed for the better, because, well, BlackRock is actually being managed in ways the sovereign debt crisis can’t. (Think BlackRock’s C-suite, starting with Larry Fink.) Instead of trying to “solve” the sovereign debt crisis, why not start with BlackRock being managed differently? After all, it rose to an undisputed shareholder superpower only after the last financial crisis of 2008. Nothing is set in stone here.

In other words, think of BlackRock recast as the global financial crisis underway at the time of writing and the “sovereign debt crisis” as its ploys to get the rest of us to believe otherwise. We know exactly who benefits from placing the blame on the Government of Zambia’s fiscal and monetary management, when the global behemoth, BlackRock, is managed even worse in terms of self-interest.

Better coping ahead with inexperience.

If the focus turns to one of managing inexperience rather than “risk” per se, it turns out that inexperience has been identified as a major factor in other financial crazes than that of the 2008 financial meltdown. To understand this, moreover, helps recast what looks first to be a problem of managing risk and uncertainty into a problem of better coping ahead with the inexperience in financial bubbles.

Case material.

Turn to an account of the 1720s financial fiascos of the South Sea Bubble in Great Britain and France’s counterpart, the Mississippi Scheme, by historian Frederick Scott Oliver in his 1930-1935 The Endless Adventure. The three volumes of The Endless Adventure—long out of print, dated in some of its language, but still worth reading—were well-regarded by the reading public and luminaries. I quote at length a wonderfully high-alpine passage to draw out this key role of coping better with said inexperience:

At the present day the simplest investor or the most junior Treasury clerk would be suspicious of such over-generous promises; but in 1720 even less was known than is known now of the mysterious laws that control the currents of a nation’s prosperity. Our own generation, as it glances backward and downward into the eighteenth century, can of course discern without difficulty the points at which an earlier race of statesmen blundered off the highway and fell among brakes and briars and morasses. Viewed from our present altitude, the road of safety shows so white and unmistakable in the foothills below us that we find it hard to understand how men of intelligence and probity could possibly have allowed their steps to stray. The most facile explanation is corruption, or else of shameful ignorance.

Our amazement, however, will be lessened, our censure may be tempered, if we pause to consider a nearer past, or if we turn our gaze forward and upward, where the as-yet-unbeaten track of the twentieth century winds out of sight among mists and mountain peaks. What lies immediately behind us is only trifle less obscure than what rises up in front. We are not yet come high enough to survey the last fifteen years in a flat projection. We have travelled, as it were, by a forest path very baffling to an ordinary man’s sense of direction; by a steep ascent, at times darker than twilight, with many a corkscrew turn and hairpin bend. We can recall in a confused and broken memory that we have come through a period of miscalculations without number and that, time and again, the predictions of the wisest statesmen and economists have been proved false by events that followed shortly after. Our guides misled us, though they were for the most part honest men who knew by rote the maxims of their financial craft as it was practised by the civilised world at the beginning of the year 1914….

But new and undreamed-of conditions produced universal derangement. Discredit fell upon the most approved principles, and so many strange heresies appeared to thrive, that mankind, panting for a new heaven and a new earth, was not unwilling to listen seriously to new guides, who vaunted the efficacy of specifics hardly less fantastic than the Mississippi Scheme and the South Sea Bubble. Those new guides were possibly as honest as the old ones, but it was certainly no less dangerous to follow where they beckoned. In doing so how often have we lost our way and been obliged painfully to retrace our steps! And yet it is not unlikely that, a hundred years hence, every political writer, every man of business, every intelligent undergraduate will be able to discern clearly the causes of our recent and present troubles. The road to safety may then appear to them so obvious, that our own failure to find and follow it will excite not only their amazement but their suspicions. They may find it as hard to believe that our faults were nothing worse than the innocent blindness of inexperience, as we do to believe that the French and English nations in the year 1720 were not criminal lunatics, or as we do to acquit the statesmen of those two countries of complicity in a series of gigantic frauds.

It’s Oliver’s reiterated honest men duped by inexperience that deserve a second look: Does this mean our finance officials, like Greenspan later, should get a free get-out-of-jail card because they are inexperienced?

Stay with Oliver a bit longer. For him, politics as governing requires apprenticeship because governing is, well, complex: “Methods that experience and necessity have evolved by slow degrees are bound to be complicated…”, and it takes time to learn what is complicated and how to deal with them. Sadly, much of what passes for good governance conspires to distance the politician (and senior officials) from gaining more experience about the complexities:

To-day, when a man of business or a cabinet minister is in doubt, or is at issue with his colleagues, he calls for a report. A host of technical advisers stands at his beck and call. A vast machinery lies ready to his hand. . . .[N]early everything he learns is learned at second hand, so that the true nature of the problem is rarely visible to his eyes. When his colleagues ask him questions—sometimes pertinent and sometimes foolish—he can neither satisfy them out of hand with sound reasons, nor can he answer them according to their folly. He promises a supplementary report; and so the game goes on.

We know that few investors or traders in the mid-2000s leading up to the 2008 financial crisis had any shared institutional memory or working knowledge of the preceding major financial debacle, the 1998 collapse of Long-Term Capital Management hedge fund. We also know that the turnover in political and business experience has been shortening over the last decades, e.g., due to term limits, political burnout and constant economic churn. The only redemptive feature in any of this is a messy, this-world realism, according to Oliver:

If we eventually escape from our present perplexities, it will not be because theorists have discovered some fine new principle of salvation; or because newspapers have scolded and pointed angry fingers at this one or that; or because we, their readers, have become excited and have demanded that ‘something must be done.’ It will be because [politicians]. . .have ‘jumbled something’ out of their contentions that will be of advantage to their country.

Here too no guarantees! More important anyway for Oliver is this: It isn’t that experience in the craft of politics enables the practitioner to better see the future. Rather, experience enables the demanding present to be seen more for what it is, namely, complex now:

Prophetic statesmen are a fairly common variety of the species, but those who not only foresee things but foresee them truly are among the rarest of human products. [The chief minister] made no pretensions to the gift of prophecy. Man of genius though he was, he owed little to his imagination. He excelled his colleagues, and opponents, and indeed every statesman in Europe, not in penetration of the hidden future, but in the clearness with which he saw things present, and in the accuracy with which he could judge by the lights or darkness of the horizon what weather might be looked for on the morrow. And he excelled them most of all in the rapidity with which his mind arranged in their true proportions the most diverse and unexpected events.

Whether this description of the chief minister in question has stood the test of time, I can’t say. But Oliver’s words describe what Part I has termed coping ahead better when one can’t manage longer term—that is, not just reacting but working out the next steps “for on the morrow.” That too is the Anthropocene: complex, now.


There is in other words a track record to be looked for in coping ahead while confronting what you and your colleagues have (yet) to experience. It is one thing to think you are managing risk and uncertainty, when you aren’t. It is quite another thing—and a good mess to be in with the Anthropocene—that you and your colleagues are better adept at coping ahead.

A practitioner’s track record of different setbacks looks a good deal more useful when compared to, say, the irreproducibility of research findings in relevant peer-reviewed publications. Note the good-mess corollary: Inexperience starts in the individual, but experience may just as well end up across practitioners, untraceably distributed and connected.

Key Concepts: Take-aways for Anthropocene analysis and management

If ever a key concept were in need of greater differentiation and granularity, it is “interconnected” and its cognates. This guide seeks to demonstrate the reverse take-away as well: “Interconnectivity” itself becomes a major optic for differentiating cases and their granularity more tractably.  

It was in undertaking research with Paul R. Schulman on the San Francisco Vessel Traffic Service (VTS) of the US Coast Guard that I had my introduction into just how important it was to differentiate types of interconnectivity. After a year or so of research did it become clearer there were at least five major kinds of “interconnected” at work, with sharp differences in the VTS’s real-time operations:

  • Interoperability: Like the textbook interoperable energy utility (where electricity is crucial for the natural gas infrastructure and vice versa), the VTS manages both vessel traffic and the regulated waterways that the vessels use (where managing the waterways affects management of the vessels and vice versa);
  • Shared control variables: Water flows are a major control variable not just for VTS navigation purposes, but also for other infrastructures (most notably large water supplies and hydropower systems). This means that unexpected changes in how one infrastructure manages water flows can affect the management of the water flows by the other infrastructures (indeed, inter-infrastructural coordination around shared control variables turns out to be crucial);
  • Whole cycle of infrastructure operations: The USCG has a range of missions and operations, two of which are the VTS and the SAR (Search and Rescue) units. VTS combines with SAR to cover the stages of this infrastructure’s operational cycle—normal operations and disrupted operations (VTS) along with search and recovery (SAR);
  • Variety of real-time configurations of interconnectivity: The VTS manages by virtue of utilizing a variety of interconnectivity configurations. For example, when VTS management of a common pool resource (the waterways) on behalf of vessels is disrupted or fails (e.g., because of disruption in VTS communications), the interconnection configuration defaults over to the reciprocal one of vessel-to-vessel communication; and
  • Inter-organizational linkages: USCG operations, including a VTS, are not only linked with other infrastructures through reliance on the Global Positioning System (GPS), but the Coast Guard’s position within the US Department of Homeland Security makes it strategically placed for focusing on GPS vulnerabilities and strengths when it comes to the US government’s cyber-infrastructure.

Once interconnectivities were taken seriously enough to differentiate, we better understood how conventional approaches to risk management could be mis-specified and misleading, as described elsewhere in Part II. Suffice it to say, “interconnectivity,” as a key optic for the Anthropocene, becomes a major means for learning about specifics that matter when it comes to “with respect to what.” The last thing we should be doing in the Anthropocene is abstracting interconnectivities before recasting their granularities.


Section II.19    Policy palimpsest: concept, examples, and the violence

Section II.20    Heuristics as clues

Section II.21    The genre of wicked policy problems

Section II.22   Etcetera-isms as crisis kitsch

Section II.23  The analogy, “we are at sea,” remade for the Anthropocene

Section II.24   Thinking infrastructurally about 11 major policy and management issues

                        Take-aways for Anthropocene policy and management

Section II.19   Policy palimpsest: concept, examples, and the violence

Background, definition and initial implications.

The notion of “policy palimpsest” arose early in contemporary policy studies, but never gained traction. Its upshot is that current statements about complex policy issues are the composites of arguments and narratives that have been overwritten across time. A composite argument rendered off a policy palimpsest reads legibly—nouns and verbs appear in order and sense-making is achieved—but none of the previous inscriptions are pane-clear and entire because of the intervening the layers, effacements, and erasures. Arguments have been blurred, intertwined and re-assembled for present, at times controverted, purposes.

So, what’s new? We want policy to come to us as instantly recognizable, just as legible as the writing on the page or screen. That instantaneity is the aim of any composite argument.

Recourse to the analogy of the policy palimpsest is to frustrate that taken-for-granted legibility. The concept of palimpsest insists that policy always comes with fractured backstories and that the backstories provide clues—like pentimenti in a painting that become visible over time and reveal working methods—for what could have been or now can be instead. I use “policy palimpsest” instead of its rough synonyms–“language games,” “archives,” or “discourse systems,” for example—because it is always with respect to a specific policy, management issue, or complex of issues (e.g., failed states) and at a level of granularity that matters for recasting the issue(s) now, not just later.

