1. The problem with calling for more research on resilience is the path dependency now long entrenched: The proliferation of new types of resilience exceeds the operationalization of the constructs already out there. More research should mean more operationalization, but there are no guarantees if the past is our guide.

In other words, resiliencies have been differentiated conceptually, but many of the conceptual constructs remain equally devoid of the details and specifics for relevant policy and management, case by case. One of the best things Paul Schulman and I did in our research on electricity infrastructures was to develop an empirical measure of when and how the transmission grid operators moved within, outside, and back into their real-time bandwidths for reliable service provision.

Operationalizing requires not thinking in terms of abstract nouns, like “resilience” or “adaptive capacity,” but thinking adverbially. To ask, “What does it mean here and now to act resiliently with respect to this rather than that,” has the great virtue of pressing for identification and specification of the practices that actually constitute “acting resiliently.” We can all talk about safety culture, but it is quite another matter to identify and differentiate the specific practices of doing this resiliently rather than that in real time.

2. “Building in resilience” can have the same kind of abstractness associated with “designing leadership:” far too easy to recommend rather than operationalize. But even if planners knew the adverbial specifications of “building in resilience” for emergency management, none of this would lessen the priority role of improvisation and ingenuity by professionals in emergency response.

There is no planner’s workaround for improvisation. This means the question, “When is ‘resilient-enough’ enough?,” is not answerable by planners on their own.

3. Resilience, at the conceptual level, is said to be optimizing the ability to absorb or rebound from shocks, while minimizing the need to anticipate these shocks ahead of time. Anticipation, in contrast conceptually, is to optimize the ability to plan ahead and deal with shocks before they happen, while minimizing having to cope with shocks when they do occur. Consider the resulting Table 1:

System planners would like managers to be both optimally anticipatory and resilient at the same time—indeed that managers maximize their “readiness” for whatever arises, whenever. These all-embracing demands of planners and project designers can, however, reduce the managers’ much-needed capacity to balance anticipation and resilience case by case. Indeed, to do the latter requires respect for the granularities of resiliencies, not their abstractions.

4. Readers are familiar with advocacy pieces that call for more adaptive, collaborative, comprehensive, integrated, holistic, and resilient approaches to emergencies, without however providing the details for that implementation, here and now rather than then and there.

While it is too easy to make such calls, notice the positive practical implication: Those who do know (some of) the details and practices have much to say about the respective abstractions called variously, “resilience”.

We know that real-time operators and managers of critical infrastructures coordinate, adapt, improvise, and redesign all the time in the face of system surprises and shocks, big and small. They also practice different types of resilience (i.e., adjusting to surprises in normal operations differs from restoring infrastructure operations back to normal after a systemwide disruption). When it comes “comprehensive and holistic,” these professionals seek to maintain team situational awareness and a common operating picture of the system, again in real time. (The latter aren’t what most planners and designers consider “comprehensive and holistic”!)

Two inter-related implications follow. First, these operators and managers are professionals, whether officially certified or not. Second, because they are professionals, their operationalized definitions of adaptation, resilience and coordination matter for and in practice. There is no reason to believe these operational definitions have been sufficiently canvassed to date by scholars of resilience, let alone macro-planners and designers.

So what? in the climate emergency

So what? in capitalism

So what? in predicting the future

So what? in leadership

——————-

So what? in the climate emergency

I

This week I attended an informative conference on sea-level rise, storm surges and flooding in the greater San Francisco Bay Area, now and projected into the near decades. I was told:

• that Bay Area would need some 477 million cubic yards of sediment–the vast majority of which can’t be sourced locally–to restore area wetlands and mudflats;
• It would require an estimated US$110 billion dollars locally to adapt to higher sea levels by 2050, this being based on existing plans in place or used as placeholders for entities that have yet to plan; and
• To expect much more sea level rise locally because of the newly accelerated melting of the ice cap melting in Antarctica and Greenland.

Millions of cubic yards equivalent to over 420 Salesforce Tower high-rises? Some $110 billion which has no possibility whatsoever of being funded, locally let alone regionally? How are these and the other unprecedented high requirements to be met?

II

But there is a major problem with these estimates of losses (economic, physical, lives, and more) incurred if we don’t take action now, right now. It’s been my experience that none of these estimated losses take into account the other losses prevented from occurring by infrastructure operators and emergency managers who avoid systemwide and regional system failures from happening that would have happened had they not intervened beforehand, sometimes at the last moment.

So what?

Why are these uncalculated billions and billions of saved dollars important when it comes to responding to sea level rise, increased storm surges, more inland flooding, rising groundwater levels and other sequelae?

Because it from this pool of real-time talent and skills and practices that society will be drawing for operationally redesigning the inevitable shortfalls in new technologies, macro-plans and regulations for climate restoration and recovery.

