Big Read: WHEN COMPLEX IS AS SIMPLE AS IT GETS– Draft Guide to New Policy Analysis and Management for the Anthropocene (July 2022)

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 every scale, What am I missing that’s 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. Everything is connected but 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     Recasting labor-substituting automation

Section II.3     Recasting long-terms, short-terms and short-termism

Section II.4     New environmental counternarratives

                        Take-aways for Anthropocene analysis and management


Section II.5     New benchmark and metric for risk, uncertainty and not-knowing

Section II.6     A typology for policy and management difficulties and implications for income inequality

Section II.7     Other typologies for the Anthropocene, Or making the best of linear thinking when it comes to “coordination”

Section II.8     Chop-logics about risks, tradeoffs, priorities, and existential threats are not appropriate for the Anthropocene

                        Take-aways for Anthropocene analysis and management

Key Concepts

Section II.9     “What’s missing?” in this catastrophic earthquake scenario

Section II.10   The problem with adaptive learning and management in the Anthropocene

Section II.11   What to do when criticisms are spot-on, but the recommendations aren’t

Section II.12   Begin, rather than end, with the radical agenda

Section II.13   “Managing” risk and uncertainty, or coping better ahead with inexperience?

                        Take-aways for Anthropocene analysis and management


Section II.14   Policy palimpsest: concept, examples, and the violence

Section II.15   Heuristics as clues

Section II.16   The genre of wicked policy problems

Section II.17  The analogy, “we are at sea,” remade for the Anthropocene

Section II.18 Thinking infrastructurally about 7 major policy and management issues

                        Take-aways for Anthropocene analysis and management

Conclusion  Power, good enough and betterment in the Anthropocene

Dedication. For Louise


This is a short work with many examples for reanalyzing and managing policy issues of high complexity, uncertainty, conflict and unfinished business in the Anthropocene. I have failed if the reader isn’t convinced that many hard issues can be recast anew and usefully so, 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 policy and management. I’ve been told that there is an underlying optimism in this guide’s argumentation. I would say it’s realism, not visionary, 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 management. No more chop-logic about starting with risks, see what the tradeoffs are, and then establish priorities. No more about too-little too-late, there is no alternative but [fill in the blank], and anyway next is worse. Even where that holds, it holds only so far, and these chop-logics certainly do not go far enough. The Anthropocene is too complex for that.

In fact, that complexity enables recasting intractable problems. To telegraph ahead, a complex policy or management issue labelled “intractable” is one that has yet to be recast more tractably without simplifying the complexity. Some policymakers, policy analysts and public managers already know this and are acting accordingly. Others will do so in the future, along with more social critics, policy and management academics, social scientists, and even some policy wonks and media specialists. This guide is for them.

I doubt anything like a formal manual would be possible, let alone useful. Instead, this work is a guide—part primer with a framework’s key constructs and part casebook with different examples illustrating their application. The framework has four pillars that differ from conventional analytical and management approaches:

  1. The guide is for major policy and management issues that are ineradicably complex. Equally important, that 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 the case examples exemplify. For this guide, the enemy of intractable policy and management is their complexity.
  3. This means policy analysts and managers can advise—more frequently than might be supposed—decisionmakers, “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 always encountered in recasting and pushing further. Fortunately, the more complex the issue, the greater chances in usefully distinguishing between managing, controlling and coping ahead with respect to its complexity. Setbacks are expected but are also more likely to be positive.

Together, the four pillars argue against thinking the Anthropocene can be universalized or reified or abstracted when in reality it is highly differentiated for the purposes of real-time policy and management. Here too many people know this. For them, it has always been a complex, uncertain, interrupted and conflicted Anthropocene.

Part I defines and connects the pillars’ key terms and concepts. I’ve kept the points brief, signposting along the way case examples sequenced together in Part II (the bulk of the guide). It concludes with a short chapter on notions of power, good enough, and betterment more suitable, I argue, for Anthropocene policy and management.

A last point. 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 for unpredictable conditions, not least of which are adaptive and participatory approaches.

By not reviewing this literature I risk being immodest in promoting my own framework while avoiding others. Had I the space I’d have had another section undertaking this literature review in terms of the framework developed in guide. In that case, you’d find much I agree with (at least from the Left; pace the radical agenda in Section II.12). Yet, most of the agreement would be of a qualified, “and yet. . .” The rationale for “yes, but” or “yes, and” is developed in Part I and Part II’s sections. That said, I do not want to be taken as dismissive of the critiques and alternatives already on record and the radical politics I’ve tried to express in the guide’s epigraph.

I have kept this work short because its intended readers already know we are in the Anthropocene or something very much like it. 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”).

But they also understand that all this is meaningful because the complications do matter for them. 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 this, but who also recognize any such admission does not go far enough in addressing the complexities. Politics, dollars and jerks have gotten us only so far and what an unholy trinity of seeming intractability they have been! In these times, even being good enough, however, requires going further–here as well as there–when it comes to “useful-for-whom-and-with-respect-to-what in the Anthropocene?”

Part I. Key concepts and terms


In ordinary language and even though different, policy and management are considered intractable when complex, uncertain, unfinished and conflicted. Climate change is one obvious example. 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 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,” 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 altogether another matter. These differences are important for better policy and management.

In the same way, “highly complex” and “intractable,” which are easily conflated in ordinary language, must be differentiated from the get-go. Complex, let alone complicated, does not mean intractable. In fact, the opposite holds when real people with real problems are operating in real time. Since readers might consider “complexity is the enemy of intractable” to be counter-intuitive, let’s be clearer about the formal 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 five features often left ambiguous in ordinary language about policy and management complexity. Discussion of the important fifth feature—the increased opportunities to recast a complex issue—is left to the section that follows.

The first feature that 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 (full stop),” such statements beg the question of more or less complex with respect to what. Just what is the baseline for establishing “complex”? To put the implication the other way around, the guide’s discussion of complexity has its ambiguities—just what is a “system” that it is more complex?—while still being less ambiguous than many ordinary language discussions. I illustrate this point with the “policy palimpsest” optic and specific applications in Part II.

Second, this definition of complexity illustrates how, say, the Earth can be the most complex ecosys­tem among ecosystems here (i.e., the Earth embraces all its ecosystems, all their differing ecosystem functions and services, and all their interconnections). The methodological point is not, however, that you “scale up to complexity,” but rather the system of interest becomes more (or less) complex by way of comparison.

Third, the definition illustrates how difficult it is to quantify complexity beyond numbers of compo­nents and functions attributed to each component. For there is no broadly accepted quantitative measure of interconnectivity (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 terms, such as “in­creasing resource scarcity,” can capture a sense of the interconnectivity at the global scale.

Fourth, 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 exactly what must not be assumed). Part II sections return again and again to the imperative for the guide’s Anthropocene audience: First, differentiate!

Recasting the intractable

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

For 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. To be clear from the outset, recast here does not mean simplify; the former’s synonyms are: reframe, redescribe, recalibrate, revise.

To initially see this kind of complexity and its import means you can start analysis 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 because of 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 become 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 also 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 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 are 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: There is no one way, let alone one single right way, to see and interpret conditions already complex. This too is not news. The world is not one way only because the world’s complexity—again, 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 complex seeing.

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, Part II cases in the guide 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 it.) Recasting methods in new 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 some cases, complex policy-relevant counternarratives are already available for recasting seemingly intractable features of issues like automation and global climate change. “Policy optics” is shorthand for these different ways to recast.

But, “useful for whom?” you ask. Answer: for those who already act in ways that demonstrate they take complexity seriously. (Yes, that’s not everybody.) I will also 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 a complex issue, illustrating the same shards can take on far more than one configuration, and that some of these configurations are potentially more appealing to decisionmakers. (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 can’t go further in thinking—until, that is, a new analogy or method or counternarrative shifts the complex focus elsewhere. This short guide does not pretend to cover the many other optics for treating complexity seriously (e.g. methodological triangulation and middle-range theories, which are better discussed 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.” This way we index the complexity out of which recastings are drawn. Here, the conjunction of “and yet. . .” has the performative function of confirming it’s complexity from which we draw the recasting(s).

“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 also matters. “Yes, your recommendation holds, but it’s usefully amended in this way. . . “ To be able to say that means one must be less vague by first asking of themselves: What am I missing that is right in front of me? How can I better recast the issue without losing complexity’s seriousness and timeliness? (Should it need repeating, there are policy analysts, managers and decisionmakers doing so already.)

Note the point of “yes, but” or “yes, and” is not to stymy or stalemate action but to turn complexity to its singular advantage. Yes, of course, 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 mess as Part II illustrates—is that the global climate crisis can’t be about the planet and science, all the way down. All the way down takes us quickly to all manner of “yes, but. . .” So too for other major policy and management issues: Differences matter, and matter in real time. For if we can’t manage better right now with all this complexity, why ever would we believe promises to manage the better later on in an ever more complex Anthropocene?

Here’s how taking complexity seriously matters so. 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 we can further understanding with “yes, but” or “yes, and”? In contrast to those glued 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.

The one “right” policy? And yet. . .