This means that any policy arguments that are urged on us because of their elegance, simplicity, logical structure or win-win import are perilous. They only wink at the complexity in their policy palimpsests. The analytic challenge becomes one of reading  any current composite argument with the blurred-away now made visible in order to acknowledge and probe what has been rendered missing in the composite reading. Once you identify what is missing in the composite but was in the palimpsest being read off—no guarantees here!—you identify potential means to recast the complex issue in new ways.

Short example.

Turn to the journal, Foreign Affairs, and a much-cited 2014 critique of the failed-states rationale put forth in the Bush Administration’s 2002 National Security Strategy (Mazarr 2014). The Bush Doctrine argued that failed states were an important cause of international terrorism. The Mazarr critique, including a review of the literature at the time of the doctrine’s formulation and later on, underscored multiple problems with its assumptions.

Yet even where the Mazarr critique and others like it are true, analysis of the failed-states argument needs to go further, not just to identify what was effaced in the policy palimpsest for terrorism at that time, but also what was effaced in these failed-states critiques which have become part of the very same palimpsest since then. [1]

The most (in)famous example of what has been erased, at least in academic journals, is the polemical avowal that America as a nation deserved 9/11 and now that it had happened, here was the opportunity for that nation to take the lead in a new rapprochement with the Islamic world. This argument was expunged from subsequent discussion, where “straight-forward” policy arguments since 9/11 should be seen in some ways as bowdlerizing its policy palimpsest.

The least recognized erasure, however, but the one that would have been most visible had such an attempt at rapprochement taken place, was the centrality of the following question for international policy jettisoned from the policy horizon with its collapsing twin towers: Where are this century’s new democracies to come from, if not from failed states, including—dare we say—parts of the US?

Longer example.


Each sentence in this guide could be said to be a composite made off of all manner of policy and management palimpsests of concern to the Anthropocene. What then am I missing in my own arguments? A great deal—though I believe this can enrich rather than paralyze analysis. Let me give a more extended example from my own practice.

Several years ago I wrote a potted history of the travails in EU’s CO2 cap-and-trade system, the Emissions Trading System (ETS):

Upon its inception in 2005 when CO2 emission credits were issued under the ETS, credit prices initially did rise, but it was realized too many credits had been issued when prices declined. (Always bear in mind the theory upon which the ETS was based is that the higher the price of carbon, the fewer the emissions, all else considered.) By 2007 it was conceded that not only had too many credits been issued, but that coal imports into the EU had been rising at the same time. Credits continued to be issued, and by the end of 2009 prices were said to be too low to encourage investment in lowering emissions. Around 2010, computer hacking, cyber-theft and permit fraud occurred coupled with the obvious fact that the low carbon prices were in part due to declining carbon emissions because of increasing use of renewable energy (in other words, success by other means). The recession following the 2008 financial crisis had a depressive effect on credit prices as well. By the end of 2013, the European Parliament had approved a rescue plan for the ETS, including a provision to delay allocation of a third of the credits—even though the market would still likely be oversupplied by 2020, at which point it was thought that the ETS should promote green technological innovation, not just carbon reduction.

When I first presented this, one workshop participant remonstrated, “Well, we had to do something like the ETS!” One option was to answer her then. Another is to update my history with more fine-grained information on ETS implementation for the period 2005 – 2018. A different option would be to bring the history up-to-date since 2018 when I wrote most of the preceding paragraph. [2]                

It seems to me now that the indented paragraph can be substantially recast via the ETS’s policy palimpsest, irrespective of these options. In this case, the palimpsest is the massed narratives and controversies, past and present, over just what is better for Europe’s environment: a carbon tax, cap-and-trade systems, renewable energy technologies, “net-zero emission” schemes, a mix of these, some other hybrid, or something altogether different? What was actually implemented since 2005 is intermixed with proposals that weren’t. The challenge is to reread my earlier description with the elements I effaced now visible, and not just with respect to ETS implementation. To repeat, resurfacing earlier points that I missed is my start in thinking along different lines. (In truth, policy palimpsests invite such foraging.)


To recap: As my earlier composite argument can be viewed as a larger fragment assembled from smaller ones, my ETS history is punctuated with interruptions blurred out in the name of readability.

By extension, one missing element in my earlier ETS history is just what kind of (larger) fragment the ETS is. Is the ETS primarily an institutional work in progress under intermittent construction? Is it partly the ruins left behind by techno-managerial elite and New Class of bureaucrats operating beyond their capacities and in the face of resource limits? Or is the ETS partly a hollow cypher—formally, an empty signifier—for all manner of environmental hopes that are no longer there, e.g., overtaken by the Anthropocene? All of these, or more? Maybe none?

To cut to the upshot: The ETS palimpsest is written over constantly (consider the recent EU proposal for carbon border taxes based on average prices in the ETS). This means more than there is no last word for the ETS. It means being better prepared for the new interruptions and having to excavate potentially useful leads more deeply submerged in the past.

Palimpsest violence

Now return to that key point: Use of the policy palimpsest concept is to remind oneself how complex policy statements that read coherently are assembled out of fragments interrupted by missing parts, all of which are smoothed over for legibility and readability purposes.

For this guide, the policy palimpsest optic serves as a potent reminder of what goes into making a policy palimpsest and composite arguments read off of it: the violence in doing so. For “effacements and erasures” include “lacerations,” all too often deliberate or willfully ignored rather than unintended.

To take an earlier example: obsolescence of AI software. This isn’t just a track record of software innovation after innovation. It’s part of a policy palimpsest about how obsolescence has been (re)constructed over time when it comes to thinking about policy and management. People are hurt along the way. What’s missing has been made missing by suturing the fragments about obsolescence. The violence is why our resurfacing what’s been made missing is, in effect, more than a matter of reflexivity: It is a duty of care.

[1] More formally, a composite argument is blurred not only by the way it conveys an argument (as if straightforward when actually a concatenation of interrupted fragments), but also by what it doesn’t convey—those elements that are now illegible or appear now interstitially as lacunae, non-sequiturs, slippages, caesurae, and aporias. As such, no policy palimpsest is inscribed with the last word; no composite argument from it is indisputable or the authoritative one; each composite argument carries the entire palimpsest with it. Indeed, the palimpsest serves as a brake on isolating any single argument. The touchstone in Anthropocene policy and management is not the benchmark ideal; it is the palimpsest(s) up to that point.

Time also changes in assembling fragments from different parts of a palimpsest. The composite may be sequenced in the form of “first-this followed by that-then,” when instead separate fragments are juxtaposed from different times and contexts. A familiar example is tagging onto today’s major policy composites variants of that phrase, “…in a world threatened by catastrophic climate change.” Any such textual adjacency rejiggers time and context around the juxtaposed fragments as well. (I’m thinking here of the Japanese practice of furigana, where a gloss appears above or to the side of the characters being annotated.)

[2] A more recent history is found in the 2021 Energy Transition or Energy Expansion? published by the Transnational Institute and Trade Unions for Energy Democracy:

The flagship example of carbon pricing has been the EU’s “Emissions Trading System” (ETS). Launched in 2005, the ETS has been plagued from its inception by serious problems. In its early days, far too many permits were issued, which kept prices low and left companies with no real incentive to curb emissions. Permits were also allocated according to performance “benchmarks”, designed by the very companies that were supposed to be regulated and thus very weak. Power companies and energy intensive industries gained billions in windfall profits during the early years of the scheme — profits that mostly turned into shareholder dividends, with little invested in new clean energy infrastructure. . . .After years of tinkering, the past two years have finally seen the price of carbon on the EU ETS starting to rise. . .But the EU accounts for roughly 10% of the world GHGs and the EU ETS covers roughly 40% of the EU’s economy, or roughly 4% of the world’s GHGs.

Section II.20   Heuristics as clues


Long-held heuristics–more familiarly, organizational routines and standard operating procedures–are shorthand ways of doing things without all the uncertainty of reinventing the wheel. Newer heuristics include big data algorithms we don’t understand and policy narratives we think we do. Both enable making decisions in the face of uncertainty. Both shorthands are treated pragmatically as good-enough, like a new atlas of maps.

Older heuristics were relied upon because they were said to reduce uncertainty; more recent ones are used to better manage or cope ahead with uncertainty that hasn’t been/cannot be reduced, at least for the moment that matters in decisionmaking. A commonality between the old and new heuristics deserves highlighting: Both are less a shorthand than clues for what to do ahead.

By way of example.

Handbooks detailing how to respond to unpredictable floods and famines were written by and for administrators in Imperial China. Over the course of some thousand years, handbooks started to group together what had been learned into tables of maxims (sometime cast in rhyme) for ease of reference by later users.

Handbooks “are quick to insist, however, that using the tables is not sufficient in the long run: for the professional administrator they are rather a ‘clue’. . .that indicates where to go in the more complete texts,” writes Pierre-Étienne Will, the most recent and wide-ranging bibliographer of these handbooks (2020, XLIV). This status of heuristic-as-clue is to alert us to important omissions that require reference beyond any shorthand exposition (Ibid, 568). Occasions when a map proves imperfect and misleading are all too familiar.

Professor Will elaborates in an email: “’clue’ (yinxian 引線. . .) literally means ‘a thread that leads to…’, ‘that can be pulled to get…, or something of the sort. The same character yin is part of the words suoyin and yinde, meaning ‘index’, in modern Chinese. The tables or rhymes are like indexes to the complete texts.”


I want to apply this notion of heuristic-as-clue more speculatively to the newer algorithms derived from large datasets. We’re told that, even though the algorithms are not based on models of known cause-and-effect, they identify complex, more or less opaque, correlations said to be worth relying upon. But that stops short of the needful.

The status of a heuristic as clue underscores that, just as with causal models, there’s also a great deal yet to puzzle out with correlations before going forward. Correlations are not just the start of an analysis. They also are in context and those contexts start the analysis as well. In particular, the status of the algorithm-as-heuristic clues you into the underlying assumptions for using big dataset algorithms. Some say, e.g.:

  • algorithms deliver the best result among the other methods and heuristics available;
  • while not free of bias, they do a better job than others by virtue of the huge run of cases and calculations;
  • some kind of result at the scale of big data is better than no result, plus the algorithmic result is often produced more timely; and
  • anyway, there’s always a danger that the critics of big-data algorithms take them more seriously than the users, like consumers who comparison-shop and then make their own decisions.

The wider point is that, while the duty of care in using heuristics means treating them as indexes of that which cannot be omitted, the omission may already have occurred via the bulleted assumptions or like. Further, omission is especially worrisome from a duty of care perspective when the usefulness of complexity is being undermined in the process.

Section II.21 The genre of wicked policy problems

The equivalent of cease-and-desist orders should have been issued long ago against the haute vulgarization of “wicked problems.” Academics have argued for just as long that far more nuanced sets of terms are required than the earlier “wicked” and “tame” dichotomy.