——————-

So what? in capitalism

Ending capitalism isn’t just hard to realize; it’s hard to theorize and operationalize. To wit: “Under capitalism” means that even with always-late capitalism, we have. . .

laissez-faire capitalism, monopoly capitalism, oligarchic capitalism, state-guided capitalism, party-state capitalism, corporate capitalism, corporate-consumerist capitalism, digital capitalism, financialized capitalism, political capitalism, social (democratic) capitalism, neoliberal capitalism, crony capitalism, wellness capitalism, petty capitalism, platform capitalism, surveillance capitalism, infrastructural capitalism, welfare capitalism, authoritarian capitalism, imperialistic capitalism, turbo-capitalism, post-IP capitalism, green (also red and brown) capitalism, climate capitalism, extractive capitalism, libidinal capitalism, clickbait capitalism, emotional (affective) capitalism, tech capitalism, American capitalism, British capitalism, European capitalism, Western capitalism, transnational capitalism, global capitalism, agrarian capitalism, residential capitalism, disaster capitalism, rentier capitalism, industrial capitalism, post-industrial capitalism, fossil capitalism, petro-capitalism, settler-colonial capitalism, supply chain capitalism, cognitive capitalism, asset manager capitalism, information (also data) capitalism, cyber-capitalism, racial capitalism, necro-capitalism, bio-capitalism, penny capitalism, war capitalism, crisis capitalism, managerial capitalism, stakeholder capitalism, techno(scientific)-capitalism, pandemic capitalism, caring capitalism, zombie capitalism. . .

Oh hell, let’s stop there. In a deep irony, much of this looks like classic product differentiation in competitive markets. In this case: by careerists seeking to (re)brand their lines of inquiry for a competitive advantage in professions that act more and more like markets anyway.

So what?

Now, of course, it’s methodologically positive to be able to differentiate types and varieties of capitalism, so as to identify patterns and practices (if any) across the diversity of cases. But how is the latter identification to be achieved with respect to a list without number? What then does being anti-“capitalist” actually mean these days for policy and management?

——————-

So what? in predicting the future

So what if we’re lousy in predicting the future? We are so used to the idea that predicting the future is more or less about accuracy that we forget how murky and unclear the present is. To paraphrase Turgot, the French Enlightenment philosopher and statesman, we have enough trouble predicting the present, let alone the future. Because the present is not one-way only by way of interpretation, why expect anything less for the future?

Again: So what?

This means that the microeconomic concepts of opportunity costs, tradeoffs and priorities, along with price as a coordinating mechanism make sense–if they make sense–only now or in the very short term, when the resource to be allocated and alternatives forgone are their clearest. Without opportunity costs, notions of stable trade-offs and prices go out the window.

——————-

So what? in leadership

Take even a cursory glance at the track record of advisers to their leaders:

• Plato and Dionysius II;
• Aristotle and Alexander the Great;
• Seneca and Nero;
• Ibn Rushd (Averroes) and Caliph Abu Yaqub Yusuf;
• Petrarch and Emperor Charles IV;
• Montaigne and Henri IV;
• Descartes and Sweden’s Queen Christina;
• Leibnitz and the Dukes of Hanover;
• Voltaire and Frederick the Great;
• Diderot and Catherine the Great; and
• In case you want to add to the list, Adam Smith and the Duke of Buccleuch or Goethe and Prince Carl August, and so on through the centuries. . .
• Or if you really want to cringe, just consider André Gide recommending against publishing Marcel Proust, Edward Garnett against publishing James Joyce, and T.S. Eliot against publishing George Orwell. . . .

I mean, get real: If these guys didn’t advise effectively, who the hell are we to think we can do better for the leaders of the day? (And, puhleeese, don’t throw up Kissinger and Nixon as the working template!)

So what?

Two things. It’s hard to imagine two words scarier in the English language than “designing leadership.” Second, we should take to heart the extensions of, “It was beyond our mental capabilities to predict Bob Dylan winning the Nobel in 2016.”

I

The typical divide across pre-disaster/disaster/post-disaster becomes more complicated when you talk to practicing emergency managers. They can go into great deal about efforts to “prepare for,” “mitigate,” and “prevent” situations even when already in immediate response and restoration, and not just beforehand.

It would however be a mistake, I think, to see preparation, mitigation and prevention as a continuous set of practices, albeit punctuated from time to time.

To telegraph ahead, what changes are different configurations of socio-technical interconnections around which ongoing prevention, preparedness and mitigation efforts are undertaken—from now into and across immediate response and initial restoration of services.

II

To see what this means for resilience, start this way.