Of course, 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 to end in exaggeration. Acknowledgement of the historical, social, cultural, economic…roots of policy analysis and concepts for management has 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 for philosophy, Giambattista Vico for history, Roy Bhaskar for science…) Humans know mathematics in a way they cannot know the universe, because the former is a human creation about which more and more can be made to know. The latter’s uncertainties are socially constructed in a way that, for lack of a better word, “unknowledge” about the galaxy 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 ending 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 often 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. (Should it need saying, humans also can and do revert to the same-old stereotypes, analogies and worse.)

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

Control, Manage, or Cope Ahead

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

To start 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 stated 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, unrest, regulatory failures and other external impacts on the inputs to energy production (such as solar and wind). Such poses 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: namely, electricity at a 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 indeed is what makes earthquakes and fires catastrophic. The best to be done in these situations is to cope better, though attempts to command, control or manage will continue as well. But this isn’t to be just coping per se. 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. This coping is coping ahead in the face of real-time unknown-unknowns and involves planning above-and-beyond the reactive.

These distinctions are elaborated in the case material and are very important to keep in mind throughout this 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. While a common term, control room operators 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 “once and for all control” solutions 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 trying to control 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 me, difficulty, inexperience and not-knowing are the persistent goad to recast—reframe, revise, redescribe, recalibrate—the issue complexity of concern.

To anticipate, 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 is a complacency we can’t afford 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.

Why does this matter? 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 permanent letdown. Less discussed are setbacks that prove to be positive. Long known is when a complex organization transitions from one stage of its 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 setbacks 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 other 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 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 an absolutely central point of focus in the Anthropocene. Track records of development practitioners surmounting different setbacks, for instance, look a good deal more useful when compared to the irreproducibility of research findings in relevant peer-reviewed publications.  

One final point. Notably missing from the above discussion is the chief 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 larger, are not an option, as I hope to staple home in Part II sections. Basically, learning from the past is difficult for the same reasons predicting in the future is under Anthropocene conditions (both require stable objectives, institutional memory, positive redundancy and low environmental uncertainty, among others). Recasting becomes a very necessary focus in these circumstances.

The over-arching analogy I use for integrating these different key concepts is again that of a kaleidoscope: shake and then twist the head, even slightly, and the different shards—these terms and concepts along with issue specifics—reconfigure anew, twist by twist and issue by issue. If the decisionmakers aren’t doing the twisting, you the analyst or manager (or their wannabee) are next in line to do that. What do these 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 four principal means of 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 informality and formality in presentation. One consequence is that some sections are shorter and more accessible.) There may well be more useful ways of reframing the topics, given the variability in reader contexts. So consider my examples at best softening up the way for your own search and reframing. The overarching context for this exercise remains the unstable Anthropocene: now, later and indefinitely.

Part II begins with counternarratives, as it is crucial readers understand that complex but better alternatives already exist for recasting crises thought to be intractable. Alternative presents and futures needn’t be invented; they are there for those who comprehend that a planet of 7.5-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 critiques of the dominant storylines. Indeed: A major policy and management issue is clearcut only until the next major counternarrative. Counternarratives below devotes its four sections to recasting, respectively: global climate change, labor-saving automation, short terms versus long terms, and most important, environmental counternarratives for the Anthropocene.

Methods covers topics related primarily to risk, uncertainty and unknowns. These three terms have become so naturalized in ordinary language that they are a matter of taken-for-granted knowledge. The application of new methods to better 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 in a world 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 rethinks the chop-logic methodologies readers are familiar with, namely: priorities follow from risks and trade-offs.

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?” The first case asks what’s missing in the most important earthquake scenario for many in the United States. The second section underscores the special problem of why adaptive learning and management are not an alternative to recasting, this guide’s chief option. The third 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 in this third case is the growing problem of corporate greenwashing and what to do about it.

The fourth section illustrates how the key concepts enable radical agendas to kick-start analysis and action in contrast to many discussions that only end by calling for such an agenda. The fifth 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 around a set of four very different analogies for recasting hard problems more tractably: policy palimpsest, clues, genre, and “we are at sea” in the Anthropocene. The examples include failed states, carbon trading schemes, algorithmic decisionmaking, wicked policy problems 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 broad diversity of cases in Part II to nail home the point that recastings of difficult policy and management issues are not only possible, they’re likely. [Cases of recasting not discussed in the guide but elsewhere in this blog include: livestock pastoralism, COVID, poverty, government regulation, societal reset, sustainability, tax havens, and healthcare.] I’ve been told, however, that to read these 17 cases in sequence feels like being in a tumble-dryer. As a pause button, each of the four groupings ends with a short, different set of Take-aways for Anthropocene analysis and management. Each take-away applies to counternarratives, methods, key concepts and analogies together and highlight what I take to be Part I points in need of special reinforcement.


Section II.1     Recasting global climate change, locally

Section II.2     Recasting labor-substituting automation

Section II.3     Recasting long-terms, short-terms and short-termism

Section II.4     New environmental counternarratives

                        Take-aways for Anthropocene analysis and management

Section II.1     Recasting global climate change, locally

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 then turn to Supplementary Note 2, where the following passage is found. (As this passage is long, the temptation is to skim it. However, the following recasting depends on the reader giving 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 avail- ability 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 passages quoted uncovers a narrative discrepancy in the review. – and we know from policy analysis that such textual discrepancies can be the window through which we can re-see a problem differently (Roe 1994). 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)?

So put, 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 level at which the responses were observed.

I do not know if the latter is true and 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.

Note that the urgency and validity of the worst-case scenario remain, with local particularity persisting in new forms catalyzed by global climate change. 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. Recasting is possible because of, not in spite of, the complexity. 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).

Section II.2     Recasting labor-substituting automation

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

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

Here’s one 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 the document review].

Assume this storyline is correct as far as it goes.

The disconnect is that narrative discrepancy, “unprecedented,” in the preceding quote. This technological change is not unprecedented. The unprecedented is happening all the time when it comes to this narrative. 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 the referenced report of that National Commission on Technology, Automation, and Economic Progress, Technology and the American Economy, you’ll 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 today’s “fully automated luxury communism.”)

It’s not the report’s resonances, but specifics that are useful here. 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.

Section II.3     Recasting long-terms, short-terms and short-termism

Much of what we hear and read sounds like short-termism. Why aren’t more people taking the long-term seriously? What’s with all the short-terms in avoiding or 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.    

Equally important, the long-terms are almost all further differentiated. British historians are apt to talk about the long 19th century as a coherent unit running roughly from the Glorious Revolution of 1688 to the Battle of Waterloo in 1815. Some Western historians are also apt to talk about the short 20th century running from 1914 (the start of World War I) to 1989 (the fall of the Berlin Wall). Whether broad generalizations based in any versions of the 19th or 20th centuries are a kind of short-termism or long-termism depends on whom you ask and the trends or patterns they take from their periodizations.

–If so, you then can think of the “preoccupation” side of preoccupation-with as short-termism or long-termism roughly independent of the “with” side, the object of which can and is denominated in different ways. By way of example, short-termism for me is captured by: “Our inability to forecast the future is the mess we are in right now.” Long-termism, in turn, is captured by: “In the long-run there is just another short-run.” Both views are consistent with much of this guide.           

But you, the reader, come to the guide 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 preoccupation with a longer term is more in line with: “It isn’t a question of if it will happen but when it happens later on.” Other long/short-ism orientations are possible (e.g., those “middle-range views”), but the four just identified are sufficiently illustrative to make the following case.

–For the purposes of 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 these orientations. Take “the healthcare crisis” in the US.

Start with “the present rise in healthcare costs can’t continue this way indefinitely.” Now rescript the healthcare crisis through the other three orientations: “The current crisis in healthcare is that we can’t predict healthcare needs with the kind of specificity we need for taking effective 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 pandemic of an unknown virus will happen.”

In this rescripting, “the healthcare crisis” not only reflects multiple but different orientations are at work but also a major way the passage of time is differentiated and tracked (i.e., “the COVID pandemic has emerged as its own healthcare crisis”).

–Another implication is subtler but 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 orientation: Where, specifically, does “not-knowing the present” come into play in each of the four orientations?

Whatever the specific 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 ones serves to nail home this point further.

The virtue of center-staging not-knowing is to remind those preoccupied with variously denominated short-terms and long-terms that predicting the future can be difficult precisely for the same reasons learning from the past is difficult: Both require stability in objectives, institutional memory, fallback reserves in case something goes wrong, and low environmental uncertainty, among others. But we are in the Anthropocene: none of these conditions prevail.

–Did I write, “the virtue of center-staging not-knowing”? For many, the absence of preconditions for predicting the future and learning from the past is outright negative. For me, it is positive to start from the fact that not-knowing, inexperience and difficulty are each variable. This becomes clear when we move to the more granular case level.

Some regional climate change modeling is of such a high resolution today that model results can be and are in some cases disaggregated in ways of use to critical infrastructures. For example, 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 the pre-existing uncertainties related to depreciation and investment cycles? No. Do modeling results increase confidence that action with respect to these cycles can be taken, nevertheless? Now: possibly.

Section II.4     New environmental counternarratives

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

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

The specifics I have researched discriminate a more granular focus in environmental scenarios on real-time operations of human societies’ key critical infrastructures within a regional context—especially for those that drive, for good or bad, 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 within the Anthropocene;
  • Operations of key infrastructures because the reliability and safety of these large socio-technical systems—think critical 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 modeling increasingly accept the region as the unit of analysis for near-term risk and uncertainty management. (High-resolution models using LIDAR data and other GIS approaches already exist that provide climate-related flooding and wildfire information useful for critical infrastructures when it comes to their nearer-term cycles, e.g., for investment and depreciation purposes.)