Fair enough, but that too doesn’t take us far enough for the Anthropocene. More terminological differentiation may actually reinforce a “there” that isn’t there.


To see how, recast wicked problems as part of a longstanding genre in literature that enables very different statements and competing positions to be held without them being inconsistent at the same time. Literary and cultural critic, Michael McKeon (1987/2002), helps us here:

Genre provides a conceptual framework for the mediation (if not the “solution”) of intractable problems, a method for rendering such problems intelligible. The ideological status of genre, like that of all conceptual categories, lies in its explanatory and problem-“solving” capacities.

In McKeon’s formal terms, “the genre of the novel is a technique to engage epistemological and socio-ethical problems simultaneously, but with no particular commitment than that.” In this way, intractability appears not only as the novel’s subject matter but also by virtue of the conventions for how these matters to be raised.

This guide proposes you think of the literature on wicked problems as part and parcel of this enduring genre. The content is not only about the intractable in complex policy and management, but also their governing context is as historically tangled and conventionalized as that of the English novel. Masses of differentiated complexities take center place in wicked problems both by virtue of content and context.

To be clear.

I am not saying wicked problems are fictitious (even so, there are the truths of fiction). Rather, I am arguing that pinning wicked problems exclusively to their content (e.g., wicked problems are defined by the lack of agreed-upon rules to solve them) misses the fact that the analytic category of wicked problems as such is highly rule-bound (i.e., by the historical conventions to articulate and discuss such matters).

First, consider that over-focus on content. The scholarly attempt to differentiate “wicked” and “tame” problems into more nuanced categories is akin to disaggregating the English novel into romance, historical, gothic and other types. But such a differentiation need not problematize the genre’s conventions. In fact, the governing conventions may become more complex for distinguishing the more complex content, thus reinforcing the genre as a bottled-up intractability.

For example, the science fiction novel has emerged as another way to tackle what has been thought intractable all along and how to talk about it. Just as the novel has been a formal response to the complexity of the lived world, so wicked problems look very much part of that response and to the same world.

Now turn to the conventions specifically. To ask, “Just what are these conventions that govern the genre, wicked problems?,” turns out to be highly revealing by way of answers. The obvious convention (and one that is most explicit) is that you mustn’t try to over-simplify wicked problems. But you would have to search long and far to find any intimation of its semiotic opposite, “Don’t over-complexify wicked problems.” There’s little understanding, it seems to me, that labeling a policy issue wicked can over-complexify a problem that would otherwise be open or even hospitable to recasting into more tractable forms without loss of its already persuasive complexity.

So what?

If wicked problems are to be better addressed, altogether different conventions and rules—what Wittgenstein called “language games”—will have to be found under which to recast these. . . . well, whatever they are to be called they wouldn’t be termed “intractable,” would they?

Wicked policy problems are complex problems that have yet to be recast through their complexity. That is not optimism; it’s realism. As with much in contemporary policy and management, wicked problems have ended up as exaggerations: Even where descriptions of wicked problems may be true as far as they go, the truth of the matter needs to be pushed further. Those who are quick to label complex problems wicked are like the visitors to modern art galleries who see an anything-goes/free-for-all without noticing the deeply conventional and conventionalizing rectangles, walls and rooms in which all this is cabined.

Declaring something a wicked problem creates, in other words, The Ultimate One-Sided Problem—it’s, well, intractable—for humans who are everything but one-sided. In so doing, these one-siders of intractability in the Anthropocene, have taken the generous notion of intractably human and scalped it.

Section II.22   Etcetera-isms as crisis kitsch

Some readers might think that an idea—like “catastrophe”—isn’t responsible for those who believe in it, but that misses the point in professing ideas—as when “catastrophizing”—embody intentions and intentionality is part of action.

Let’s then say one piece of good news is when catastrophizing trips over into kitsch, i.e., presenting itself as so-awful you can’t keep your eyes off it. There are religious ceremonies and then there is the Nazi kitsch of the Nuremberg rallies. There are parades and then there is the communist kitsch of May Day. There is Greek tragedy, and then there is French farce. There’s Venus de Milo and then there are Venus de Milo salt and pepper shakers.

So too there is crisis kitsch in policy and management.

As in: “Policymakers need to worry about those other factors—societal, political, economic, historical, cultural, geographical, governmental, psychological, technological, ethical, religious, etc etc—that are so undeniably central to our lives.”

Or as in: The very same people who question the use of GDP as a measure of human health and the environment end up being among the first to urge “Increase government budgets by x% of GDP for health and the environment and social protection and this and that, and more, etcetera”

That is say, things are critical enough to note by indirection but require no explicit mention because, well, all the other stuff should have seized our attention by this time. This is about as helpful as planting liberty trees was to spreading the French Revolution.

Furthermore. . .

Even here someone can say kitsch is its own kind of catastrophe. Or if you prefer, the only way crisis kitsch comes across as serious is when the grievances behind all those etcetera’s are kept under wraps. Grudges? Those contingencies, which equate to no specialisms, must end where we  catastrophists stand, or else. There is no alternative.

How better to insult our intelligence. There is not the slightest hint of possibility that the decades of environmental advances since the 1960s have been a noble experiment.

Instead, we’re told it’s easier to mismanage an ecosystem than it is to manage it. Ecosystem collapse is more certain than ecosystem sustainability; negative externalities are to be expected, positive ones not. Economic growth is never a sufficient condition for improving the environment, while economic growth’s irreversible impacts on the environment are always a sufficient condition for precaution—except that failure is not an option! “Therefore” everything is at risk and what happens next is surely worse.

What then is to be done?

Well, that can be quickly answered. Look for the affordances in all this! Let’s end this section with a few of them:

**Moral: First, differentiate this realism, existential panic, dog-whistle alarmism, or whatever term where you work and live. Not to put too fine a point on it, there are differences that matter, say, between Raymond Pettibon’s artwork, “Don’t fuck with the apocalypse,” and Ronald Reagan writing in his White House diary, “I swear I believe Armageddon is near.”

**In this spirit of differentiating from the get-go, it would be good to know if we are, as some say, nine missed meals away from civil unrest, or only four missed meals, as others say.

**How else but managing better in real time are we to respond, if indeed all the etcetera-isms hold? Otherwise, critiques of productivism, extractivism, capitalism, racism, colonialism, militarism, imperialism et al end up too elitist for their own good. As if vox populi deserves what it gets by not dealing with all this “holistically” (whatever that might mean, methodologically or counternarratively).

**And anyway, who wouldn’t resist burn-out, if told repeatedly they haven’t “taken control” of climate change, species extinction, biodiversity loss etc?

**And anyway, post-apocalypse? Tax havens in the Cayman Islands, Bermuda, Hong Kong and the Netherlands? Under water. Multinational corporations? They should be so lucky! Forgone tax revenues? After the apocalypse, what taxes? Unless, of course, we already know that getting rid of these tax sinkholes for the rich and already undeserving are among the few things truly urgent, like climate change.

As if, in other words, we’re being told it’s unethical not to experiment on a worldwide scale, when if anything calls for an explicit ethics it is to experiment only after (1) having globally canvassed and being alert to better practices (and their contingent closure rules!) emerging with respect to reversing specific cases of climate warming, species extinction and biodiversity loss and (2) having to address really-existing disasters we already know more about or consider also urgent.

Section II.23   The analogy, “we are at sea,” remade for the Anthropocene

Start with a sample of excerpts on what it means to find ourselves “being at sea.”

Apologies: The twelve quotes are a hefty read before I get to my own recasting. That said, it’s important you look for any connections that strike you along the way:

*Rene Descartes, philosopher: “The Meditation of yesterday filled my mind with so many doubts that it is no longer in my power to forget them. And yet I do not see in what manner I can resolve them; and, just as if I had all of a sudden fallen into very deep water, I am so disconcerted that I can neither make certain of setting my feet on the bottom, nor can I swim and so support myself on the surface. I shall nevertheless make an effort . . .until I have met with something which is certain, or at least, if I can do nothing else, until I have learned for certain that there is nothing in the world that is certain.”

*Charles Sanders Peirce, philosopher: “…the solid ground of fact fails…It still is not standing upon the bedrock of fact. It is walking upon a bog, and can only say, this ground seems to hold for the present.”

*Blaise Pascal, philosopher: “On a vast ocean we are drifting, ever uncertain and bobbing about, blown this way or that. Whenever we think we have some point to which we can cling in order to strengthen ourselves, it shakes free and leaves us behind…Nothing halts for us.”

*Immanuel Kant, philosopher: “This land [of true understanding], however, is an island, …surrounded by a broad and stormy ocean, the true seat of illusion, where many a fog bank and rapidly melting iceberg pretend to be new lands and, ceaselessly deceiving with empty hopes the voyager looking around for new discoveries, entwine him in adventures from which he can never escape and yet also never bring to an end.”

*Michael Oakeshott, political philosopher: “In political activity, then, men sail a boundless and bottomless sea; there is neither harbour for shelter nor floor for anchorage, neither starting-place nor appointed destination. The enterprise is to keep afloat on an even keel; the sea is both friend and enemy; and the seamanship consists in using the resources of a traditional manner of behaviour in order to make a friend of every hostile occasion.”

*Alexis de Tocqueville, historian and political scientist: “The legislator is like a navigator on the high seas. He can steer the vessel on which he sails, but he cannot alter its construction, raise the wind, or stop the ocean from swelling beneath his feet”.

*Leo Tolstoy, novelist: “While the sea of history remains calm the ruler-administrator in his frail bark, holding on with a boat hook to the ship of the people and himself moving, naturally imagines that his efforts move the ship he is holding on to. But as soon as a storm arises and the sea begins to heave and the ship to move, such a delusion is no longer possible.”

*Otto Neurath, philosopher of social science: “Imagine sailors who, far out at sea, transform the shape of their vessel…They make use of some drifting timber, besides the timber of the old structure, to modify the skeleton and the hull of their vessel. But they cannot put the ship in dock in order to start from scratch. During the work they stay on the old structure and deal with heavy gales and thundering waves. . . A new ship grows out of the old one, step by step—and while they are still building, the sailors may already be thinking of a new structure, and they will not always agree with one another. The whole business will go on in a way we cannot even anticipate today. . . .That is our fate.”

*Hans Magnus Enzensberger, author and critic: “The question whether it’s best to swim with the current or against it seems to me out of date…. The method of the yachtsman who tacks with the wind as well as against it seems more fruitful. Such a procedure applied to society demands stoic disbelief and the greatest attentiveness. Anyone who wants to reach even the nearest goal must expect, step by step, a thousand unpredictable variables and cannot put his trust in any of them.”

*Isaiah Berlin, historian of ideas: “. . .they pretend that all that need be known is known, that they are working with open eyes in a transparent medium, with facts and laws accurately laid out before them, instead of groping, as in fact they are doing, in a half-light where some may see a little further than others but where none sees beyond a certain point, and, like pilots in a mist, must rely upon a general sense of where they are and how to navigate in such weather and in such waters, with such help as they may derive from maps drawn at other dates by men employing different conventions, and by the aid of such instruments as give nothing but the most general information about their situation.”