Some infrastructure operators and emergency managers we interviewed say they are best in response and restoration when following plans; others say they are at their best when surprised by the unexpected. This means operations people may look like cowboys to the engineer department because both cognitively understand the same system differently: “I don’t think you respond to 92 breaks in 13 days without having the ability to adapt on the fly,” said a city’s water distribution manager.

But this may be less a matter of different professional orientations and more about orientations with respect to different “scales of operation,” even within the same city.

For engineers, seismically retrofitting a bridge represents efforts to manage ahead latent interconnectivity so that it does not become manifest during or after an earthquake, e.g., the bridge holds and traffic is not disrupted there. For operations people, even if the seismically retrofitted bridge does fail in the earthquake and traffic disrupted, improvisations are still possible, both by the city departments involved and by commuters who individually or collectively organize alternatives. The respective interconnectivities, before and after, of course look very different.

Improvising after failure may seem like weak beer compared to the promise of better avoiding failure in the first place, but not foregrounding the necessity of improvisations (and improvisational skills) leads to confusion about “building in resilience” and its role in emergency management.

All the money and political will beforehand won’t get rid of the key role of improvisation in emergency management. There is no planner’s workaround for improvisation. This means the question, “When is ‘resilient-enough’ enough?,” is not answerable by planners.

Climate doomers are to the climate emergency what heavy metal is to apocalyptic war: a kind of niche gardening.

“Culture eats policy for lunch every day.”

Ignorance leaves traces via surprise or shock, which means trace is never without place.

If pictured as a Renaissance ceiling fresco, risk-seeking innovators would be little putti wheeling around St Market, upwards into a cerulean sky.

One reason for policy messes is that those who should be turning in their graves can’t.

Inequality, like congeries, is a plural noun.

Sheets of blank paper held up by protesters–now that’s no empty signifier! [Alternatively: “It’s damned hard,” as Wittgenstein reportedly said, “to write things that make blank sheets better!”]

The function of policy and management messes is to frustrate the storyline of beginning, middle and end–which is a very good mess to be in at times.

The “r” in “water” is for reliability.

They read less as crisis scenarios in need of details than grudges passed off as threats.

It’s because we demand complex organizations to be rational (formal) that they have had to become natural (informal).

So many new policy statements are like staging a house for sale. If bought, the furniture actually used inside differs considerably.

Somewhere between platform governance and content moderation is curation of multiple websites granular enough for different policies and their management.

There is no little irony in a privatized market approach to critical service provision, based in individual self-interest, and a technology-based approach that promises to free us from all manner of selfishness when it comes to that provision.

Consider the economist’s “the opportunities are attractive, if technological and regulatory challenges are overcome” and the engineer’s “the opportunities are attractive, if economic and regulatory challenges are overcome”: In either case, scapegoating regulation keeps each discipline from fragmenting further.

It’s the crudeness: As if more the sheer numbers of people were even a credible unit of analysis, full stop, for policy or management. As if complex could be abbreviated simply.

Not a scintilla of recognition:

• that perceptions and management of policies differ, at least, by a person’s age, education, income, gender, and ethnicity;
• that not-knowing, difficulty and inexperience with respect to population numbers and to perceptions, at the very least, set disciplines, fields and ways of being apart from each other;
• that what stops further polarization of disciplines, fields and ways of being are not fewer numbers but the not-knowing, difficulty, and inexperience; and
• that when the numbers do polarize, fear becomes a solipsism, believing itself to be an anti-politics machine.

Default to numbers on their own is, in other words, an Olympian capacity to deoxygenate all living matter.

I

That people act in an imitative fashion under conditions of high economic uncertainty is not news: Panic selling, spiraling inflation, overheated art markets, and speculative frenzies (I sell when you sell, buy when you buy) are some of the many instances of imitative economic behavior.[1] 

What’s bothered me, though, is the relative lack of reference in the economic literature to René Girard’s theory of mimetic contagion (mimetic desire, in his terms). Girard’s framework has major implications not identified by economists writing on market contagion and associated crises.

II

Brief description of a Girardian economics

From a Girardian perspective, financial and economic uncertainty begets ever more uncertainty, as more and more people imitate each other in a desperate rush to figure out what to do. At some point, classes of people are arbitrarily identified (scapegoated in Girard’s terms) as the cause of the crisis, widespread violence ensues against or because of them, and new financial and economic institutions emerge from the hostile, violent conditions.

Most economic contagion models do not go that far in predicting violence (to be clear, predicting does not mean advocating).[2]

Contagion modelers argue that the way to break the cycle of imitation is through more accurate information. Girardians will have none of that. They insist the underlying and overwhelming problem is pervasive uncertainty for which there is no recourse to “certainty” to solve. Appeals to “market fundamentals” or “getting back to normal” stabilize temporarily, and that is at best only. Such appeals do not and cannot resolve the baseline widespread uncertainty that corrodes each and every stabilization effort.