Where do we specifically find new or under-acknowledged environmental scenarios? If the challenge is to identify specifics—that more granular focus on real-time operations of societal 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–the villains of the piece in many environmental crisis narratives. Yet because some infrastructures, particularly water and energy, are based in ecosystem processes and services, many of them 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 ecologists, biologists & renewable energy specialists directly onto the floor of the infrastructure control rooms. This is already being done, but not to the extent possible. If environmental specialists cannot now reliably advise on real-time infrastructure operations (already founded in ecosystem processes), why would we believe that those promising to do so later on will actually know by then? In the real world, complex large systems are only reliable as the next failure ahead. Why then is preventing the next case of failure any less important than putative failures in the later future?

Practice 2: Redefine system boundaries. Wetlands have been an iconic ecosystem in ecologists’ stories. Yet wetlands serve as “ecoinfrastructures” in other large system definitions. Those that moderate the effects of wind and waves on the adjacent levee structures are, as we saw earlier, part of the levee system definition just as the levees provide an ecosystem service by protecting these wetlands in other adverse events.

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 floodfighting 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 (San Francisco 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 key empirical issue is where that extra investment would produce the greatest positive impact on the ecosystem and landscape: planting trees and greenscapes 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 (needless to say, politically, culturally, geographically. . .as well), the devil is in the detailed scenarios.

Practice 3: Act on the full implications of the infrastructure control room as a key institutional & 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. Let me mention several. We keep hearing that global problems must have global solutions. If true, those solutions will never be highly reliable at that scale. There is, for example, no global water infrastructure nor a 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. (We’ve embarked on doing so in California.) It is far more plausible to imagine water and energy control rooms coordinating at the regional level than globally when it comes to collaborating. Indeed, some argue that it’s far more plausible that global fossil fuel accounting frameworks be based on really-existing physical and capacity characteristics of site-specific fossil fuel infrastructure than the more abstract definitions of fossil fuel “reserves.”

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, more) depend upon critical infrastructures for their survival, it’s important that environmentalists and other concerned groups recognize the early warning signals—think: storylines—that indicate to control room 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 it 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.”
  • Real-time operational redesigns (“workarounds”) by control room operators of inevitably defective equipment, premature software, and incomplete procedures are not effective.
  • Control room skills as professionals in identifying systemwide patterns and undertaking what-if scenario become attenuated or no longer apply.
  • 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.

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 another source of future environmental narratives—and one more fitting with global and regional complexity.

Let’s leave the control room for a moment and move to the field site. Two ideal types, the carvers and the molders, drive current narratives about site-specific ecosystem restoration. In idealized form, carvers see their task is to release the true ecosystem from the surplusage around it. Chip away at all that population increase, chisel off the built environment, get rid of the non-native species and banish pollution—only then 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 (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 complexity may be little like the pre-disturbance or pre-settlement states. (Indeed, the grievance that ecosystems are continually degraded signals landscapes are moldable.)

–Now the important part: Unsurprisingly, really-existing ecosystem managers and restorers fall somewhere between the two textbook orientations—they are ideal types after all—making do with what’s at hand and with what is possible. What is clearer now, however, is that this good-enough improviser is itself a third ideal type for ecosystem management and restoration.

Think of this third ideal type as its own narrative. The newly credentialed environmental professional starts with the expectation that the “ecosystem” or “risk” or “tradeoffs” are out there to be identified, only to realize in the field that each has to be specified in more detail. (Risks with respect to what failure scenario? Under what conditions does your solution hold? Just what is this a case of?) As practice continues, the environmental professional gradually recognizes that his or her challenges arise because what is out there depends on how “it” can be 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 storyline isn’t sufficient case-by-case.)

Improvisation has its own idealized and practical benchmarks and practices. You see this, most prominently, where cities are discussed as “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 the case-specific narratives look like 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 here this point needs to be pushed further.

I, for one, want to know more about the real-time conditions under which middle-level operators and managers in China are operating these large-scale infrastructures. Are the reliability professionals not there or are they there 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 them 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 revolves around “environmental governance.” Here I focus on an early formulation of governance. 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 the case studies and associated literature reviews in their edited volume, Governance for the Environment: New Perspectives. For our purposes, note the environmental arenas where multiple spheres overlap, particularly those related to what has been called eco-labelling, placed at the center of Figure 1 (the shared area of the three intersecting sectors).

One 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,” but some organization invested in high reliability above and beyond that of the US Army Corps of Engineers, California Department of Water Resources, and Delta-based reclamation districts). 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 met 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 deepwater 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 that which was levee uncertified. Yes, this would be “political,” but that is not the point. We need to push further: It is at the case-by-case level (say, different delta by different delta) that politics must be expected to vary.

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 many 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.” He has been criticized for his role in colonial British ecology, but here Tansley is of 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. Those had just-so stories about “climax communities” evolving on their own—if and 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 ecological societies in many 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 the profoundest 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 large critical infrastructures, created to satisfy desires and wants, as having Anthropocene 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, a point made by Adam Phillips, the psychoanalyst: “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”.

So, the same could be said of Nature’s contingencies and our relations to them. Fair enough, were it not for Agnes Heller, the philosopher, concluding the opposite of Phillips and with respect to the very same contingencies:

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 (not the only one obviously) stirs us to ask under what conditions is her point also the case. And I think those reading her passage can see what she’s trying to get at: For our purposes, we have yet to make what we can of the Anthropocene’s risks, uncertainties and unknowns. Complexity and contingency are not the same thing: Accidents, chance, luck and happenstance occur but within complex contexts and the context here is a very complex Anthropocene. 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.

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.

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 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, and so must our responses be, where that background condition of having many sides inherently frames the action we take. As will become clearer later, humans are intractable only in being intractably many-sided.

Conventional risk analysts and crisis managers are quick to counter: “What do you mean we are one-sided? 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.


Section II.5     New benchmark and metric for risk, uncertainty and not-knowing

Section II.6     A typology for policy and management difficulties and implications for income inequality

Section II.7     Other typologies for the Anthropocene, Or making the best of linear thinking when it comes to “coordination”

Section II.8     Chop-logics about risks, tradeoffs, priorities, and existential threats are not appropriate for the Anthropocene

                        Take-aways for Anthropocene policy and management

Section II.5     New benchmark and metric for risk, uncertainty and not-knowing

Let’s begin with risk and uncertainty and in the process discuss relevant aspects of not-knowing (variously, ignorance, unstudied conditions, unknown-unknowns).

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 failure is the product of the probability and the consequences of failure; 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 in the guide, the language of risk and uncertainty is now 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 thing 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 in real time for management.

An 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 encircling levees are needed because its productive areas are considerably below 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 should counsel against plans to place, say, a 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 just 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 to think 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.

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

  • Criterion 3. Priority for addressing levee fragility is with respect to 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 question becomes then: 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 such 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 the points 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 distinctions. You’d be wrong. Criterion 3 was altogether outside remit for conventional risk assessment and management at the time of the research. Major problems with the ritual calling for “more coordination” are discussed in Section II.3, which offers a very different recasting of coordination.

Broader methodological implications of with-respect-to scenarios. Before proceeding to better benchmarks of Anthropocene risk and uncertainty, it is important to tease out what is meant and entailed by “with respect to”:

  1. If you define risk of failure 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?)

Accordingly, 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 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 never 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.

  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:

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

It becomes an open question after a point 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 dangerously wrong seemed limitless.

In other words, the probabilities and consequences of large system failure can be underestimated 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.

  1. Underestimation 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 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.

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? Against this background and in comparison to conventional risk analysis, at least three new benchmark metrics for major risk and uncertainty can be identified primarily by virtue of their differentiated with-respect-to failure scenarios.

I.             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 no separate and island, then better practices emerge for ensuring that. (Again, this is why we look to evaluating existing risk mitigation programs and measures, and not just in the infrastructure concerned but also in like infrastructures.)

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 power 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?” should be preceded by: “What’s working?” “What’s even better?” “How can we get there?” and 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? (Needless to say, the complexities in these questions can be addressed interactively rather than sequentially.)

II.            A new metric for ranking crisis scenarios

Start with a better-known prediction of Martin Rees, 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. How might we evaluate and rank his prediction in terms of risk and uncertainty as understood in this guide?

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 did foresee 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, and fast-spreading pandemics of as-yet unknown viruses lack comparable specificity by way of their 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 disaster scenarios into fractions or multiples of Wilsons?

The temptation is to dismiss outright that Woodrow Wilson foresaw the future. Were that dismissal scientific consensus, it would then be quite significant: Here at least is one scenario that is just-not-possible. To render any such finding means, however, the criteria used for concluding so apply to other crisis 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, though, become clear. To ask how confident specialists are specifically about nuclear terrorism quickly becomes just what is meant by “an act of nuclear terrorism.” What, indeed, are the pertinent with-respect-to scenarios? 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 now is 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 catastrophe 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, though, 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. Whether the masses of 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, where possible, are those crises whose details have already been triangulated upon and thereby confirmed.