*Joseph Conrad, novelist: “He would reason about people’s conduct as though a man were as simple a figure as, say, two sticks laid across each other; whereas a man is much more like the sea whose movements are too complicated to explain, and whose depths may bring up God only knows what at any moment.”

*G.L.S. Shackle, economist: “[We] are like a ship’s crew who have been wrecked in a swirling tide-race. Often a man will hear nothing but the roar of the waters in his ears, see nothing but the dim green light. But as he strikes out, his head will come sometimes well above the water, where for the moment he can see clear about him. At that moment he has the right to shout directions to his fellows, to point the way to safety, even though he may feel sure that next moment he will be again submerged and may then doubt whether after all he has his bearings.”

Let me stop, as any wider selection of excerpts would have been arbitrary as well. (For more, see the locus classicus on the topic: Hans Blumenberg (1997). Shipwreck with Spectator: Paradigm of a metaphor for existence. Translated by Steven Rendall. The MIT Press: Cambridge MA.)

Thought experiment and initial implications.

What follows is my line of thought in drawing out connections that I hadn’t thought about before assembling the quotes together. My aim is discovering what I’ve missed about “being at sea,” and how this might help recast what that means for policy and management in the Anthropocene.

In reading the quotes, a colleague of mine thought the most obvious connection was between an implied comprehensive rationality (where you already know enough) and the actual bounded rationality of really-existing decisionmaking. That level of generality was not the first thing that struck me: What sticks out instead is that Tocqueville says the navigator cannot alter the ship’s construction while at sea, while Neurath’s point is that the ship has to be rebuilt at sea.

Pause a moment and note what I have just done. By assembling the list of quotes I’ve created anomalies—more specifically, anomalous connections—where none were before without the comparison. This has been done through the arbitrary juxtaposition and sequencing of quotations, so as to extend my own thinking. And where does my juxtaposing the quotes of Tocqueville and Neurath lead me? Whither the navigator “cannot alter its construction, raise the wind, or stop the ocean from swelling beneath his feet” in contrast to “They make use of some drifting timber, besides the timber of the old structure, to modify the skeleton and the hull of their vessel. . .During the work they stay on the old structure and deal with heavy gales and thundering waves”?

To me, it’s the granularity of swelling ocean, heavy gales and thundering waves that the quotes share. Actual responses to these forces differ (other quotes also confirm), but they can’t be wished away (and literally so for the Anthropocene). Yet push further: The more we think about being at sea like this, the more we grasp how so much of policy and analysis has been just this kind of wishful thinking.

Indeed, this is my recasting: It’s magical thinking that also keeps us at sea in the Anthropocene.

–We’ll return in a moment to how this recasting helps. Suffice it for now, long-lived debates in the policy and management with which I am familiar have been fought at the extremes: Market and Hierarchy; Coordination and Regulation; Regulation and Innovation; Innovation and Politics; Politics and, well, Science and Technology, or other such abstractions. Worse yet: Holism versus Reductionism, Quantitative versus Qualitative, Positivist versus Post-positivist. Such has been the methodological injunction of First, simplify! and about as far away as you can get from today’s imperative, First, differentiate!

We are still told that, when it comes to high reliability of society’s critical infrastructures, macro-design trumps micro-behavior (i.e., operator error); alternatively, micro-behavior drives macro-design (i.e., self-organizing, complexly adaptive systems). If only we designed efficient energy markets, the grid would be able to take care of itself; if only we had real-time metering in every household and business, the grid would be able to take care of itself; if only we distributed multi-agent software to self-heal the grid, the grid would be able to take care of itself.

If only we had full cost pricing, or political will, or had publics that could handle Arrow’s voting paradox, then everything would be on track. If only we got rid of all that mess in between, we’d be better off. Then we’d get to the point. Which way Africa: Kenyatta or Nyerere? Brazil: Is it race or class? Whither the world: Globalization or [fill in the blank]? Xi or Modi? Engineering an economy’s soft landing, derisking private investments, ensuring large systems fail gracefully, and other ways to slice clouds in half. We might as well talk about who is more likely to be in a Christian heaven, Plato with his soul or Socrates for his self-sacrifice.

–Policy can sometimes look like the conjuror’s misdirection. A policy directs your attention to one area while the real action happens elsewhere. You focus on the policymaker when the other hands of middle-level managers and professionals ensure rabbits and hats go together.

As a newly-minted policy analyst (nor alone in this), I was told we had first to nail the politics. Without the right political arrangements, how can we have the right policies? I remember vividly times when I was assured that change political institutions and human behavior changes accordingly.

Further along we were told: Actually, it’s all about economics. “After all, you can’t repeal the business cycle,” we were told. And with the right macroeconomic and microeconomic arrangements in place, politics and political conduct have changed for the better, I was assured.

We were then told that, well, it’s really about getting the science and technology down. Dummy, it’s politics and economics that have gotten us into this mess and will keep us there, unless we start taking science seriously. We’re in a climate emergency, after all!

And yet. . .the very same misdirection continues. Farms still get their subsidies—be it because agriculture is politically important, food is economically important, carbon sequestration is environmentally important, and global science and technology are  reallyReally more important without which there will be no earth, no climate, no food, no agriculture, no subsidies, no nothing worth speaking of.

We could as well believe philosopher Kant’s early musings about how the collapse of the universe—yes, the entire universe—can be brought about by even the slightest derangement here. (Derangements of course cascade on Planet Earth, but that begs the more important question: Under what conditions and with respect to what specific failure scenarios?)


How many times have we heard or been magicked by something like, “If implemented as planned…,” “If done right…,” “Once the risks are under control. . .,” or “Given market-clearing prices…” Just like that older version: “Monarchy is the best form of government, provided the monarch possesses virtue and wisdom.”

‘‘If implemented as planned,’’ when we know that is the assumption we cannot make. ‘‘If done right,’’ when we know that “technically right” is unethical without specifying just what the ethics are, case by case. “Once the risks are under control,” when any notion of control is ludicrous in radical uncertainty. ‘‘Given market-clearing prices,’’ when we know not only that markets in the real world often do not clear (supply and demand do not equate at a single price)—and even when they do, their ‘‘efficiencies’’ can undermine the very markets that produce those prices.

Admit it: We could as well believe that the surest way to heat the house in winter is by striking a match under the porch thermometer. Would you believe that, “with the right structures in place,” installing the wheel closer to the engine gets you to your destination sooner?

No wonder we’re at sea, figuratively and literally.

Fair enough criticism, but criticism is not enough.

Where then does reframing of being at sea leave us? What does being at sea mean now and for the better in the Anthropocene? One answer returns us to that earlier: Be careful what you wish for!

Those who study wishes and wish-lists are likely to come across the fable of the mythical animal skin, which in the process of realizing each new wish, shrinks smaller and smaller—until nothing is left upon which to wish further. And why would you need to make more wishes? Because—so the moral of the story goes—of all the unintended aftermaths in need of correction that follow from even the most well-thought-out wish.

This analogy of the mythical animal skin recasts, considerably, the conversation stopper, “All that is missing is the political will to do what is needed…” Political will eats itself up and is manifestly a finite resource. Be careful what you wish for! is now everywhere in the Anthropocene. It isn’t a conservative caution in response to difficulty, inexperience and not-knowing ahead. Be careful what you wish for! is the way we admit these difficulties, inexperience and not-knowing publicly and still move on in our duty of care.

Section II.24   Thinking infrastructurally about 11 major policy and management issues

Critical infrastructures are usually defined as those large-scale systems and physical assets so vital to society that their failures drastically undermine society and economy, in whole or major part. I hope that the guide’s preceding sections have convinced the reader of their centrality and criticality, both positive and negative to the Anthropocene.

If I have learned one thing in over 25 years of large-systems research, it is that critical infrastructures are a very useful lens through which to rethink topics of major importance like risk/uncertainty, or infrastructure fragility and market failure, or healthcare and cyber-attacks, or equality versus efficiency, or the next global pandemic for that matter. It’s also a useful optic with which to think more about key concepts of importance to this guide, particularly social construction and sociotechnical imaginaries.

Below are eleven (11) reconsiderations of ongoing importance in the Anthropocene. The points are presented by and large independently of each other and are intended to be illustrative and wide-ranging. In other words, I apologize in advance for the length of this section, but in defense much more could and should be written on each the many topics.

1. Thinking infrastructurally about whole-cycle risk and uncertainty.

Describing the whole-cycle.

Think of an infrastructure as having an entire cycle of operations, ranging from normal, through disrupted and restored back, or if not, eventually tripping over into failed operations, followed by emergency response including efforts at initial service recovery, then into recovery of system assets and other services, and onto a new normal of service operation (if there is to be one). There are other ways to characterize the cycle or lifespan—for example, shouldn’t maintenance and repair be separated out of normal (routine) and disrupted (non-routine) operations?—but these demarcations from normal through to a new normal works for the guide’s purposes here.

Our research suggests that “risk and uncertainty” vary both in type and degree with respect to these different stages in infrastructure operations. In normal, disrupted and restoration-back-to-normal operations, we observed infrastructure control room operators worrying about management risks due to complacency, misjudgment, or exhausting options. But when infrastructures actually fail outright as systems, the management risks and uncertainties are very different.

The cause-and-effect relationships of normal, disrupted and restored operations are moot when “operating blind” in failure. What was more or less visible cause-and-effect is now replaced in failure by nonmeasurable uncertainties accompanied by contingency-filled aftermaths, neither of which are well understood. Further, when there is urgency and clarity in immediate emergency response, that in no way obviates the need for impromptu improvisations and unpredicted, let alone hitherto unimagined, shifts in human and technical interconnectivities as system failure unfolds.

As for system recovery (if they get to that stage), the control room operators we interviewed (during their normal operations) spoke of the probability of failure being even higher in recovery than during usual times. Had we interviewed them in an actual system failure, their having to energize or re-pressurize line by line may have been described in far more specially demanding terms of operating in the blind, working on the fly and riding uncertainty, full of improvisations and improvisational behavior.

First-order implications.

In short, risk and uncertainty are to be distinguished comparatively in terms of an infrastructure’s different stages of its lifespan operations. Once we recognize that the conventional notion of infrastructures having only two states (normal and failed) is grotesquely underspecified for empirical work, the whole-cycle comparisons of different understandings of infrastructure risk and uncertainty become far more rewarding.

For example, I believe that what separates the risks and uncertainties of longer-term recovery from risks and uncertainties found in a new-normal is whether or not the infrastructures have adopted new standards for their high reliability management. Endless recovery is trying to catch-up to some set of reliability and safety standards; new-normal is managing to standards and the risks that follow from managing to the standards.

This may or may not be in the form of earlier, old-normal standards seeking to prevent specific types of failures from ever happening. We now know that major distributed internet systems, increasingly viewed as critical infrastructures, are reliable because they expect components to fail and are better prepared for that eventuality, along with other contingencies. Each component should be able to fail in order for the system to be reliable, unlike systems where management is geared to ensure some components never fail.