In a Girardian economics, the more uncertain things are, the more wealth we desire to buffer against that uncertainty; but the more wealth we have, the more desire we have for even more wealth. The specification of wealth itself becomes increasingly problematic as uncertainty persists. Once wealth “ceases to be identified with the instituted money, [economic agents] no longer know behind which mask it is hiding.  Stocks, real estate, gold, foreign currencies, primary commodities, etc. attract the anxious attention of individuals looking for likely refuges from the ‘terrible oscillations of chance’,” the economist, André Orléan, writes.

This leads to what Girard calls a crisis of undifferentiation. Uncertainty becomes everywhere intensified; economic behavior grows more and more uniform; and ever more wealth becomes desired as “what is wealth?” becomes increasingly difficult to answer. Markets undergoing crises of undifferentiation—epidemics of contagion where everyone ends up imitating each other—are instances where we do not know enough to distinguish, in econo-speak, satisficing from maximizing or the second-best from the Pareto-optimal, and where no one is clearly right but where everyone hopes they are.

Girardian features of the 2008 financial crisis

This sense of free-fall and groundlessness is neatly captured in the comments of bankers and investors just before and during the 2008 collapse of Lehman Brothers. “It feels as if we are 15 minutes away from the end of the world,” the head of equities at a large U.K. bank told the Financial Times about the lead up to the first major U.S. bailout.

“The market has changed more in the past 10 days than it had in the previous 70 years,” reports a senior executive at a European investment bank in 2008. “We have no idea of the details of our derivative exposures and neither do you,” conceded a senior Lehman Brothers official at a meeting of bankers and regulators just before it collapsed. “The crisis continues because nobody knows what anything is worth,” said one informed observer. The chair of Morgan Stanley Asia concluded, “We have gone to the edge of an abyss that few thought was ever possible”. I can find no reports of financial experts appealing to “underlying” market fundamentals during these weeks.

For Girardians, people under these conditions–these crises of undifferentiation–respond by scapegoating. Scapegoating provides the certainty to move on. Reports from and about the last quarter of 2008, with the collapse of Lehman Brothers, the bailout of Freddie Mac and Fannie Mae, and the further bailouts of AIG and Citigroup, were replete with terms such as “panic,” “herd instinct,” “mob mentality,” “mob rule,” “witch hunting,” “finger-pointing,” “lynching,” and “show trials” along with the ubiquitous referencing of “scapegoats” and “scapegoating” (all terms from contemporaneous reports in the Financial Times).

Many commentators, of course, believed they were in fact correct in their blaming this one or that one for the crisis. Girardians argue, in contrast, that the choice of scapegoat is completely arbitrary, where pervasive uncertainty drives economic behavior. Some of this arbitrariness was witnessed in the belief that if no one is to blame, then everyone is. We were told “there is enough blame to go around for every one” and “we are all to blame for the meltdown.”

In heated financial markets where everyone is buying or selling at time t+1 because, well, most everyone was buying or selling at time t, there is no way to validate that selling save by stating it is what everyone else was and is doing. This point was famously made by Chuck Prince, former head of Citigroup, when he told the Financial Times in mid-2007, “When the music stops, in terms of liquidity, things will be complicated. But as long as the music is playing, you’ve got to get up and dance. We’re still dancing.”

But where’s the blood?

Its focus on an ensuing violence, however, is what sets a Girardian economics apart from other contagion models. A full-blown Girardian economics, at least as I understand it, would hold that imitative behavior goes beyond the scapegoating. It turns into mob behavior, not as a reporter’s hyperbole but in actuality. People are killed, and it is only after widespread violence that people respond in revulsion to their behavior by forging social and economic conventions so that such violence “never happen again.” In this view, new economic and financial institutions arise only after panic and mob-like behavior and the post-hoc rationalizations for what all the preceding “really” meant.

We certainly heard calls from politicians and regulators alike for “never again,” when it came to the 2008 financial crisis. So too, a manager or two committed suicide or disappeared from the scene. But it is an odd sort of crisis when those harmed on such an unprecedented scale did not take screaming to the streets. In 2008, we witnessed food riots over crop prices but no real violence over this massive wealth destruction. Which prompts the question: “Where’s the blood?, as René Girard asked me when I presented my version of a Girardian economics at his Stanford seminar.

I suppose some of it is there if we look for it. Already well documented, murder and suicides and violence do go up during a severe economic downturn like the one to which this financial crisis led. This, however, scarcely qualifies in Girardian economics as mob behavior essential for the rise of new social convention and institutions governing finance and economics.

So what happened?