III.          A new metric for estimating societal risk acceptance

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 then to any retrospective orientation to failure, as in: “Well, it hasn’t happened in the past, 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 being based on past (in)frequencies, it is grounded in the expectation that all manner of major system accidents and failure lie in wait unless actively managed against (again, manage as defined in Part I)?

I suggest 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.

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

While major assumptions, the virtue of the preceding is in seeking to operationalize in far more detail what current retrospective risk approaches do not. Most notably, the ALARP (“as low as reasonably practicable”) method  assumes “society sets acceptable and unacceptable risks,” often leaving the implied somehow-this-happens utterly devoid of the necessary specifics. But there have been few alternatives to versions of ALARP (at the time of writing). For example, below is a found ALARP graphic used in an NSF research project I was involved in on levee fragility in the California Delta:

The figure shows estimated probabilities of 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 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 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 emergencies when options have dwindled, to impose onto their service users a single emergency 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, e.g., 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 so.

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 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 jobs. Contemporary examples abound, e.g., these performance modes and risks were evident in the public health infrastructures over the concatenated COVID-19 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 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 control rooms and infrastructures 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 a precluded-event standard by their 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 societal risks at the time of calculation for the critical infrastructure services of interest 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—for the present.

–Even though all this is difficult to detail, let alone operationalize—but less so than the conventional 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 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 (or last surge in case of COVID-19)—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 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 also 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 but different 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 errors under the pretense it’s all about “the politics of risk management” anyway.

Section II.6     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 for our purposes 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 events): contingent, tactical, modal, and ontological. Our example 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.

As contingent difficulties, “Just what does uncertainty and its assessment or management really mean?” has any number of 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 poses obscurities that are deliberately difficult and not meant to be settled by looking up an answer. Legal ambiguities may be intentionally introduced in documents or situations 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?” To focus on connective tissue of both questions, 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 to observe, prices modeled on the prices of inputs into that model, or something else? Or 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 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 chancy circumstances, and how that experience changes personally or interpersonally. “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 get a glimpse that 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.” (Such could be conceded for the Killing Fields of Cambodia and Hiroshima/Nagasaki, to name two others.) As ontological difficulties, inequality and uncertainty radically alter our humanity. They make us in ways indescribable and beyond the limits of cognition, knowledge and feeling.

Major Inference. While the four types of difficulty come brewed together, first-order 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 only provisionally.

Two, those who handle these difficulties are often found in teams, groups and networks rather than individually, since the difficulties are so knowledge-intensive that they require varied experiences with heterodox contingencies in heterodox contexts. So too in 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, by definition, differentiated, at least in that or other ways.

The upshot is profound: There are costs in asking us to address 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. Even the contemplative life is made difficult by daily versions of latter, that is, 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.)

Specifically, the difficulty with “a more equal or less risky society” isn’t that society is idealized or reified, per se. Rather the ideal of a more equal and less risky society is not as variably difficult as are inequality and high risk 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.

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. There still is that broader caveat, though: The more experience with complexity and not-knowing we accumulate, 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 needs 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?

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 you) 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:

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 more complicated than its inequality.)

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, think of 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 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. For example, 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 growing 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 that 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, 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” as it in some places, unequal or not? 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—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 be extended, but stop there. I have been talking about 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 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: “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 surely 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 would mean: 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. This would be much along the lines that no single heart is the same as another but these and other different hearts set the stage for recognizing and differentiating patterns, “healthy” or otherwise, across them. 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.7    Other typologies for the Anthropocene, Or making the best of linear thinking when it comes to “coordination”

It borders on truism that the Anthropocene requires unprecedented levels of coordination among the disparate populations and nations of the world. In light of the increasing calls for better coordination, 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. In this view, “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 do it when generalized across cases, when it—or something very much like it—needs to be done in the cases at hand. 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). Calls for more coordination are unavoidable when the remaining uncertainty, complexity, incompleteness and conflict need to be reduced but are not at that point reducible: “Thus,” it goes, “we need better coordination.”

If so, then the call for thus-coordination is an empty signifier for our having not yet recast the issues to determine whether we can better tolerate or 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.

Surprisingly, doing so 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 by relying on linear thinking. So, 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 or some such table is easily criticized for simplifying reality. That, however, misses what has always been the latent methodological function of typologies in the 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 granular for differing implications to become visible. Multiple typologies are not the pieces that complete a picture puzzle; they make a puzzle detailed enough to see a different puzzle or puzzles already there. Robert Capa, the famous photographer, put it: “When the picture is not good enough, go closer…”

–The typologies in my own 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 obvious 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., “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)

No major issue emerges unchanged from the seriatim application of these granularizing typologies. More, Anthropocene issues—be they inequality, poverty, war, climate change, pandemics, healthcare or more—merit their application.

But in all this, remember the cardinal virtue in applying typologies. It is to move you from the myriad types of contingent (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, or whatnot. It instead is to move 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.

–Where the preceding holds, no single casting or recasting resolves the amalgam of uncertainty, complexity, incompleteness and conflict that remains after (re)framing a complex policy and management issue. The question before us, then, 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. . .”? Either 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.

Section II.8    Chop-logics about risks, tradeoffs, priorities, and existential threats are not appropriate for the Anthropocene


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 will tell you each very major disaster is different. While admitting commonalities, they insist the emergencies they have experienced differbecause of 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’ll deal with the methodological dead-end of existential threats in a moment.)

Take any major policy issue—not just as an emergency—and start analyzing it. Much of the talk quickly becomes one about the risks involved, tradeoffs they reflect, and the priorities both call for. Even trained professionals, who should know better, take for granted that RTPs are, well, the natural place to start analysis in a world of limited resources. You certainly see the same for the Anthropocene.

I can’t imagine a more misleading and misguided way to analyze complex policy and management now and ahead.

It’s a chop-logic when assuming (1) difficult policy and management share the same starting point and (2) their first-order differentiation is around different kinds of RTPs (financial, environmental, you-name-it). Why? 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. This central tendency should be expected to continue, even if (especially when?) these infrastructures are more sustainable and just in the future.

–Three sets of empirical reasons for this being the case come immediately to mind.

Empirically yes, it’s obvious that major critical infrastructures—like those for electricity, water and telecoms—operate under budget and personnel constraints. Obviously, risks, tradeoffs and priorities surface and at times take center-stage when path dependencies are as long as they are 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. Why? Because when the electricity grid islands, people die. 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 some kind of designated emergency planning and preparedness or pre-disaster mitigation programs.

Empirically, when a sudden catastrophe does happen, the pressing clarity, urgency and logic 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 really matters and will continue to do so in the sudden and abrupt emergencies coming.

In fact, there is no better acknowledgement of the importance and centrality of 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 normal operations fail across infrastructures.

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

Even so, really-existing analysis and deliberation during recovery are far, far messier than, e.g., “the risks, tradeoffs and priorities with respect to flood recovery are the obvious center of attention.” Entailed in an RTP-logic is the frequent assumption that the real problems in recovery are bad politics, follow the dollar, and jerks undermining good work. The actual problem is that the chop-logic of “P follows from R and T” isn’t anywhere near reality. Being anti-empirical gets you only so far.

–Methodologically, this empiricism means that the first-order differentiation in policies and management that are critically society-wide is not presumptively around RTPs. 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 and contingently path-dependent, if not case specific.

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


The 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 us 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 suddenly.

It is notable that the climate emergency has yet to elicit this type of social dread to prevent the precursors of climate change from occurring. This failure to preclude the causes of 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 the next section (Section II.9): 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.

Think of this scenario as a local template for global destruction scenarios. Everyone we’ve interviewed recognizes an earthquake-racked CEI poses an existential threat to lives, property and ways of living not just in Portland but for the state and beyond. And just like global climate change, the social dread this elicits is not at a level to do more than tinker with this or that CEI pre-disaster mitigation.

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 plane travel and tap water don’t kill them and that electricity lines don’t routinely collapse and electrocute them. 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 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 screaming inside the plane plummeting to earth, or retching poison at the kitchen sink, or caught by power lines whipping and sizzling about them.

This grip of the Real is of course tied very much to the brain as it has evolved—fear and flight response in the primitive amygdala, the much more recent kludge of the prefrontal cortex, and the sense of certainty that comes from one’s limbic system.

–So what?

Not only do many people mistakenly think they see through a clear pane of glass outwards, many also believe we can bracket the historical, cultural, and societal exigencies that color this seeing: “At least I recognize I’m biased.” Even then, hardwired cognitive biases (confirmation bias, attribution bias and more) crisscross the pane with all manner of defects, which we can only hope are not mistaken for existential threats.

Where, though, is that hope? The notion that hope is rooted in neurology but existential threats aren’t would itself be an existential threat, if many of us 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 be bargained down. Hope is not traded-off. In this guide, hope is to existential threats as high reliability is to critical infrastructures. In other words, the problem with dreaded existential threats is not only that there are other not-so-dreaded-but-should-be existential threats. It’s also because hope is another way to take those threats very seriously indeed.

Methods: Take-aways for Anthropocene analysis and management

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

You should see recasting not as the goal or end in itself, but as a way of reaching a granularity (different granularities) more tractable for this policy and management. Methods that drive us to asking and making explicit “with respect to what” are key here. So too, as we saw, for counternarratives that rest on contingencies and specifics already present but avoided or ignored by prevailing crisis scenarios. 