So what?

The point not to lose sight of is that both nonmeasurability and high-contingency aftermaths still convey important information for their infrastructure operations during and after the disaster. This information, moreover, is especially significant when causal understanding is most obscure(d). When experienced emergency managers find themselves in the stages of systemwide infrastructure failure and immediate emergency response, nonmeasurability and high contingency tell them to prepare for and be ready to improvise, irrespective of what formal playbooks and plans have set out beforehand.

“Coping with risk” is thus a very misleading term when an important part of that “coping” is proactive improvisations and in response to infrastructure failures that unfold in ways well beyond predicting or imagining what are now conflated all-too-frequently as, “low probability, high consequence events.”

2. Thinking infrastructurally about the fragility of large sociotechnical systems.

Probably the last thing most people think is that infrastructures are fragile. If anything, they are massive structures, where “heavy” and “sturdy” come readily to mind. But the fact that they not only fail in systemwide disasters, but that they also require routine (and nonroutine) maintenance and repair as they depreciate over their lifespans, requires us to take the fragility features seriously.

Fortunately, there are those who write on infrastructure fragility from a broadly socio-cultural perspective rather than the sociotechnical one of this guide:

For all of their impressive heaviness, infrastructures are, at the end of the day, often remarkably light and fragile creatures—one or two missed inspections, suspect data points, or broken connectors from disaster. That spectacular failure is not continually engulfing the systems around us is a function of repair: the ongoing work by which “order and meaning in complex sociotechnical systems are maintained and transformed, human value is preserved and extended, and the complicated work of fitting to the varied circumstances of organizations, systems, and lives is accomplished” . . . .

It reminds us of the extent to which infrastructures are earned and re-earned on an ongoing, often daily, basis. It also reminds us (modernist obsessions notwithstanding) that staying power, and not just change, demands explanation. Even if we ignore this fact and the work that it indexes when we talk about infrastructure, the work nonetheless goes on. Where it does not, the ineluctable pull of decay and decline sets in and infrastructures enter the long or short spiral into entropy that—if untended—is their natural fate.                                              

S. Jackson (2015) Repair. Theorizing the contemporary: The infrastructure toolbox. Cultural
Anthropology website. Available at: https://culanth.org/fieldsights/repair

The nod to “sociotechnical systems” is welcome as is the recognition that these systems have to be managed—a key part of which is repair and maintenance—in order to operate. Added to routine and non-routine maintenance and repair are the just-in-time or just-for-now workarounds (software and hardware) that are necessitated by those inevitable technology, design and regulatory glitches—inevitable because comprehensiveness is impossible to achieve in complex large-scale systems.

Not only is this better-than-expected operation (beyond design and technology) because of repair and maintenance. It is also because real-time system operators have to actively manage in order to preclude must-never-happen events like loss of nuclear containment, cryptosporidium contamination of urban water supplies, or jumbo jets dropping like flies from the sky. That these events do from time-to-time happen only increases the widespread affective dread that they must not happen again.

So what?

What to my knowledge has not been pursued in the sociotechnical literature is that specific focus on repair:

Attending to repair can also change how we approach questions of value and valuation as it pertains to the infrastructures around us. Repair reminds us that the loop between infrastructure, value, and meaning is never fully closed at points of design, but represents an ongoing and sometimes fragile accomplishment. While artifacts surely have politics (or can), those politics are rarely frozen at the moment of design, instead unfolding across the lifespan of the infrastructure in question: completed, tweaked, and sometimes transformed through repair. Thus, if there are values in design there are also values in repair—and good ethical and political reasons to attend not only to the birth of infrastructures, but also to their care and feeding over time.


That the values expressed through repair (in sociotechnical terms, expressed as the practices of actual repair) need to be understood as thoroughly as the practices of actual design reflects, I believe, a major research gap in the sociotechnical literature with which I am familiar.

I cannot over-stress the importance of this notion of infrastructure fragility, contrary to any sturdy-monolith imaginary one might have about infrastructures. One can only hope, by way of example, that wind energy infrastructure being imposed by the Morocco-Siemens occupiers of Western Sahara is so fragile as to necessitate their endlessly massive and costly repairs and maintenance—but I confess that is my management take from the guide’s sociotechnical perspective.

3. Thinking infrastructurally about the market failure economists don’t talk about.

Economists tell us there are four principal types of market failure: public goods, externalities, asymmetric information, and market power. Rarely they talk about the fifth type, the one where efficient markets actually cause market failure by destroying the infrastructure underlying and stabilizing markets and their allocative activities.

Consider here the 2010 flash crash of the US stock market. Subsequent investigations found that market transactions happened so quickly and were so numerous under conditions of high-frequency trading and collocated servers that a point came when no liquidity was left to meet proffered transactions. Liquidity dried up and with it, price discovery. ‘‘Liquidity in a high-speed world is not a given: market design and market structure must ensure that liquidity provision arises continuously in a highly fragmented, highly interconnected trading environment,’’ as a report by the Commodity Futures Trading Commission (CFTC) put it for the crash. Here, efficiencies realized through high transaction speeds worked against a market infrastructure that would have operated reliably otherwise.

The economist will counter by insisting, ‘‘Obviously the market was not efficient because the full costs of reliability were not internalized.’’ But the point remains: Market failure under standard normal conditions of efficiency say nothing about anything so fundamental as infrastructure reliability as foundational to economic efficiency.

The policy and management challenge is to identify under what conditions does the fifth market failure arises empirically. Until that is done, the better part of wisdom—the better part of government regulation—would be to assume fully efficient markets are low-performance markets when the stabilizing market infrastructure underlying them is prone to this fifth type of market failure. What, then, is “prone”? Low-performing market infrastructure results from the vigorous pursuit of self-interest and efficiencies when hobbling real-time market infrastructure operators in choosing strategies for longer-term high reliability of the market infrastructure.

There is another way to put the point: High reliability management of critical infrastructures does not mean those infrastructures are to run at 100% full capacity. Quite the reverse. High reliability requires the respective infrastructures not work full throttle: Positive redundancy or fallback assets and options—what the economists’ mis-identify as “excess capacity”—are needed in case of sudden loss of running assets and facilities, the loss of which would threaten infrastructure-wide reliability and, with it, price discovery. To accept that “every system is stretched to operate at its capacity” may well be the worst threat to an infrastructure and its economic contributions.

In this view, critical infrastructures are economically most reliably productive when full capacity is not the long-term operating goal. Another way to put that is the long-run in question has not been differentiated enough for purposes of efficiency. Either way, efficiency does not serve as the benchmark for economic performance.

4. Thinking infrastructurally about healthcare.

The US Department of Homeland Security states healthcare is one of the nation’s critical infrastructures sectors, along with others like large-scale water and energy supplies.

Infrastructures, however, vary considerably in their mandates to provide vital services safely and continuously. The energy infrastructure differs depending on whether it is for electricity or natural gas, while the latter two differ from large-scale water supplies (I’ve studied all three). Yet the infrastructures for water and energy, with their central control rooms, are more similar when compared to, say, education or healthcare without such centralized operations center.

What would healthcare look like if it were managed more like other infrastructures that have centralized control rooms and systems, such as those for water and energy? Might the high reliability of infrastructural elements within the healthcare sector be a major way to better ensure patient safety? Four points are raised by way of answer:

(1) High reliability theory and practice suggest that the manufacture of vaccines and compounds can be made reliable and safe, at least up to the point of injection. Failure in those processes is exceptionally notable—as in the fungal meningitis contamination at the New England Compounding Center—because failure is preventable.

When the perspective is on medical error, the patient is at the center of the so-called sharp-end of the healthcare system. But healthcare reliability is a set of processes that includes the capacities and performance of upstream and wraparound organizations. When dominated by considerations of the sharp-end, policymakers and managers overlook—at our peril—the strong-end of healthcare with its backward linkages for producing medicines and treatments reliably and safely.

(2) If healthcare were an infrastructure more like those with centralized control centers, the criticality and centrality of societal dread in driving reliable service provision would be dramatically underscored.

Yet, aside from that special and important case of public health emergencies (think the COVID-19 pandemic), civic attitudes toward health and medical safety lack the public dread we find to be the key foundation of support for the level of reliability pursued in other infrastructures, such as nuclear power and commercial aviation.

Commission of medical errors hasn’t generated the level of public dread associated with nuclear meltdowns or jumbo-jetliners dropping from the air. Medical errors, along with fires in medical facilities, are often “should-never-happen events,” not “must-never-happen events.”

What would generate the widespread societal dread needed to produce “must-never-happen” behavior? Answer: Getting medical treatment kills or maims you unless managed reliably and safely.

(3) How a reliable and safe healthcare system encourages a more reliable healthcare consumer would be akin to asking how does a reliable grid or water supply encourage the electricity or water consumer to be energy or water conscious. Presumably, the movement to bring real-time monitoring healthcare technology into the patient’s habitation is increasingly part of that calculus.

(4) In all this focus on the patient, it mustn’t be forgotten that there are healthcare control rooms beyond those of manufacturers of medicines mentioned above: Think most immediately of the pharmacy systems inside and outside hospitals and their pharmacists/prescriptionists as reliability professionals.

One final point from an infrastructure perspective when it comes to healthcare risks and uncertainties. Can we find systematically interconnected healthcare providers so critical that they could bring your healthcare sector down (say, as was threatened for the US when the 12 systematically interconnected banking institutions were under threat during the 2008 financial crisis)? If so, we would have a healthcare sector in need of “stress tests” for systemic risks just as post-2008 financial services institutions had to undergo.

5. Thinking about infrastructurally about differences between large system risks versus large system safety.

There is the popular belief, not least among engineers, economists and system modelers, that reducing large system risks is a major way to improve its large system safety. This is not true for those critical infrastructures society’s survival depends upon. Or if you prefer, even where the belief could be true in theory, that truth needs to be pushed further when the large systems in question are really-existing critical infrastructures.

The reasons are many for not assuming that in large sociotechnical systems “reduce risks and increase safety” or, for that matter, “increase safety and you thereby reduce risks:”

However it is estimated, risk is generally about a specified harm and its likelihood of occurrence. But safety is increasingly recognized, as it was by an international group of aviation regulators, to be about “more than the absence of risk; it requires specific systemic enablers of safety to be maintained at all times to cope with the known risks, [and] to be well prepared to cope with those risks that are not yet known.”. . .In this sense, risk analysis and risk mitigation do not actually define safety, and even the best and most modern efforts at risk assessment and risk management cannot deliver safety on their own. Psychologically and politically, risk and safety are also different concepts, and this distinction is important to regulatory agencies and the publics they serve. . . .Risk is about loss while safety is about assurance. These are two different states of mind.                                                        

Danner and Schulman, 2018

Once again, the differences emerge because of the associated failure scenarios—risks with respect to these granularities as distinct from safety with respect to those.

If you doubt this, look at the actually-existing behavior of the reliability professionals inside and outside their large critical infrastructures. A good number of them continue to live and work in major earthquake zones, for example, even if they can move away.