In July 2009, former Treasury Secretary Henry Paulson testified before Congress on his involvement in the financial crisis. He admitted he had been deeply concerned about frightening the public if he expressed his real fears about the financial system unraveling: “[W]hen a financial system breaks down, the kinds of numbers that we were looking at in terms of unemployment was [sic] much greater than the numbers we’re looking at now. People in the streets, and of course, around the world—it was very significant and I remember talking about it…”.

But people did not take to the streets. Why?

Girardians, as I understand them, would resist two popular “answers:” (1) government interventions worked, and/or markets went back to fundamentals; and (2) it is too early to say how things are working out. As such argued, Girardians would have expected considerable violence during and after events of September/October 2008, and there is no chance, as I understand them, that such reforms to the financial system as there were would ever make things more “certain” in the absence scapegoating and ensuing violence.

My answer

There are at least four ways in which a crisis of economic undifferentiation could be delayed, albeit not averted, when comes to market contagion. More, if I understand Girardians, these four ways are the value added to contagion models of the financial crisis already proposed by mainstream economists:

If you can’t reduce pervasive uncertainty, the next best alternative is to impede the resulting rivalry (“increase the costs of rivalry”);

If you can’t reduce the rivalry, the next best alternative is to impede the associated imitative behavior (“increase the costs of imitation”);

If you can’t reduce the rivalry or imitation, the next best alternative is to foster and prolong differentiation (“decrease the costs of differentiation”); and

Lastly, if you cannot do any of the above, the alternative is to slow down or wait out the crisis of undifferentiation (“increase the costs of undifferentiation”).

These actions are, I believe, what have been happening by way of the financial and economic reforms undertaken since 2008. Their effect has been to delay the consequences of the financial crisis by sidelining the scapegoating. Let’s examine each in more detail:

Increase the costs of rivalry.

In the Girardian framework, markets are mechanisms to increase the transaction costs associated with rivalry, not decrease them, as conventional economic theory would have it.

Markets are what keep us from killing each other for the goods and services we desire. They transform us into price takers rather than commodity thieves. What happened in the lead up to the 2008 financial crisis was just such increased thievery (e.g., insider trading and predatory lending). Many existing and proposed reforms—most notably, increasing capital adequacy reserves in banks and lending institutions—have been intended to make the excesses of rivalry too costly to undertake.

But increasing the costs to rivalry poses a dilemma from a Girardian perspective. To increase their costs may lessen that rivalry, but the higher costs serve as an incentive for increasing the wealth needed to cover (buffer against) the now-higher costs associated with rivalry. For Girardians, it is no surprise that firms, such as Goldman Sachs and JPMorgan Chase, were driven to return to wealth-making faster than would have been expected given the economic conditions and liquidity shortages said to exist at the time.

Increase the costs of imitation.

The principal feature of the lead-up to the 2008 financial crisis was that costs of imitation were too low. Behavior, as many pointed out, became positively correlated, when finance theory insisted such behavior should have been uncorrelated through risk dispersion.

Instead of diversification and risk spreading, hedge funds and others ended up acting in very similar ways. Either “[t]oo many funds bought the same assets” or the “problem was that, while these assets are heterogeneous, the owners were not. In tough times they behaved the same way….Diversification was therefore fake”. “Far from promoting ‘dispersion’ or ‘diversification’ [financial] innovation has ended up producing concentrations of risk, plagued with deadly correlations,” according to a Financial Times’ correspondent at the time.

Calls for “increased transparency” are routinely given as the solution to this problem. Risk cannot be concealed or obscured if financial processes are transparent, so this argument runs. From a Girardian perspective, such calls are self-defeating. Greater transparency would reveal the financial system is transparently complex and in many ways visibly beyond human comprehension when it comes to measurable risk and unmeasurable uncertainty. At worst, everyone sees the system for what it is, a house of cards impossible to shrink through “better risk management” or shrink-wrap with “better macro-prudential regulation.”

Either way, calls for greater transparency would lead people to becoming even more rivalrous as they hunt for ever greater wealth to protect or buffer themselves.

Decrease the costs of differentiation.

Now things get really interesting. You saw everywhere in the 2008 financial crisis the insistence of major participants that each differed from the others and that they were not—repeat, not—all alike.

Hedge funds insisted they did not start the financial crisis but that banks and investment houses did; the latter institutions insisted they were not all the same, some were better (or accused of being worse) in managing securitized assets; not all securitized assets were the same—that is, all toxic; more, not all toxic assets were equally valueless; still others argued that it depended on the valuation procedure used and few agreed which was the better one; no over-arching agreement, moreover, because the regulators themselves did not agree….; and so on.