The underlying method of recasting starts with recognizing the conceptual possibility of recasting the intractable (that is the purpose of conceptual framework in Part I) and the empirical cases of recasting the now seemingly intractable (that is the purpose of the “real-life” examples in Part II). Without presupposing any guarantees, if you land on one or more insights—think of insight more formally as different granularity—that you hadn’t (fully) realized before, you use that to extend your analysis and actions further and more usefully. Redescribe, reframe, recalibrate or revise are the guide’s operative descriptors of this basic approach. You could as well say you are rewriting, recycling, restaging, reclaiming, or (re)presenting precisely because of the issue complexities.

Key Concepts

Section II.9     “What’s missing?” in this catastrophic earthquake scenario

Section II.10   The problem with adaptive learning and management in the Anthropocene

Section II.11    What to do when criticisms are spot-on, but the recommendations aren’t

Section II.12    Begin, rather than end, with the radical agenda

Section II.13   “Managing” risk and uncertainty, or coping better ahead with inexperience?

                        Take-aways for Anthropocene policy and management

Section II.9     “What’s missing?” in this catastrophic earthquake scenario

Return to Part I basics: A system is more or less complex in terms of the number of components it has, the different functions each component serves, and the degree of interconnectivity (latent and manifest) between and among the number of components and their differing functions. This social science definition isn’t the only one (cf. complexity is the ineffable beyond words), but the problem in practice isn’t too many competing definitions. Rather, in ordinary language people talk about complexity as if everyone knew what it was, only later having to conclude “it must be more complicated than that.”

Two conclusions follow from our Part I definition. Right off, the imperative is not, “First, simplify!,” but, “First, differentiate!” What components? What functions? What interconnections? Equally important: Complex with respect to what? Complex under what conditions? Only in probing this way, I believe, can you come to understand what you have simplified by taking it for granted.

If the point of departure is, “First, differentiate!,” then the chief question to ask upfront is, as we saw in Part I: “What am I missing that’s right in front of me to help with that differentiation?” If you can’t see what you’d be seeing if it were not for your blind-spots (cognitive, professional, other), how can you expect to find the complications that matter but aren’t visible, as if behind your head, out-of-sight?

–This guide means “what’s missing right in front of me” literally. First, two examples from outside policy and management. 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 to 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’s print,

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

–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 a second or further 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 astounding still, overlooking the complexity is that simplification taken for granted which robs us of surprises that can 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 that world, new connections can and are to be uncovered all the time where not-knowing, inexperience and difficulty are ever present.

Now an example of how what’s missing and the rest work in policy and management. So as not to make this easy, consider what many call the most catastrophic natural disaster in the United States, were it to happen: a magnitude 9.0 earthquake in the 800-mile long off-shore Cascadia subduction zone in the Pacific Northwest. To make the impacts real, I focus on research and work at one specific 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 (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 highly 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 confirm.

Unsurprisingly, 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 my thinking is distracted by a familiar counternarrative that stirs to mind: Today, it’s easier to imagine an end to the world than an end to capitalism.

It’s easier to imagine a M9 earthquake scenario both obliterating an even better-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.

–Which returns us to the aforementioned “Unsurprisingly.” Say again? “We know the earthquake is coming. We know we have to take steps to address this.” Huh?

In fact, think a bit more about what they don’t—can’t?—see right in front. What better way, save war and the plague, to bring the governments of in the Pacific Northwest to their collective knees than ‘‘solutions,’’ like those pre-disaster mitigations, because 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 “easier to imagine,” we are to believe, is taking complexity seriously.

(Apologies for the sarcasm. As novelist Muriel Spark put it, sometimes ridicule is the only honest weapon we have left.)

Section II.10    The problem with adaptive learning and management in the Anthropocene

When I started out 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. Learning need take them only to where what they don’t know doesn’t add or subtract value for their acting now. 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.

The appeal of optimal ignorance waned when I implemented projects that I had helped plan. On those occasions, 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 formal education in public policy analysis.

My own view 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 in the imperfection of circumstance. But I didn’t fully understand that until considerably 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. Optimizers with whom I’ve worked, on the other hand, 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.

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. Yet, as with soil and water conservation and other projects, we must ask: managing adaptively for what? With respect to what scenario granular enough for its details can be evaluated?

What is often desired, moreover, is its own scenario of high reliability water, water, water—reliable water for urban use, for agricultural use, for ecosystem rehabilitation and the environment; for ports, for shipping lanes, for recreation, for hydropower, for. . .you name it, water is needed for it. 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, less interconnected, 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 messes 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”.

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?’’ 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 those 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.11   What to do when criticisms are spot-on, but the recommendations aren’t

Most readers have probably experienced reading something on a major policy issue that was utterly convincing—up to, that is, the recommendations offered. “Where did these come from?” you’re left to guess.

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 the solution? Yes, Big Polluters continue to damage and harm the environment under the pretext of committing to specific climate change measures; but when did banning them, immediately, verge on 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 and too many political wills—we need to do this!—and that!—and those!—and these!—and you, you need to do even more!—are the principal source of so many of the difficulties in falling well short?

Convincing criticisms that led to nowhere feasible once exasperated me. It took too long to realize that my “These people 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, not them. I may not be smarter, but my framework—this guide’s framework—helps usefully to differentiate matters. 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 are and for the very reasons they have established.

First, I’d ask the policy advocates to push each recommendation further with, “Yes, but…?” Yes, the recommendation holds, but does hold because it doesn’t go far enough? Second, I’d ask of myself: What am I missing right in front of me, when it comes to their recommendations? I consider them implausible in stopping short, but can I recast their recommendations in a more tractable way without losing their seriousness and urgency?

Let’s address each question and conclude with the major implication.

     Yes, but?

There is nothing wrong with recommendations that are in effect a wish-list. Wishes keep us going—as long as: Be careful of what you wish for!

Being careful requires more than establishing whether or not the references and citations in support of the recommendations actually do the job. Checking sources is needed, but that too does not go far enough. Why? Because research on complex policy and management issues is more than likely to uncover mixed findings, some or many of which are limited in scalability.

But mixed findings do not mean you are stalemated into calling for more research before all else. Mixed results suggest findings may be sufficiently differentiated by sites and cases around different means and ends. More, differentiation in means and ends implies not only that some results reflect useful work locally, but also that useful practices may be evolving over a run of the different cases.

An example helps. 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—we 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 these 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:

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),” advises 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, including in this guide). But no amount of “immediate,” “drastically,” “vastly” and such will stop the policy analyst and others from having to press further, “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, as in this example, 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 perhaps under constraints of politics, money and egos similar to or worse than your own case?

More, the second you differentiate is the second you begin treating seriously the unintended consequences of implementing blanket recommendations and macro-design “solutions. Which leads us right 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 killing even more? Or from the other side, Are we in a position to do something major and not know it?

To ask those question takes us full circle back to the need to differentiate further by asking: Where is there political will left to stop these polluters—if not here, at least there, then, and under those conditions rather than others? Where is there a track record in people seeing they didn’t know all that they thought they knew and knew more than they initially had thought about net-zero emissions or some such? Only in these ways can we see what’s not on the wish-lists that are even more efficacious. Equally important, doing so treats the recommendations with the same seriousness and urgency as do such reports.

Section II.12    Begin, rather than end, with the radical agenda

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 the subsequent paragraphs lead? In what directions do I drive what is now my agenda? To make this interesting, I sketch five extensions of this guide that most differ, I believe, from what the authors appear to assume:

  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, then elsewhere? My 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 I pre-define key terms (capitalism, power, democracy. . .), the better practices identified in #1 do the next best thing: entail the ends sought by the means used. Here, behaving democratically is with respect to these practices to achieve those outputs or outcomes. There, power is supposed to be controlled by these means for those ends; elsewhere, power is actually managing in these rather than those ways as control is not (if ever) possible.
  3. Instead of starting by prioritizing what do first, second and afterwards, 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 more. Each new argument is assembled from older effaced ones; even when each argument seems connected and integrated, it is in fact an unstable composite of fragment and image. Resurfacing earlier erasures is a way to signal where my paragraphs can go. 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 differently. 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, and 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. Better to know this than delude ourselves in thinking it’s about “Reduce uncertainty!,” when not “First, simplify!” (The guide recasts “at sea” for the Anthropocene in Section II.16.)
  5. Instead of seeking to integrate the agenda into a single coherent 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 two references to “infrastructures.”

But these point raises a productive question: Are there conditions under which money is an infrastructure just like large scale water supplies and electricity grids? One such set of conditions suggests itself to a writer such as myself, namely: when government releases emergency funding to recover from those disasters that have destroyed the infrastructures upon which we survive. Here, money and assets are fungible. By extension, think of the agenda as a massive emergency response to recover critical infrastructures (like that for justice and education) that failed us.

–Such would be the gist of Results section in my proposed article. I’m in no position to sketch a follow-on 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, “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 I fervently hope not.

It’s not just the contingent (idiosyncratic), complex and uncertain remain unavoidable whatever our agenda for the Anthropocene; it’s not just that the unfinished here may be unfinishable. Nor is it just that case-by-case economic and political power is far more complex than its power’s usual adjectives–direct/indirect/dispersed–convey (the complications are discussed in the guide’s Conclusion) It’s also because your radical differs from my radical, while radical responses, including social movements and revolts, are to be expected regardless (precisely because?) of the differences. If people of the Earth are as equal as the teeth of a comb, the numbers of different combs are too many to add up.