This tells you something about their preferences for safety. But it is safety with respect to the known unknowns of where they live and work versus safety with respect to unknown-unknowns of “getting away.” Repeat: these are unknowns (more formally, unknown granularities), not risks.

So what? This highlights an obstinate truth: The costs to society of confronting limitless disaster scenarios is set by the dangers of ignoring the disasters easier to identify, assess and know (think again earthquakes and follow-on).

6. Thinking infrastructurally about cyber-attacks.

In no order of priority:

(1) It’s commonly assumed cybersecurity is a special concern for interconnected critical infrastructures: Failure of security in one (e.g., a ransomware attack) can well have knock-on effects for other infrastructures dependent on it. Examples are frequently cited.

Yet the empirical literature on real-time infrastructure operations indicates that disruptions in one infrastructure are often managed by real-time control operations so as not to disrupt the interconnected ones. Not always, not every infrastructure, but often enough not to be ignored. These saves need to be recorded and learned from as much as cybersecurity failures.

(2) Interconnectivity is configured in many ways between and among critical infrastructures. These configurations are not all tightly coupled and complexly interactive and do not cascade “on their own.” Consider all those graphics that show large sociotechnical systems to be densely and multi-linked with other systems. Not all of interconnections, however and importantly, are ones of tight coupling and complex interactivity primed to fail in no time flat when normal operations are breached.

More, some interinfrastructural cascades look considerably less instantaneous and unmanaged than presumed. One interviewee underscored how a ransomware attack on an important city infrastructure was contained so as not to affect other units and their real-time operations within that department. In fact and as noted above, other data also exist supporting the assumption that disruptions in some critical infrastructures are actually managed so as not to spread beyond.

No guarantees, of course. It has to be asked, nonetheless, to what extent is this real-time management response capacity to cyber-attacks undermined by security software promised (prematurely) as the digital equivalents to guns, guards and gates.

(3) Another assumption is that the cyber-attackers know what they are doing—as if they were as reliable as the infrastructures they attack. We hear and read far less about those cases where the hackers can’t control or otherwise manage their own attacks. They too must cope with unintended aftermaths:

A study of 192 cyberattacks by national governments found that Russia ‘fails much more often than it succeeds’ at hacking, and that even its victories have provoked self-defeating countermeasures. After enduring a denial-of-service attack from Russia in 2007, Estonia significantly boosted its defences, which now serve as the basis for NATO’s cybersecurity strategy.                                                             


(4) Significantly different professional orientations within an infrastructure exist with respect to cybersecurity. The “cultural divide” between control room operators, system engineers, and IT staff is well-known. Those who run operational systems have had quite different views about new software and patches introduced by the respective IT units.

(5) Cyber-attacks on critical infrastructures are said to be special not only because they portend catastrophic cascades but also because they undermine confidence and trust in the public and private sectors that these vital services can be reliably protected. Where so, societal dread of these attacks moves center-stage. Although it might reflect reduced confidence and trust, we would expect a societal dread of digital-wide collapse also to increase pressures on those public and private infrastructures to be more reliable.

How this would work out is an empirical question, e.g., dread of medical error hasn’t been sufficient to make hospitals high reliability organizations. Differentiated contexts clearly matter, however: “I’m more concerned about that [cybersecurity related to control facilities] right now than I am about a big earthquake,” a district infrastructure director in the Pacific Northwest told us. “It’s a daily threat,” said a state roads emergency manager of cybersecurity there.

So what?

Prevention of cyber-attacks is almost always seen as a technology and design challenge rather than very much the management challenge it also is.  At least one very important implication for policy and management follows: While rarely discussed as such, “thinking infrastructurally about cyber-attacks” means taking obsolescence—both in security equipment and management skills and not just with respect to cybersecurity software—much, much more seriously (for more on the importance of obsolescence in the Anthropocene, see Section II.6).

7. Thinking infrastructurally about cognitive reversals.

What else can we do, senior executives and company boards tell themselves, when business is entirely on the line? We must risk failure in order to succeed! But what if the business is one of the many critical infrastructures privately owned or managed, as in the case not only in the US?

Here, if upper management seeks to implement risk-taking changes, they rely on middle-level reliability professionals, who, when they take risks, do so in order to reduce the chances of systemwide failure. To reliability-seeking professionals, the risk-taking activities of their upper management look like a form of suicide for fear of death.

When reliability professionals are compelled to reverse practices they know and find to be reliable, the results have been deadly:

• Famously in the Challenger accident, engineers had been required up to the day of that flight to show why the shuttle could launch; on that day, the decision rule was reversed to one showing why launch couldn’t take place.

• Once it was good bank practice to hold capital as a cushion against unexpected losses; capital security arrangements later mandated they hold capital against losses expected from their high-risk lending. Mortgage brokers traditionally made money on the performance and quality of mortgages they made; in the run-up to the 2008 financial crisis, their compensation changed to one based on the volume of loans originated but passed on.

• Originally, the Deepwater Horizon rig had been drilling an exploration well; that status changed when on April 15 2010 BP applied to the US Minerals Management Service (MMS) to convert the site to a production well. The MMS approved by the change. The explosion occurred five days later.

To summarize, decision-rule reversals have led to system failures and more: NASA was never the same; we are still trying to get out of the 2008 financial mess and the Great Recession that followed; and the MMS disappeared from the face of the earth.

But, that’s a strawman, you counter. “Of course, we wouldn’t deliberately push reliability professionals into unstudied conditions, if we could avoid it.” Really?

The still recommended approach, Be-Prepared-for-All-Hazards, looks first like the counsel of wisdom. It is dangerous, however, if requiring emergency and related organizations to cooperate in ways they currently cannot, using information they will not have or cannot obtain, for all manner of interconnected scenarios, which if treated with equal seriousness, produce considerable modeling and analytic uncertainties, let alone on-the-ground flaws.

8. Thinking infrastructurally about the next global pandemic.

My introduction to the policy side of pandemics was in 2005, when I read two articles, “Preparing for the next pandemic” by Michael T. Osterholm and “The next pandemic?” by Laurie Garrett, both in Foreign Affairs (July/August 2005). I think any reader today would find these articles prescient indeed. While some numbers haven’t turned out as supposed, the articles are spot-on when it comes a COVID-19’s major first-order impacts on mortality rates, medical shortages, societal and personal security, food systems, finance, trade, and economics.

The problem is, to telegraph ahead, newer understandings of the COVID-19 pandemic may be obscuring the very idea and necessity of pandemic preparedness via infrastructures.

At the start of the last pandemic

Below are titles of a few among many reports to be found in the COVID-19 folder of the international aggregator, The-Syllabus.com, over six days between April 23 – 30, 2020:

  • Tech Giants Are Using This Crisis to Colonize the Welfare System
  • The COVID-19 Pandemic Crisis: The Loss and Trauma Event of Our Time
  • Migrant workers face further social isolation and mental health challenges during coronavirus pandemic
  • ‘Calamitous’: domestic violence set to soar by 20% during global lockdown
  • The Fog of COVID-19 War Propaganda
  • The Case for Drafting Doctors
  • Covid-19 Threatens to Starve Africa
  • Covid-19: the controversial role of big tech in digital surveillance
  • For a more equal world: Coronavirus pandemic shows why ensuring gender justice is an urgent task
  • COVID-19 in the Middle East: Is this pandemic a health crisis or a war?
  • Urban Warfare: Housing Justice Under a Global Pandemic
  • New Age of Destructive Austerity After the Coronavirus
  • The Coronavirus and the End of Economics
  • Covid-19 is ‘an affront to democracy’
  • Health vs. Privacy: How Other Countries Use Surveillance To Fight the Pandemic
  • World Bank warns of collapse in money sent home by migrant workers
  • Coronavirus: will call centre workers lose their ‘voice’ to AI?
  • How Can Low-Income Countries Cope With Coronavirus Debt?
  • Is Our War with the Environment Leading to Pandemics?
  • The World Order Is Broken. The Coronavirus Proves It.
  • The West has found a new enemy: China replaces Islam
  • Will COVID-19 Make Us Less Democratic and More like China?
  • Pandemic Science Out of Control
  • Tech giants are profiting — and getting more powerful — even as the global economy tanks
  • The Legal and Medical Necessity of Abortion Care Amid the COVID-19 Pandemic
  • Will a child-care shortage prevent America’s reopening?
  • Covid-19 or the pandemic of mistreated biodiversity
  • Coronavirus, war, and the new inequality
  • Firms in EU tax havens cannot be denied Covid bailouts
  • This Crisis Demands an End to Mass Incarceration

I suspect you’d have to search long and hard in pre-COVID warnings of the next pandemic for the above specificities–which by the way are but the tip of the iceberg of COVID reportage at the time of writing.

Of course, you’d be right to conclude that these titles reflect the widespread and deep impacts of the corona crisis for society, economy, culture and more across the world. You’d also be a fool not to see pre-existing policy agendas glomming onto the crisis as of way of furthering their own important priorities—be they inequality, climate change, labor, migrants, and the rest—that have risen to more attention and visibility since 2005.

So what?

We of course need a 2020s version of “the next pandemic,” not one from mid-2000s. True, but that point is pushed further by the obvious question when it comes to pandemic preparedness:

How could we be better prepared for the future if, now and far more so than in 2005, we insist pandemics are caused by unresolved, interrelated issues over, inter alios, climate change, the international order, neoliberal economics, poverty, inequality, national welfare systems, global and local injustice, privacy rights, gender and reproductive rights, biodiversity loss and species extinction, geopolitics, cross-border migration, along with other claimants listed above and more?

If formulated this way, then predicting the future is the mess we are in now. Bluntly, the next pandemic is the one currently underway.

What then are we to do?

I have one suggestion: here too, think infrastructurally.

It’s clear that the professionals who should have been informed about the dangers of the 2020 pandemic were not among the people addressed by most public health experts. The professionals not consulted were those who operate in real time critical infrastructures, like water, electricity, telecommunications and transportation. No one told those men and women in the control rooms and out in the field that COVID-19 would wreak such havoc as it did in systems mandated to be so reliable.

From our interviews in Oregon and Washington State, it’s obvious no one predicted the actual, mega-impacts and interruptions that COVID has had on the real-time operations of essential infrastructures. You may already know essential workers were sent home to work offsite. Less known perhaps is the fact that those on-site had to be vaccinated, and some very experienced personnel left as a result. Far less appreciated is the earlier mentioned finding: COVID put a brake on major infrastructure investment, improvement and management activities. Said one logistic manager of his state’s response, “All [COVID-19] planning happened on the fly, we were building the plane as it moved, we’d never seen anything like this.”


In effect, public health experts were talking to the wrong decisionmakers. The experts seemed to operate under two misleading beliefs: their public role is to convince key politicians and officials about what to do, even if privately they “know” the real problems are politicians and politics.

Both beliefs remain fall short in a pandemic world. In the US, as our example, we wouldn’t have a foundational economy, we wouldn’t have markets, if it weren’t for electricity, water, telecoms and transportation being reliable. Yet to my knowledge the professionals responsible for real-time operations in the infrastructures were never specifically warned, were never specifically talked to, and certainly never had a chance to listen to our pandemic experts and ask their questions. They were treated as uncoupled and unconnected to large sociotechnical systems whose interconnections depended fundamentally upon them.