Against a Girardian background, this sustained insistence on differentiation, even as finance and banking were in the midst of uncertainty, is especially important to note. Circumstances remained, at least in the minds of the finance sector, differentiated in major forms before and through the crisis. Very different social conventions emerged with respect to financial transactions, and the conventions evolved and innovated at that time as they diffused through institutions and among their participants. While accusations of “You’re all the same!” reached near fever-pitch, banking and finance services were still far from being homogenous and uniform, even during the crisis and the Great Recession that followed.

In other words, the blame game remained cheap throughout the 2008 crisis: The costs of differentiation were lower than one would have expected in a full-blown crisis of undifferentiation. I return to this point in a moment.

Increase the costs of undifferentiation.

A last strategy is to wait out the financial collapse in the hope that the longer people hold out before the crisis of undifferentiation becomes total, the more likely undifferentiation will not be total nor the contagion completed in full-blown scapegoating. One way to make undifferentiation “cost more” is to fuel the rumor mill about the who, why, how, when and where of the financial crisis, since it takes time to settle a rumor. (Small beer, but beer nonetheless.)

Since 2008, we have had an incoming tide of books and publications that keep all manner of whodunit suspicions and fevers alive. Rather than narrowing down identification of those who are “really” to blame, we have a surfeit of candidates said to have caused or contributed. In fact so many that some take the 2008 financial crisis to have been overdetermined. Instead of knowing who is to blame, we are encouraged to conclude, “With all that was going on, it would have been a miracle if the financial crisis didn’t happen!” Error here has many fathers when reliability is orphaned.

III

In short, scapegoating has become difficult to complete during and since 2008, thereby diffusing the prospect of violence and the rise of new financial institutions: . . . so far, Girardians underline. Yes, scapegoating has begun, some violence has been witnessed, but there has yet to be polarization around one scapegoat or defined set of them. Or from the other direction, what polarized agreement that has occurred has been more around phenomena—notably, rising inequality—than on specific groups or classes of agents.

Yet even if the financial crisis were not the one predicted by a purely Girardian economics—how could it be a crisis of undifferentiation and scapegoating without the violence?—it is remarkable how well the four types of interventions just described fit the course of events as we know them today.

As such, arguably the most telling lesson learned so far is that it can’t be assumed widespread uncertainty is pervasive uncertainty. There are extreme events where widespread uncertainty comes to us as separable uncertainties—more differentiated and differentiable than might first be supposed. Rather than being the lack of information, some uncertainties are very informative.

---

Endnotes

[1] Conlisk (1980) wrote about the widespread importance of imitation in economic behavior. Topol (1991) focused explicitly on mimetic contagion in investment behavior. Scharfstein and Stein (1990) and Banerjee (1992, 1993) modeled herd behavior among investors. The critical-mass (“tipping”) models of Schelling (1978) and Akerlof (1984), as well as the “informational cascades” model of fads and cultural change developed by Bikhchandani, Hirshleifer and Welch (1992), captured the notion that, under uncertainty, economic agents end up copying each other’s behavior. Most famously, Nobel Laureate in Economic Sciences, Robert Shiller (e.g., Shiller and Pound 1989; Shiller 1989, 2006) writes about and focus on contagion models in investment and the strategic role of imitation among investors. He argues, for example, that the subprime mortgage crisis and the 2008 financial crisis that followed had a great deal to do with “the contagion of market psychology” that led to bubbles under the boom conditions of the turn of the century (Shiller 2008). More recently, Shiller (2019) has focused on the role of narratives in the spread of and response to market contagion and crises.

[2] Not all economists who rely on the Girardian framework focus on violence as the instigator of new economic arrangements. Scholars such as Jean-Pierre Dupuy, Mark Anspach, Paul Dumouchel, and André Orléan, among  others, have applied aspects of Girard’s contagion model to economics and related topics. In my view, the most notable application is that of economist, André Orléan, in his The Empire of Value: A New Foundation for Economics (translated by M.B. DeBevoise, 2014, The MIT Press: Cambridge, MA.). Violence is not a key feature of his analysis of money and the 2008 financial crisis in that book. (See also Orléan 1988, 1989, 1992a,b, 1998.)

References

Akerlof, G., 1984. A theory of social custom, of which unemployment may be one consequence. In An Economic Theorist’s Book of Tales. Cambridge University Press, Cambridge.

Banerjee, A., 1992. A simple model of herd behavior. Quarterly Journal of Economics 107, 797-817.

————— 1993. The economics of rumours. Review of Economic Studies 60, 309-327

Bikhchandani, S., D. Hirshleifer and I. Welch, 1992. A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy 100, 992-1026.

Conlisk, J., 1980. Costly optimizers versus cheap imitators. Journal of Economic Behavior and Organization 1, 275-293.