Section II.13   “Managing” risk and uncertainty, or coping better ahead with inexperience?

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

For this guide, inexperience is one proxy for not-knowing. How this matters for now and ahead 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 routinely supposed and not just with respect to central banks.

–Fed chair, Greenspan presented a major paper, “Risk and Uncertainty in Monetary Policy,” to the American Economics Association, which published it in the Association’s Papers and Proceedings of May 2004. As Greenspan 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.

All the above makes sense—and eminent sense for the Anthropocene, right?—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, the policy management approach still looks reasonable for accommodating risk and uncertainty: That is, as many others have summarized, don’t get caught in intellectual 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. That track record, if it existed, 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 we will have to credit more of the 2008 financial crisis to inexperience than, as now, 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-) COVID-19 pandemic responses by the central banks of the world’s major nations.

Better coping ahead with inexperience

Inexperience is identified as a major factor in other financial crazes than just that of the 2008 financial meltdown. To see this 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. 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 worth reading still—were well-regarded by the reading public and luminaries. I quote at length an astonishing, 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 his reiterated honest men duped by inexperience that deserve a second look: Does this mean our finance officials 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 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. Additionally, 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, in the one case due to term limits and political burnout and in the other case due to constant economic churn. The only redemptive feature in this is a messy this-worldly 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.

To repeat, there are of course no guarantees. More important is this for Oliver: 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:

The circumstances that surrounded were complicated and bewildering; the gleams that guided him were intermittent and often of a twilight dimness. A statesman so situated must do much by guess-work… 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 belooked 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 the words all but describe what Part I has termed coping ahead better when one can’t manage anything longer term—that is, not just reacting but working out the next steps “for on the morrow.” That too is precisely the Anthropocene: complex, now.

There is in other words a track record in coping ahead in the face of what you and your colleagues have (yet) to experienced. 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 all around—that you and your colleagues are better adept at coping ahead than the deluded beside you. (A development practitioner’s track record of different setbacks looks a good deal more useful when compared to 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 shared.

Key Concepts: Take-aways for Anthropocene analysis and management

If ever there were a concept in need of greater differentiation and granularity, it is “interconnected” and its cognates. This guide, however, seeks to demonstrate the reverse as well: “Interconnectivity” becomes a key concept in recasting the moment it is used to differentiate cases 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 first real experience of just how important and useful the latter tactic can be.

To cut to the quick, after a year or so of research did it become clearer there were at least five major kinds of “interconnected” at work, having 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 was reported to us);
  • Combined 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 failure and recovery (SAR);
  • Variety of real-time configurations of interconnectivity: The VTS manages by virtue of resorting to a variety of interconnections with the vessels concerned. When VTS management of a common pool resource (the waterways) on behalf of inter-related vessels is disrupted or fails (e.g., because of defect 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 too many conventional approaches to risk management of critical infrastructures were so mis-specified and misleading (as described in preceding sections of Part II).

The broader point is this: “Interconnectivity” as a key concept for the Anthropocene is a major way to learn about specifics that matter when it comes to “with respect to what.” Not only do you need to know a lot about what happens on the ground, you need to know a good deal about specificities to understand the importance of searching for new ones. This means the case level is unavoidably and in that way usefully central. The last thing we should be doing in the Anthropocene is abstracting about interconnectivities before recasting their particularities.


Section II.14    Policy palimpsest: concept, examples, and the violence

Section II.15    Heuristics as clues

Section II.16    The genre of wicked policy problems

Section II.17  The analogy, “we are at sea,” remade for the Anthropocene

Section 11.8 Thinking infrastructurally about 7 major policy and management issues

                        Take-aways for Anthropocene policy and management

Section II.14   Policy palimpsest: concept, examples, and the violence

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 sensibly—nouns and verbs appear in order and sense-making is achieved—but none of the previous inscriptions are pane-clear and whole through 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 this page. 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.

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 is to read any new composite argument with the blurred-away now made visible in order to acknowledge and probe what has been made 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, perhaps more tractable 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, not to put too fine a point on it, 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 profound problems with its assumptions.

Yet even if 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 many academic journals, is the polemical avowal that America deserved 9/11 as a nation and now that it had happened, here was the opportunity for the nation to take the lead in a new rapprochement with the Islamic world. This argument was expunged from the discussion, where “straight-forward” policy arguments since 9/11 have been attempts to bowdlerize 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 the 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, I believe, to the Anthropocene. What then am I missing in my own arguments? A great deal, I confess—though I believe this enriches rather than paralyzes 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 said, “Well, we had to do something like the ETS.” One option is to answer her now. Another is to update my history with more fine-grained information on ETS implementation for the period 2005 – 2018. A different option is to bring the history up-to-date since 2018 when I wrote most of the preceding paragraph [2]                

It now seems to me that the paragraph can be substantially recast via the ETS’s policy palimpsest, irrespective of these other 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 implemented is intermixed with proposals that weren’t. The challenge is to reread my earlier description with the elements I effaced now visible. To repeat, resurfacing earlier points that are right there in front of me but which I missed is my start in thinking along different lines. (In truth, policy palimpsests invite such foraging.)

–If the composite argument can be viewed as a larger fragment assembled from smaller ones, then my ETS history is punctuated with interruptions blurred out in the name of readability. The problem, which only later I understood, is that fragments not only differ by virtue of their content but fragments differ importantly in kind.

For this guide’s purposes, there are at least three kinds of “fragments,” small or large (see Davis 2019): that which awaits finishing or completed, that which survives after being finished or completed, and that which is (no longer) finishable or completable.

You confront a hole in the ground. In one version, it surrounds the foundation upon which a structure will be built. In the second, it surrounds the remaining ruins of a previous structure. In the third, it surrounds what is now nothing: What was there has rotted or eroded away entirely.

By extension, one missing element in my earlier ETS history is the open question about just what kind of (larger) fragment the ETS is. Is it primarily an institutional structure 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 quick: 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.

–What do I mean by resurfacing “more useful leads” or better yet, “ways to recast more tractably”? By way of illustrating, let’s turn from a European example to a global one.

I wrote this following originally just as COP26, the 26th United Nations Climate Change Conference, ended. For many whose opinion I respect, it was a failure to do the needful in limiting temperature rise. Let’s say that is true.

Even then, the crux is not, e.g.: “Thus,” alternative voices were left out and alternative politics side-lined. You can no more essentialize those voices and politics than you can essentialize the conference. (To think you could is like thinking a composite argument essentializes its policy palimpsest.)

This means that one of the first questions to be asked of the conference is: Which COP26 failed? Any such conference is never one thing only, if only because those attending in Glasgow were being themselves in one venue, while being other selves in other venues there. COP26 was riddled with this kind of intermittence and who’s to say the earlier or later versions between October 31 and November 13 2021 are not its upside? To declare the conference, overall, as a failure (or success for that matter) is to colonize that intermittence with your own people.

Which is to say: I’m sure I’ve left a very good deal out in stopping short at COP26 as an overall failure. Just as I did in my history of ETS travails. So too presumably for this guide’s “being at sea” and the Anthropocene as their own palimpsests.

Palimpsest violence

Earlier I said 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 also 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. What’s missing has been made missing by suturing the fragments. Or think of it this way: the latest composite arguments read off a longstanding policy palimpsest can have negative seigniorage, i.e., they’re a public currency whose social costs of production may have far exceeded their face value.

The typical excuse for this—“We’re only generalizing from case material”—is no more valid than saying a statistical meta-analysis of mixed findings is tracked by the standard error around something called an average. It’s more complicated than that.

Claiming that over-arching explanations of power, for example, are empirical generalizations made across complex cases too often voids the case-specific diversity of responses and emerging practices of importance for policy and management. Part of our duty of care is to question any over-arching explanation or the soft-packaged imaginary that comes masqueraded as a generalization founded in cases when it is nothing more than a highly-edited composite off a policy palimpsest that has long had a life and heft of its own.

[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.

Time also changes in assembling fragments from different parts of a palimpsest. The composite may appear to be “first-this followed by that-then,” when instead separate fragments are juxtaposed as if, say, one is now read as a textual gloss about time annotating nearby fragments about something else. 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 everything below or after it. (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.15   Heuristics as clues

Long-held heuristics, like 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 of which enable making decisions in the face of uncertainty. Both shorthands are treated pragmatically as good-enough, like a new atlas of maps.

The older heuristics are relied upon because they are 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. 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 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 comprehensive bibliographer of 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, albeit 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. Correlations index spatial-temporal references to be pursued.

–There is no obvious point of entry when it comes to revealing wider references. For purposes of illustration, start with the canonical index of fire, smoke. In the same way, the heat from server centers (some now call it “data exhaust”) indexes the large electricity usage in generating and updating algorithms. But context doesn’t stop there. Other clues are less spatial-temporal and more social for the heuristic inseparable from wider referential meanings.

Again, by way of example, the status of the algorithm-as-heuristic clues you into the underlying assumptions for using big dataset algorithms, not least of which exemplify “trust.” 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 the duty of care in using heuristics means treating them as indexes of that which cannot be omitted, yet could have already been omitted, from analysis and practice when usefulness with respect to complexity is the question.