Consulting these critical infrastructure people the next time around won’t answer the questions of inequality, poverty, war and pestilence but would go some way to increase pandemic preparedness and response.

9. Thinking infrastructurally about the link between efficiency and equality

A good deal has been written arguing that economic efficiency and equality in economic well-being can move in the same direction (e.g., healthier people are more economically productive).

But the dominant view remains the two are in The Big Tradeoff: more equality means less efficiency and vice-versa. A good number of economists seem to have shifted little from the postulate that efficiency assumes market-clearing prices based on whatever distribution of wealth and income is in place, where to privilege one distribution over another isn’t really what mainstream economics is all about.

All this is curious from the perspective of the other social sciences: Why would anyone take a movement in efficiency (or equality) to be caused by a movement in the other rather than caused by some intervening variable affecting both efficiency and equality independently?

More institutionally-informed economists say they do talk about such intervening variables as critical infrastructure reliability, at least in the form of secure property rights that underpin gains in economic efficiency. Those, nevertheless, are second-order considerations. For when economists talk about the necessity of “secure property rights,” they are not talking about the infrastructure conditions needed to be in place under which a hugely reliable contract law, insurance and title registration infrastructure are “always on.” That real-time high reliability of critical infrastructures, as we just saw with respect to market failures, is on another agenda altogether.

If reliability is the missing link between the economist’s equality and efficiency, then any number of related issues look very different. Could it be, for example, that consumption is frequently less unequal than income precisely because critical infrastructures have been more reliable and more efficient when it comes to the delivery and distribution of goods and services than they have been in the creation and generation of income opportunities for those doing the consuming?

10. Thinking infrastructurally about social constructions, particularly “scale.”

It’s no news that our categories for thinking are both strengths (e.g., your field of specialization) and weaknesses (its particular blind-spots). Nor is it news that both are social constructions morphing over time. What is news, I believe, is where that social construction takes place and why it matters.


In public policy and management, it’s assumed that major meaning- and sense-making take place at the micro, meso and macro levels—even as we admit that the scales are socially constructed (think: what we use to call international and then global and now planetary).

That micro/meso/macro are easily historicized doesn’t stop me (nor should it stop you, the reader) from thinking through linkages and connections between these individual, emerging and system levels. There are instances where this usage poses no real problem to recasting complex policy issues more tractably.

There is, however, at least one set of cases where it is problematic, and importantly so. It’s where dynamic interconnections determine the scale and shifts in scale thereafter.

A city water manager told us that recent improvements in the potable water system meant that, in case of emergencies, they could close down portions of physical system, segment by segment, interconnection by interconnection. This enabled them to isolate, in their words, “the scale of their problem”. At these times and for these purposes, scale follow from interconnectivity changes, regardless of the obvious that both interconnectivity and scale are social constructions.

So what?

If infrastructure operators, like those for the city water system, are unavailable after a disaster, then damage assessments for new funding default to the emergency management agencies. They are arguably more familiar with devastation (another social construction) than with the real-time interconnectivity of backbone infrastructures like water and electricity (backbone being a very different social construction). The latter, for example, can be much more adept in moving, say, mobile generators and cell towers nearby to affected infrastructures for their initial service restoration.

To reiterate: the “where” and the “when” of the social construction really matters.

11. Thinking infrastructurally about sociotechnical imaginaries.

Sociotechnical imaginaries are “collectively held, institutionally stabilized, and publicly performed visions of desirable futures, animated by shared understandings of forms of social life and social order attainable through, and supportive of, advances in science and technology”                                            

S. Jasanoff, 2015. Future imperfect: Science, technology, and the imaginations of modernity. In Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power, ed. S. Jasanoff and S.-H. Kim, pp. 1–33. Chicago: The University of Chicago Press.

But then: whose visions? Even within a large sociotechnical system like a critical infrastructure, whose imaginaries? Clearly just not those of the CEO and the rest of the C-suite. Nor investors and the regulators. Nor the policymakers and legislators.

For it is also the case that large sociotechnical systems have their equivalent street-level bureaucrats, front-line implementers, and middle level reliability professionals, who have their own templates and facts on the ground at variance with others in the same system.


Consider the commonplace that regulatory compliance is “the baseline for risk mitigation in infrastructures.” Even so, there is no reason to assume that compliance–a sociotechnical imaginary if there ever was one!–is the same baseline for, inter alios,

  • the infrastructure’s operators in the field, including the eyes-and-ears field staff;
  • the infrastructure’s headquarters’ staff responsible for monitoring industry practices for meeting government compliance mandates;
  • the chief officials in the infrastructure who see the need for far more than compliance by way of enterprise risk management;
  • those other specialist professionals in the same infrastructure responsible for thinking through a wide range of “what-if” scenarios that vary by all manner of contingencies; and, last but never least,
  • the infrastructure’s reliability professionals—its control room operators, should they exist, and immediate support staff—in surmounting any (residual) stickiness by way of official procedures and protocols—the “official” sociotechnical imaginary—undermining real-time system reliability.

So what?

These differences in orientation with respect to “baseline compliance” mean societal values of systemwide reliability (and for that matter, system safety) can be just as differentiated as these staff and their responsibilities are. Where highly reliable infrastructures matter to a society, it must also be expected that the social values reflected in these infrastructures not only differ across infrastructures but within them as well. Sociotechnical imaginaries, in other words, must be assumed from the get-go to be highly nuanced forms of life.

To repeat: First differentiate!

Analogies: Take-aways for Anthropocene analysis and management

Analogies, in the view of this guide, make visible just how much the exercise of recasting is not a one-way street but more an intersection up ahead. You drive to greater/different granularity. . .and yet, there are other analogies (and so too other methods and counternarratives) to push and pull in other directions. To shift the metaphor, any one configuration of the shards in the Anthropocene kaleidoscope is not sufficient indefinitely, no matter how useful sticking there for the moment is.

What does this mean practically? It’s highly predictable that there are already existing but underacknowledged analogies to redescribe complex policy and management issues. At the time of writing, the Green New Deal has most often been likened to Roosevelt’s New Deal. It’s also been likened to the Civil Rights Movement, 19th century abolitionism, and the war economy of the Bolshevik Revolution. There should be no doubt that the climate emergency has been or will be compared to many other events you and I won’t imagine until that comparison is made. The crux is which one sticks, and usefully so. As a surrealist once put it, reality is the metaphor that lasts.

Go back to the policy palimpsest. Each policy palimpsest is not only overwritten by really-existing past and current policies, laws, regulations and the like; they are not only overwritten by past and current proposals that never got implemented and which come to haunt the present. Policy palimpsests are also overwritten by all manner of analogies, methods, counternarratives and the guides key concepts that come into play for complex policy and management issues. Yes, you’re better off in the Anthropocene by knowing a lot about a lot. But this guide is clear: That “a lot” is also importantly with respect to the domains of analogies, methods, key concepts and counternarratives.

Conclusion. Human agency and power in the Anthropocene

The guide concludes by drawing on the key concepts and notions of counternarrative, methods and analogies so to better understand the roles and functions of human agency and power in the Anthropocene. Unsurprisingly by this point, some of what follows might well not be the way you think about these topics. All the better for those trying to take Anthropocene complexity seriously.

Human agency.

The assumption here is that human agency is constrained differently at different times in different places and by different factor. As such, it is not its own homogenous dominant policy or management narrative. It has a much more important function, that being a counternarrative. From the perspective of the guide, human agency is best seen as a key global counternarrative to hegemonic policy and management.

The differences in context and function are obvious the second anyone defines human agency. Here is mine (not an uncommon one): “an individual’s capacity to determine and make meaning from their environment through purposive consciousness and reflective and creative action”. This definition accents the reflexivity; yours in contrast might highlight self-determination, imposition of the one’s will on the environment, or something other. My gamble is that similar or parallel points to which we now turn would be observed in applications of your definitions.

In order that we are on the same page, here are two examples of human agency that illustrate my definition, one from a case study of migration and the other from case studies of child labor:

Specifically, the current mainstream narrative is one that looks at these people as passive components of large-scale flows, driven by conflicts, migration policies and human smuggling. Even when the personal dimension is brought to the fore, it tends to be in order to depict migrants as victims at the receiving end of external forces. Whilst there is no denying that most of those crossing the Mediterranean experience violence, exploitation and are often deprived of their freedom for considerable periods of time (Albahari, 2015; D’Angelo, 2018a), it is also important to recognize and analyse their agency as individuals, as well as the complex sets of local and transnational networks that they own, develop and use before, during and after travelling to Europe.                                                                                       

J. Schapendonk (2021). “Counter moves. Destabilizing the grand narrative of onward migration and secondary movements in Europe.” International Migration: 1 – 14  DOI:10.1111/imig.12923

First, as the data [from three countries] have demonstrated, labor, and the need for children to work, is the predominant lens through which young people and the adults that surround them conceptualize children’s engagement with gangs and organized crime. This was in contrast to the other standpoints that permeate discourse. Labeling the children as gang members is a poor reflection of their drivers of involvement in crime and is likely to stigmatize children engaged in a plight to ensure their own survival. Alternatively, the young people were not child soldiers nor were they victims or perpetrators of trafficking or slavery. A victim lens is also problematic in this context. The relationship between young people and organized crime is complex and multifaceted. Young people are victims of acute marginalization, poverty and violence but they do have some agency over their decision making. The data from all studies illustrated how gangs offer young people ways to earn an income but they also provide social mobility, ‘social protection’ (Atkinson- Sheppard, 2017) and ‘street capital.’ In some instances, criminal groups offer young people ways to earn ‘quick and easy money.’ Thus, the young people are not devoid of agency, but their decision making should be considered within the context of restricted and bounded lives.                                                                  

S. Atkinson-Sheppard (2022). “A ‘Lens of Labor’: Re‐Conceptualizing young people’s involvement in organized crime.” Critical Criminology https://doi.org/10.1007/s10612-022-09674-5

So what?

Human agency (as defined and just illustrated) looks very different from the positions of pattern recognition and localized contingency scenarios than it does from the much more familiar macro and micro positions in policy and management. Let’s cycle human agency through these differences.

There are those who think the realization and/or control of human agency are among core principles around which to design large-scale systems involving humans, individually or collectively. Over-arching notions of “the individual” and “the collective” are contested at the macro-design node. Others focus on the individual or micro-level, where the agent acts in real time, reactively, proactively or with other adverbial properties. Here too contestation abounds, if only because of vastly different optics on the “micro” from psychology, phenomenology, law, microeconomics, and more.

Then, there are two other levels and units of analysis, which are the ones this guide focuses on with its definition of human agency. First is human agency as empirically expressed and observed across a run of different cases of “individuals,” “capacities,” “task environments,” “purposes” and “reflexivities” for starters. (Think of the analogy of searching out family resemblances.) Are there patterns to be recognized over a run of diverse cases of human agency, and do these patterns constitute contingent generalizations, even as they fall short of anything like macro-design principles?