Orléan, A., 1988. Money and mimetic speculation. In P. Dumouchel, editor. Violence and Truth. Stanford University Press. Stanford, CA.

————, 1989. Mimetic contagion and speculative bubbles. Theory and Decision 27, 63-92.

————, 1992a. The origin of money. In F. Varela and J-P Dupuy, eds. Understanding Origins. Kluwer Academic Publishers. Netherlands.

———— (co-authored with Robert Boyer), 1992b. How do conventions evolve? Journal of Evolutionary Economics 2, 165-177.

———–, 1998. Informational influences and the ambivalence of imitation. In: J. Lesourne and A. Orléan (Eds.) Advances in Self-Organization and Evolutionary Economics. Economica: London.

Roe, E., 1996. Sustainable development and Girardian Economics. Ecological Economics 16, 87-93. The article is the principal source for this blog entry, though material from the original has been updated substantially.

Scharfstein, D. and J. Stein, 1990. Herd behavior and investment. The American Economic Review 80, 465-479.

Schelling, T., 1978. Thermostats, lemons, and other families of models. In Micromotives and Macrobehavior. W.W. Norton and Company, NY.

Shiller. R., 1989. Stock prices and social dynamics. Fashions, fads, and bubbles in financial markets. In Market Volatility. The MIT Press, Cambridge, MA

————, 2006. Irrational Exuberance. 2^nd Edition, Paperback, Broadway Business.

————, 2008. The Subprime Solution:  Today’s Global Financial Crisis Happened, and What to Do about It. Princeton University Press: Princeton, NJ.

————, 2019. Narrative Economics: How Stories Go Viral & Drive Major Economic Events. Princeton University Press: Princeton, NJ.

Shiller, R. and J. Pound, 1989. Survey evidence on diffusion of interest and information among investors. Journal of Economic Behavior and Organization 1,: 47-66.

Topol, R., 1991. Bubbles and volatility of stock prices: Effect of mimetic contagion. The Economic Journal 101, 786-800.

I

It turns out that what the Delphic oracle said about Socrates varies by the account given for how Socrates defended himself at his trial for impiety and corrupting the young.

Plato’s famous version has Socrates’ recounting that the oracle pronounced no human being wiser than Socrates. Socrates then goes on to ask, Aren’t there others in fact wiser? In the process, he seeks to underscore his knowledge of his own ignorance.

In contrast, Xenophon (a contemporary of Socrates and Plato) has Socrates saying the Delphic oracle pronounced no one freer, more just, or more prudent than Socrates. Socrates then proceeds by asking and answering nine questions which are meant to lead to that conclusion.

II

For my part, I like the updated composite version: wise enough to disagree, free enough to agree.

Socrates being wise is entailed in Xenophon’s version, whereas being wise in Plato’s version also means knowing you’re ignorant of things, including: prudently put, just how free am I?

III

Not quite, then, the ethics of “Do unto others as you would do unto them.”

Closer instead to: “I am not so arrogant, as to commend mine owne gifts, neither so degenerate, as to beg your toleration” (Robert Jones, 1611).

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Source: P.A. Vander Waerdt (1993). “Socratic Justice and Self-Sufficiency. The Story of the Delphic Oracle in Xenophon’s Apology of Socrates”. In: Oxford Studies in Ancient Philosophy, 11. 1-48.

When I and others call for better recognition and accommodation of complexity, we mean the complex as well as the uncertain, unfinished and conflicted must be contextualized if we are to analyze and to manage case-by-granular case.

When I and others say we need more findings that can be replicated across a range of cases, we are calling for identification not only of emerging better practices across cases and modifiable in light of new cases, but also of greater equifinality: finding multiple but different pathways to achieve similar objectives, given case diversity.

What I and others mean by calling for greater collaboration is not more teamwork or working with more and different stakeholders, but that they “bring the system into the room” for purposes of making the services in question reliable and safe.

When I and others call for more system integration, we mean the need to recouple the decoupled real-time activities in ways that better mimic, but can never reproduce, the coupled nature of the wider system environment.

When I and others call for more flexibility, we mean the need for greater maneuverability across different performance modes in the face of changing system volatility and options to respond to those changes.

Where we need more experimentation, we do not mean a trial-and-error learning where the next systemwide error ends up being the last systemwide trial destroying survival.

Where others talk about risks in a system’s hazardous components, we point to different systemwide reliability standards and only then, to the different risks and uncertainties that follow from the different standards.

I

“Healthcare” is considered to be one of the nation’s critical infrastructures sectors, according to the Department of Homeland Security.

Infrastructures, however, vary considerably in their mandates to provide their services safely and continuously. The energy infrastructure differs depending on whether it is for electricity or natural gas or hazardous liquids, while the latter three differ from large-scale water supplies (I’ve studied all four).