Section II.16  The genre of wicked policy problems

Cease-and-desist orders should have been issued long ago against the haute vulgarization of “wicked problems.” Academics have long argued that more nuanced sets of terms for complex policy and management problems 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. How so?

To see how, recast wicked problems as part of a longstanding genre in literature, which 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.”

Intractability appeared 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, but also its governing context is as historically tangled and conventionalized as that of the English novel. Masses of complexities take center place in wicked problems both by virtue of content and context.

I am not saying wicked problems are fictitious (even so, there is the well-known truth in 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, in this case through novelistic means). Otherwise, we are like the 18th century French Academician when confronted with a relatively new musical form uttered in exasperation, “Sonata, what do you want of me?” “Wicked problems, what do you want of us?”

The answer gets us to the really important part: the conventions at work in wicked problems. Return to the scholarly attempt to differentiate “wicked” and “tame” problems into more nuanced categories. Doing so 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.

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? In this way, the answer to “Wicked problems, what do you want from us?” is, in other words, the irrelevance of the question. There’s little understanding, it seems to me, that labeling a policy issue wicked can over-complexify a problem that would otherwise be open to recasting into more tractable forms without loss of its complexity. It’s more than passing odd, for example, that social scientists and policymakers who declare policy issues to be wicked problems do not consult the rest of us who have a rather big say in accepting their labels.

Wicked policy problems are complex problems that have yet to be recast through their complexity. That is not optimism; that’s realism. As with much in contemporary policy and management, wicked problems have ended up as exaggerations: Even where that may be true as far as it goes, the truth of the matter needs to be pushed further.

In fact, the litmus test that an issue is overly complexified or overly simplified is whether or not it can be recast in ways that open up fresh options for intervention without gainsaying its complexity. If—and yes it is a big “if”—a simplification can be recast as complex in ways that new interventions are now plausible or if the issue thought to be so complex no further action is possible can be recast to show otherwise, then the matter has been pushed and pulled beyond the current exaggerations. To recognize that your account can and should go further is, on the other hand, no exaggeration.

Problems aren’t wicked when they are hard problems that profit from being left open. Instead, declaring something a wicked problem can create The Ultimate One-Sided Problem—it’s, well, intractable—for humans who are everything but one-sided. In effect, one-siders of intractability, Anthropocene or not, have taken the generous notion of intractably human and scalped it.

Section II.17   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, just as any wider selection of excerpts would have been arbitrary as well. 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. To be frank, that level of generality was not the first thing that struck me: What sticks out for me by way of contrast 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—anomalous connections—where none were before. I’ve done this through the arbitrary juxtaposition of quotations, as a way of extending my own thinking. And where does my juxtaposing the quotes of Tocqueville and Neurath lead me? Whither their 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 swelling ocean, heavy gales and thundering waves that the quotes share. Actual responses to these forces differ (that 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 has keeps us at sea in the Anthropocene. We’ll return in a moment to how this recasting helps.

Long-lived debates in the policy and management with which I am familiar have been fought at extremes: Market and Hierarchy; Coordination and Regulation; Regulation and Innovation; Innovation and Politics; Politics and, well, every other abstraction from Science and Technology. Worse yet: Holism versus Reductionism, Quantitative versus Qualitative, Positivist versus Post-positivist. Such has been the methodological injunction of First, simplify! and nothing about today’s imperative, First, differentiate such twofold contrasts!

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 apple 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 handle Arrow’s voting paradox, then everything would be okay. If only we took short-cuts to reliability and got rid of all that mess in between, we’d be better off. Then again, which way Africa: Kenyatta or Nyerere? Brazil: Is it race or class? Whither the world: Globalization or [fill in the blank]? 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 as practiced 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. Sadly, to focus on the spectacle and not the handiwork is the real  “policy blunder.”

As a newly-minted policy analyst (nor am I alone in this), I was told we had first to nail the politics. Without correct political arrangements, how can we have worthwhile 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. I remember being assured “After all, you can’t repeal the business cycle;” and with the correct macroeconomic and microeconomic arrangements in place, politics and political conduct have changed for the better, so I was assured.

We were then told later that, well, it’s really about getting the science 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!

And yet. . .the very same misdirection continues throughout. Farms continue to get their subsidies—be it because agriculture is politically important, food is economically important, carbon sequestration is environmentally important, and global politics is reallyReally more important without which there will be no earth, no climate, no food, no agriculture, no subsidies 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: In the terms and concepts of Part I, under what conditions and with respect to what specific failure scenarios?)

–Would you believe that installing the wheel closer to the engine gets you to your destination sooner? And yet…

How many times have we heard or been ensorcelled by something like, “If implemented as planned…,” “If done right…,” “Once the risks are controlled. . .,” or “Given market-clearing prices…” Sure thing, 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 controlled,” when any notion of control is ludicrous when 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: All these end up little more than the magical thinking of a primitive people. We could as well believe that the surest way to heat the house in winter is by striking a match under the porch thermometer.

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

Where then does reframing of being at sea leave us? (As the sample of quotes indicate, the human condition has been at sea a long time.) What does being at sea mean now and for the better in the Anthropocene? One answer is that earlier: Be careful what you wish for!

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

This analogy of the mythical animal skin recasts, considerably, the commonplace, “All that is missing is the political will to do what is needed…” Political will eats itself up and is manifestly a finite resource, sutured together case by case. 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.18   Thinking infrastructurally about 7 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.

But critical infrastructures are also a very useful lens through which to rethink topics of major importance like risk/uncertainty and low probability/high consequence events, or infrastructure fragility and market failure, or healthcare and cognitive reversals, or that ever-present worry, Big System Collapse. Below are seven (7) reconsiderations prompted by thinking infrastructurally about issues of ongoing importance, I believe, in the Anthropocene.

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

Think of an infrastructure as having an entire cycle of operations, ranging from normal, through disrupted and restored back, or if not, tripping over into failed operations, followed by emergency response including efforts at initial service recovery, then into asset and full service recovery, and onto a new normal (if there is to be one). There are, of course, 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 this segmentation from normal through to a new normal works for our purposes here.

I want to suggest that “risk and uncertainty” vary both in type and degree with respect to these different stages in infrastructure operations. In normal, disrupted and restoration operations, we observed infrastructure control room operators worrying about management risks due to complacency, misjudgment, or exhausting options. When infrastructures fail, 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 cause-and-effect is now replaced in failure by nonmeasurable uncertainties accompanied by disproportionate impacts, with no presumption that causation (let alone correlation) is any clearer in that conjuncture. Further, when there is urgency, clarity and logic 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, in earlier research 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.

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, it 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 kind 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 precisely 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.

More can be said, but let me leave you with those who insist “the new normal” is at best endless recovery, with far more having to cope with risk and uncertainty than proactively being able to manage them. There are of course no guarantees in the whole cycle, but at least its format doesn’t, e.g., miss Dresden-now by stopping the cycle at the highly controversial Allied bombings and devastation of 1945. In case it also needs saying, a new-normal, if there is one, brings with it dependencies that are both positive and negative.

2. Thinking infrastructurally about low-probability, high-consequence events.

Return to having to operate blindly and on the fly in widespread infrastructure failure, where cause-and-effect scenarios most often found in normal operations have given way to being confronted by all manner of nonmeasurable uncertainties and disproportionate impacts, none of which seem obviously cause-and-effect.

The point is that both nonmeasurability and disproportionality still convey important information for their infrastructure operations during and after the disaster. This information 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, the nonmeasurability of uncertainties and disproportionality of impacts tells them to prepare for and be ready to improvise, irrespective of what formal playbooks and plans have set out beforehand.

“Coping with risk” is highly misleading 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 a “low probability and high consequence event.”

3. Thinking infrastructurally about fragility of large socio-technical systems.

The last thing most people think is that infrastructures are fragile. If anything, they are massive structures, where “heavy” and “sturdy” come 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 socio-technical one with which I am familiar:

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.

Jackson S (2015) Repair. Theorizing the contemporary: The infrastructure toolbox. Cultural
Anthropology website. Available at:

The nod to “sociotechnical systems” is welcome as is the recognition that these systems have to be managed–a great 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.

What to my knowledge has not been pursued in the socio-technical 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 (we would say, 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 socio-technical literature with which I am familiar.

Finally, I cannot over-stress the importance of this notion of infrastructure fragility, contrary to any sturdy-monolith imaginary one might have. 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 of them endlessly massive and costly repairs and maintenance–but I confess that is my management take from a socio-technical perspective.

4. 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. They do not 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 U.S. 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 my 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 research 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 type of market failure. But 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-identified “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. Where so, efficiency no longer serves as a benchmark for economic performance. Rather, we must expect the gap between actual capacity and full capacity in the economy to be greater under a high reliability standard, where the follow-on impacts for the allocation and distribution of services are investments in having a long term.

5. 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, by way of example, can be made reliable and safe, at least up to the point of injection. Failure in those back-end 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, we 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 in the US that they could bring the healthcare sector down (say, as was threatened 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.

6. 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 have to risk failure in order to succeed! But what if the business is one of the many critical infrastructures privately owned or managed?