And speaking of macro-design principles, are there cases where one or more of the contested principles have been modified to reflect local conditions and circumstances? For example, is a country’s driving code enforced or implemented differently in its mountainous regions than on its open plains? More formally, have macro-design principles been customized to reflect local contingency scenarios?

Far less mentioned, in the view of this guide, are these really-existing better practices for realizing human agency that have evolved over widely different cases or for modifying principles over widely different contingency scenarios locally. More often than not, case studies and literature reviews assert “best practices” in the form of macro-principles (“this is what it means to act democratically”) or where “lessons learned” have been scaled up from one site or a handful of them. This is certainly true not just in the migration and child labor literatures with which I am familiar.

Again, so what?

One could, for instance, counter there are no “better practices” anyway in the absence of best-macro ideals involving democracy and justice. From the guide’s perspective, the invocation of universal macro-principles is premature and accounts for why many the really-existing better—please, not “best”—practices are too infrequently discussed. The notable exceptions—e.g., participatory research and action generalized from a wide variety of cases and modified in light of various equity principles—can be counted on two hands.

One thinks also of the rush to judgment in, say, macro-labeling election results and protests as “populist”. There are again exceptions.  But it is a rush to judgment when the criteria for any first cut differentiation between, say, alt-right populism, nationalist populism or such pre-exist the analysis offered, where the criteria in no way emerge contingently—as patterns or as contingency scenarios—from the complexities of elections, protests and movements dominating the cases at hand.

From this perspective, human agency is best understood as an insistent counternarrative for moving away from dominant and domineering micro and macro-level narratives of human action and behavior. I believe this to especially hold as we go forward into the Anthropocene (more below).

But first: What about power? What about power’s constraints on human agency?


Other than a few references to politics, dollars and jerks, the guide might be seen as noticeably silent on the nature and role of power—actually, different kinds of power—going forward in the Anthropocene. This would be a major gap for a text so focused as is this one on differentiation in public policy and management: Even a formal history of power as used in ordinary language would describe different attempt after different attempt to identify, compare and contrast types of power (direct, indirect, dispersed. . .).

But formal histories are not the issue. What isn’t sufficiently acknowledged is that—on this already highly differentiated planet of these more than 8 billion people—numerous informal counternarratives, analogies and methodological approaches for power exist and thrive.

I cannot speak for these other narratives nor would I try to generalize from my reading. What I want to do instead is illustrate how “material power” is a very old, very overwritten policy palimpsest. Those who write on material power, this guide submits, are grabbing specific fragments from the palimpsest so as to assemble specific composite arguments. I will be doing the same below for my own composite argument about material power.

What is different about mine is this. Methodologically, my composite is visibly stitched together—no attempt at seamlessness here—and deliberately stitched into an argument you have never read before as written. Yet the gamble here is that even this unusual composite will resonate with you. More, it will do so by highlighting the lacunae, erasures and effacements that have been necessary for you to produce your own account of “material power”.

To be clear from the outset, what follows is illustrative—it has its own lacunae—and in no way seeks to pre-empt the search for underacknowledged counternarratives already differentiating material power in useful ways.

One power counternarrative

It’s said Lord Acton despaired over the prospect of ever finding French, German and British historians who agreed on an account of the Battle of Waterloo. So too others. In The Charterhouse of Parma, Stendhal recounts the misadventures of Fabrizio, who makes his way to Waterloo on the eve of the battle. Everything turns chaotic, with confusion supreme. “A few minutes later Fabrizio saw, twenty paces ahead of him a ploughed field, the surface of which was moving in a singular fashion. . . .[O]ur hero realized it was shot from guns that was making the earth fly up all around him. . . . ‘But is this the real battle’,” he asks a sergeant”.

Friedrich Hayek, Nobel economist, picks up the story and asks, “Was the man plowing his field just beyond the extreme wing of Napoleon’s guards part of the Battle of Waterloo?. . .To follow up this kind of question will show at least one thing: that we cannot define a historical fact in terms of spatiotemporal coordinates”. Literary critic, Nicola Chiaromonte, revisits that narrative: “Certainly the Battle of Waterloo that Napoleon saw and directed (or thought he directed) is not the event Fabrizio wanders into. Nor is the explosion of incidents in which Fabrizio finds himself the same event as the mortal engagement of the soldiers who jeer at him. . .The Battle of Waterloo was all of these, separately and together, plus countless other happenings.” By no means last, a more recent Fabrizio, Tod Hackett, runs to watch the chaotic, confused and eventually disastrous filming of the Battle of Waterloo sketched out in Nathanael West’s Hollywood novel, The Day of the Locust

This kind of power in “the Battle of Waterloo” is very much the power that political scientist, James G. March, described long ago as “different parts of the system contribut[ing] to different decisions in different ways at different times”. Contingency is writ large in this power. It can of course be countered that war and capitalism are their own powerful engines of contingency, but so equally it must be said of, say, natural selection or human agency as just described.

The power of contingency

Contingency is the chief feature of battle and contingency, as we saw in Part I, is allied with surprise. Even when understanding that contingency takes place in context, this looks little like the direct power defined as the ability of A to get B to do something B would not have done. Again the contexts of interest here are complex. To appreciate how this matters for the guide, start with the power that contingency plays in A getting A to do what A would not have done otherwise. Here is poet and essayist, T.S. Eliot:

My writings, in prose and verse, may or may not have surprised other people; but I know that they always, on first sight, surprise myself. I have often found that my most interesting or original ideas, when put into words and marshalled in final order, were ideas which I had not been aware of holding. It is ordinarily supposed that a writer knows exactly what he wants to say, before he sits down at his desk; and that his subsequent labours are merely a matter of a better choice of words, a neater turn of phrase, and a more orderly arrangement. Yet I have always discovered that anything I have written—anything at least which pleased me—was a different thing from the composition which I had thought I was going to write.

Consider below the range of other evidence that those “most interesting or original ideas”—those most powerful ideas—are the ones you don’t know until you act by setting them down or seeing them before you. A host of very different practitioners put the point on behalf of their collectivities:

  • “A writer doesn’t know what his intentions are until he’s done writing,” says poet, Robert Penn Warren. Even when the writing is done, poets “are apt to discover that what they decide to express is not everything their poems say,” writes Anne Stevenson, herself a poet, adding: “Nothing in my experience is more important about the writing of poems than that they should surprise you; that while you are submitting to their rigorous demands of rhythms and sounds they find a way of saying things you never meant to say or never knew you knew.” “I never consider a poem done until a friend has seen it and put that extra glare of light on it,” said poet, C.K. Williams. “It’s a very strange thing—as soon as you give the poem to someone else, even before they read it, it shifts a little, it becomes slightly something else from what you had thought it was, and you begin to look at it in a slightly different way.”
  • “How can I know what I think till I see what I say?” asks a character of novelist, E.M. Forster. “Therefore, till my work is finished, I never know exactly what result I shall reach, or if I shall arrive at any,” wrote Alex de Tocqueville to John Stuart Mill. “I do not know what I think until I have tried to write it,” said political scientist Aaron Wildavsky.
  • “You never know what you’re filming until later,” remarks a narrator in Chris Marker’s 1977 film Le Fond de l’Air est Rouge. Ralph Rugoff, a well-known curator, admits, “I sometimes think that I have an idea of what an exhibition I am curating is about. But then, often when I sit down to write the catalogue text, I discover that it’s actually about something else.” “You start a painting and it becomes something altogether different. It’s strange how little the artist’s will matters,” adds Picasso (and any number of other artists). In like fashion, “one important reason for making drawings, I imagine, is not to draw a likeness of what one sees, but to find out what it is you see,” offers poet and art critic, James Schuyler.
  • Harrison Birtwistle describes his process of composing a piece of music: “I know what it is before I’ve even written it, but in other ways I don’t know at all. As I unravel it, it never turns out to be what you think it’s going to be”. J.M. Coetzee, Nobel novelist, manages to make all this sound commonplace: “Truth is something that comes in the process of writing, or comes from the process of writing”.


If your point of departure in thinking about power is that ability of A to influence B to behave otherwise, then the persons we are after having learned we know more or less than we initially thought has enormous power over who we were before being distracted and surprised by that discovery. How can changing your mind and acting differently not be material?

In short and to be blunt, it’s not good enough to say power is primarily about that A (now, individual or collectivity) making that B (individual or collectivity) do something instead. Nor is it good enough to say power is primarily about controlling the decision agenda or determining peoples’ interests without them even knowing it. Power that is concentrated, or roundabout or everywhere present in no way exhausts power’s sheer variety.

So what?

The power in this illustrative counternarrative lies in surprise and, since surprise is that chief feature of complexity, surprise and its power should be thought of as complex from the get-go. So too for the global counternarrative of human agency. As counternarratives, the great threat in addressing power and agency is to think there is an outside to contingency, let alone an outside to complexity. This means that the most powerful response to the Anthropocene headline, “Uncertainty is not our friend,” is surely: It’s more complicated than that.

“It’s more complicated than that” is not good enough in the Anthropocene if treated as a conversation stopper, rather than the start of analysis and management. It’s correct, but still doesn’t go far enough. “I have noticed that it is never enough to be right,” Joan Didion writes in A Book of  Common Prayer, “I have noticed that it is necessary to be better.” It’s useful then by way of concluding this guide, to summarize two take-aways about when good enough is better than “optima” from the perspective of this guide’s Part I key concepts, Part II case material, and counternarratives allied to the power-contingency just sketched.

The first: We’ve seen that more than enough occasions where attempts at full, direct control to achieve results produce effects well short of what would have been the case had one managed or coped better with respect to the inevitable contingencies in trying to get there. “Control” is far too simplified and narrow even to be good enough for the contributions of human agency in the Anthropocene.

Second, managing for good enough can produce results even better than the initial “best-case scenario.” These surprises are all over the place. Examples include Anwar Sadat, Mikhail Gorbachev, and Nelson Mandela. Each was a very imperfect person, comrade and leader, but each helped prevent some fresh hell on earth. They were good enough to take advantage of contingent time and place and in that way took us further than we could have expected, albeit we of course want to go further still.

The point underscored by this guide is that you work very hard to get to good enough since it can’t be assured. Good enough can never free itself (nor does it pretend to) from difficulty, inexperience and not-knowing associated with policy and management complexity. Good enough, under Anthropocene conditions, is what happens when you (plural) realize how much depends on advancing to the decision point of “yes but” and “yes and.” Why? Because at that juncture, you are pushing complexity’s advantage of further. Plainly put, stopping short at currently-understood progress or growth, be they in their bad-economic or good-sustainable versions, is just like stopping at the currently dominant power narratives of direct, indirect and dispersed: Both are premature.


My special thanks go to Paul Schulman, my colleague in the infrastructure research mentioned here. Thanks as well to Rob Hoppe and Stian Antonsen for their close reading and input on an earlier draft. Arjen Boin, Janne Hukkinen and Ian Scoones also have my gratitude for their comments. Remaining defects testify to my stubbornness.

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