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 operation centers.

Which provokes a useful question: What would healthcare look like if it were managed more like other infrastructures that have centralized control rooms and systems? Might the high reliability of infrastructural elements within the healthcare sector be a major way to better ensure patient safety?

II

Three points are offered by way of answer:

(1) High reliability theory and practice suggest that the manufacture of standard vaccines and compounds can be made reliable and safe, at least up to the point of the interface with patients. Failure in those back-end processes is exceptional—as in the 2012 fungal meningitis contamination at the New England Compounding Center—precisely because failure is so preventable.

Yet, under routine healthcare, it is the sharp-end of patient interface with those treatments that receives priority attention. The risk here is this focus dilutes attention, encourages complacency and divert management from the strong-end of healthcare, namely, the prevention of key production and distribution errors in healthcare without which patient safety doesn’t stand a chance.

(2) If healthcare were an infrastructure more like those with centralized control centers, the importance of societal dread in driving reliable service provision would be far more visible and dramatic.

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 widespread public dread we find undergirding the reliability demanded of other infrastructures, such as nuclear power and commercial aviation.

Clearly, 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 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?

One answer: Hospitals, if not managed reliably kill you. “Going to the hospital always means risking your life” is another way to put the dread. Once societal dread over medical error is high, expect to see medical errors of all sorts to be prevented more effectively.

(3) One response to preceding is to resist their implications and insist on treating healthcare from the doctor’s or specialist’s perspective as a craft or crafts surrounded by advanced infrastructure elements (think technologies and information systems).

Yes, mistakes are made, even horrible ones, but where would healthcare be without first and foremost the patients’ trust in doctors, staff and their expertise? (I’ll leave aside the fact that control room operators in major infrastructures are themselves craft professionals responsible for far more lives in real time than hospital and clinic staff!)

But in the high reliability management research with which I am familiar, distrust is as core as trust. One reason control room and front-line operators are reliable (that is, safe and continuous providers of services) is that they actively distrust the future will be stable or reliable in the absence of the system’s vigilant real-time management. Their wraparound support units—the experts in system engineering, economics, and modeling—may be telling them one thing and their unique real-time experience quite another.

From an infrastructure perspective, it is not surprising then that a US healthcare system that encourages each patient to be his or her own reliability manager entails a basic shift from the healthcare professionals as the primary wraparound for the patient to the patient’s immediate family, friends, and internet searches as primary support. More, the primary role of the latter is now to combat any complacency in patient treatment by healthcare professionals (complacency being a big risk in routine control room operations). Such tensions, including distrust of what are now seen as complacent medical professionals, are understandable from an infrastructure perspective and not ones to be smoothed over or otherwise “solved”.

III

So what?

Limitations of our analogy are obvious. The patient does not share the same situational awareness that his or her team/network of healthcare professionals may have about the him or her, and even then, the healthcare professionals may not have team situational awareness like that we have observed in water or electricity control rooms.

More, the electricity or water user is his or her own reliability manager typically only during severe water or energy shortages, when their participation and collective mindfulness in rationing is critical. Is a reliable patient necessary for a reliable healthcare system during high demand times (and again not just in a public health emergency) in the same way as energy-conscious or water-conserving consumers need to be during their high use times? Presumably, the movement to bring real-time monitoring healthcare technology into the patient’s habitation is increasingly part of the reliability calculus.

Yet 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.

Note: I thank Paul Schulman for many discussions, suggestions, and points; the provocations that remain are mine alone.

When asked why they are studying [central bank digital currencies], responses from central banks do not focus on a single reason. The safety or robustness of the payment system, financial stability, efficiency of payments, implementation of monetary policy and the goal of greater inclusivity in accessing payment systems by lower income populations—all seem to be considered at least somewhat important. Lacking a single vision of what they want to accomplish, central bankers seem to be afflicted by a generalized sense of unease. Though scenarios can be only vaguely delineated, shifting sands in the payments and monetary landscape suggest to central banks that, if they do not provide a digital currency, they could find themselves isolated and weakened in unfamiliar ways. Having sufficient control over the retail payments system might, they suppose, prove to be essential for ensuring the stability and efficiency of the monetary and payments system.

From a quote in: Cesaratto, S. and E. Febrero (2022). Private and Central Bank Digital Currencies: a storm in a teacup? A Post-Keynesian appraisal. DT 2022/1, Working Papers, Department of Economics and Finance, Universidad de Castilla – La Mancha, Spain (accessed online at https://www.uclm.es/es/departamentos/daef/-/media/Files/A05-Investigacion-departamentos/daef/documentos_trabajo/2022-01-DT-DAEF.ashx?la=es)