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 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 now mandate 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 U.S. Minerals Management Service (MMS) to convert the site to a production well. The MMS approved by the change. The explosion occurred five days later.

In brief, 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 oft-recommended approach, Be-Prepared-for-All-Hazards, looks first like the counsel of wisdom. It however is dangerous 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 really-existing impracticalities.

7. Thinking infrastructurally about Big System Collapse.

Here are early warning signals—typically not recognized—that the major critical infrastructures upon which we survive are in fact 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 it online for now!”)

–The 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.

–The decision rules operators reliably followed before are turned inside out: “Prove we can do that” becomes “Prove we can’t.”

–Real-time operational redesigns (workarounds) by control room operators of inevitably defective equipment, premature software, and incomplete procedures are not effective as before.

–Their control room skills as professionals in identifying systemwide patterns and undertaking what-if scenario become attenuated or no longer hold.

–Instead of being driven by dread of the next major failure, control room professionals are told that their track record up to now is to be benchmark for system reliability ahead.

I have yet to come across these as key indicators of infrastructure and big system collapse in the literature I’ve read.

Analogies: Take-aways for Anthropocene analysis and management

Analogies, broadly writ, make better visible just how much the exercise of recasting is not a one-way street but more like a traffic 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 toward other directions. To shift the metaphor, one configuration of the shards in the Anthropocene kaleidoscope is not definitive or sufficient indefinitely, no matter how attractive staying there may seem in the moment.

What does this mean practically? Here we come 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 “key concepts,” current and past, 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. Power, good enough and betterment in the Anthropocene

Other than references to politics, dollars and jerks, the guide might be seen as noticeably silent on the nature and role of power in the Anthropocene. This would be a major gap for a text so focused as this one on differentiation in public policy and management: Even a formal history of power as used in ordinary language would describe one attempt after another 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 7.5 plus billion people—numerous informal counternarratives, analogies and methodological approaches for power exist and thrive. Our Part II case examples suggest two take-aways in that regard: (1) It is at level of the case and the event where you best see material power—directly, indirectly, dispersed, differently—at work and (2) it should not then be surprising that generalized readings about power in the absence of differentiating cases are more problematic than supposed. (To put it another way: Material power is a very old, very overwritten policy palimpsest.) At best for this guide, reading power entails two readings: What you now know (how power worked itself out in the case at hand) might enable you to reread what you’ve read as “a case of this or that kind.” But two take-aways hardly exhaust the variety of really-existing power narratives and their significance for those seeking to recast more tractably hard problems in the Anthropocene.

Among the many under-reported counternarratives, the one below takes Part I key concepts as its center of gravity. To be clear from the outset, what follows is illustrative rather than seeking to pre-empt the search for better ones already differentiating the planet.

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, the 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 and must 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 the irreducible particularity of being.

Contingency is the chief feature of battle and contingency, as we saw in Part I, associates 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 before you. A host of very different practitioners put the point on behalf of their respective groups and collectivities (to read off the respective palimpsest in no particular order):

  • “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.” Note the accent on the we-collectivity here.
  • “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,” adds poet and art critic, James Schuyler. Goethe noted “my tendency to look at the world through the eyes of the painter whose pictures I have seen last”.
  • 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.

In short and to be blunt, it’s not good enough to say power is primarily about that A making that B do something instead. Nor is it good enough to say power is primarily about controlling the decision agenda or determining peoples’ interests without them knowing it. Power that is concentrated, or roundabout or everywhere present in no way exhausts power’s sheer variety. The power in this other 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. Call it power-contingency, for shorthand.

But you ask, “What is more important, power or contingency?”, and I tell you, “That’s like asking which chopstick is the fork…” I’m saying that the objective correlative of power is contingency. In this counternarrative, the great threat in addressing power is to think there is an outside to contingency, let alone outside complex contexts. This means surely the most powerful response to the Anthropocene headline, “Uncertainty is not our friend,” is: It’s more complicated than that.

“It’s more complicated than that” is, however, not good enough in the Anthropocene if treated as a conversation stopper, rather than the start of analysis and management. What then by way of conclusion is good-enough for the purposes of this guide and how does it help us better maneuver in Anthropocene policy and management?

Calling something “good enough” borders on the pejorative in the US, as in the “good enough for government work.” Less pejorative, but found wanting still, is the sense in which a second-best result is good enough only because the optimal [sic] is not—yet—achievable (think: efficiency benchmarks from microeconomics).

It’s useful at this point to summarize the take-aways about when good enough is better than said optima from the perspective of this guide’s Part I key concepts, Part II case material, and counternarratives allied to the power-contingency just proposed. The first take-away: We’ve seen that when it comes to complex policy issues, efforts at full or direct control to achieve results may 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.

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 take us further than we could have expected, albeit we want to go further still.

There’s also the sense in which “progress” or “growth” (economic, sustainable. . .) stops short of betterment, a really-existing good enough. (The annex has some of the relevant literature on good enough and betterment.) In this view, progress and growth don’t take us far enough. The problem with insisting on something like “progress” or “growth” arises when doing so means we can never be good enough today—better off today—by relying on yesterday’s standards. But of course we can. “But just how ‘good’ is good enough?” you ask. That, however, risks a systematically misleading answer: “You must respond within x minutes of a call. . .,” where goal displacement (that is, meeting the response criteria) becomes the end in itself.

The point underscored by this guide is that you work very hard to get to good enough since it can’t be assured once and for all. 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.” At that point, you are pushing the advantage of complexity further. In fact, I argue that recasting the intractable can usefully last longer. Plainly put, stopping short at a conventionalized progress or growth, whatever else they are, is premature. It lacks betterment’s maturity of and-yet grounded in obvious complexity—key, as that must be, to making and remaking the Anthropocene. Convergence and well-being are often understood as policy objectives (e.g., in the European Union), but for betterment, the expectation is one of diverging conditions and instances.

Annex. A precis of good enough and betterment

Good enough: The gloss on good enough most relevant for this guide is that of D.W. Winnicott, the psychotherapist, when describing the good-enough mother. The good-enough mother is not perfect, and that is a Very Good Thing. At baby’s birth and for a period thereafter, the good-enough mother is one who manages to be there when child needs mother. So available and in sync with the child’s needs is mother that the child at some point feels it created mother—indeed, created the perfect mother. Over time, the real mother—and this is where her “good enough” comes in—disillusions the child that “mother” is its very own creation.

For the purposes of this guide, Winnicott describes what the good-enough mother does as “management,” “provision” and “reliability:”

One cannot help becoming a parent-figure whenever one is doing anything professionally reliable. You [nurses] are nearly all, I expect engaged in some sort of professionally reliable thing, and in that limited area you behave much better than you do at home, and your clients depend on you and get to lean on you.

The reliability professionals discussed in Part’s I and II face this same dilemma of good-enough: How do they disabuse us, the consumers of water, electricity and other vital services, that our being better off is now more up to us than before and in ways we really haven’t yet appreciated? How to reinforce in us that the declines in services underway aren’t “declines” any more than is the reality-check that we did not create mother on our own?

Betterment. Earlier definitions of betterment figured in versions of the 18th century European Enlightenment. The term was used interchangeably with “improvement” or “progress,” though from time to time singled out as its own unit of analysis (most famously in political economist Adam Smith’s “the great purpose of human life which we call bettering our condition”).

The sheer variety of Enlightenment thinkers made it inevitable that not-knowing, difficulty and inexperience would be highlighted as well. Voltaire discusses not-knowing in the entry “On the Limits of the Human Mind” of his Philosophical Dictionary; David Hume, Scottish Enlightenment philosopher, grappled with the acknowledged idea of “not-knowing as the key to the contented life,” according to one commentator; in the view of another, Adam Smith expressed “an open skepticism about the possibility of knowing definitively what it is we are really doing;” while famously Immanuel Kant wrote about “the unknowability of things-in-themselves.” “Full recognition of the importance of uncertainty and the unknowable in analysing economic processes is an eighteenth-century heritage. . .which cannot be emphasized too often,” writes a third observer.

As for difficulty, historian Jonathan Israel sketches its central role in the Radical Enlightenment: “Theories of progress, however, contrary to what many have assumed, were usually tempered by a strong streak of pessimism, a sense of the dangers and challenges to which the human condition is subject. The notion, still widespread today, that Enlightenment thinkers nurtured a naive belief in man’s perfectibility seems to be a complete myth conjured up by early twentieth-century scholars unsympathetic to its claims. In reality, Enlightenment progress breathed a vivid awareness of the great difficulty of spreading toleration, curbing religious fanaticism, and otherwise ameliorating human organization, orderliness, and the general state of health was always impressively empirically based.”

Nor was the role of inexperience remote to versions of Enlightenment: “In the light of the triumph of Newtonian science, the men of the Enlightenment argued that experience and experiment, not a priori reason, were the keys to true knowledge,” writes historian, Roy Porter, where inexperience ironically has become a touchstone for criticizing French Enlighteners: “Above all, critics complained, in politics the philosophes lacked the quality they pretended to value most: experience.” Yet, the almost universal priority given to education by Enlightenment advocates across its highly differentiated spectrum reflected their acknowledgement that more education meant, acutely, more experience to manage or cope better ahead with their inexperience.


My special thanks 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.

This is a draft: Full bibliography, citations and footnotes to be provided.

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