Recasting “low probability, high consequence events”

It is easy to see why a magnitude 9.0 earthquake in the Cascadia subduction zone off of the Pacific Northwest coastline has been called a “low probability, high consequence event.” The estimated probabilities and estimated consequences reinforce this classification, notwithstanding caveats that the earthquake is “scientifically impossible to predict”.

My aim here is modest: to bring to the reader’s attention a very different way to think about Cascadia M9, one which to my knowledge has not been discussed in the scholarly or grey literatures.

The argument

Real-time experienced infrastructure operators and managers do worry–and for obvious reasons–about the effects of Cascadia M9 on their infrastructures, in this case, the interconnected backbone systems for water, electricity, telecoms and roads. These professionals, however, do not see their “what-if scenarios” for Cascadia M9 framed in terms of probabilities and consequences.

For them and in my terminology, thinking through Cascadia M9 has two foci: nonmeasurable uncertainties accompanied with disproportionate effects. No presumption is being made that “accompanied with” is causal or correlative. The point is that both nonmeasurability and disproportionality still convey important information for their infrastructure operations before, during and after the disaster. This information is especially significant when causal understanding is most obscure(d).

–I also claim that had we an analytic framework that took nonmeasurable uncertainties and disproportionate effects as its starting point, the policy and management options would differ not only from those of experts wedded to the low-probability-high-consequence typology. They would also differ from those in the emergency management profession who see themselves as first-responders in contrast to the infrastructure operators and field staff who in fact are the first-responders for catastrophic failure of backbone infrastructures.

Unique properties of Cascadia M9 and the experience base of infrastructure operators and managers

For those infrastructure operators and emergency managers we interviewed, the Cascadia M9 earthquake will be an unfolding catastrophe of unimaginable proportions, and not just for their infrastructures. Wider society and economy are at issue. What makes it unimaginable is that there can be no closure rule for “what-if” scenarios. For those knowledgeable about infrastructures, there’s always a new scenario that merits attention, and more so for the unimaginably bad.

More, the actualities in Cascadia M9 will be unpredictably localized with respect to the infrastructure systems and the impacts will be interconnected and amplified in unforeseen ways. “Unpredictably localized” entails having new nonmeasurable uncertainties compared to what the professionals already know about their infrastructures from past disruptions and worse. “Interconnected and amplified” means having unforeseen effects that are demonstrably disproportionate when compared to what they already know about their infrastructures during disruptions and worse.

Nonmeasurability of uncertainties and disproportionality of effects are what their experience tells the professionals to associate with Cascadia M9. These are infrastructure professionals who come to the M9 earthquake already knowledgeable about uncertainties and impacts, especially those that can or cannot be measured with effects inside or outside previous bandwidths and known proportions.

Informally, this means. . .

“Operating blind” with the loss of telemetry, cellphones and power is how one infrastructure operator described the experience in an ice storm. But it’s that “operating,” even then and now or ahead under worse circumstances, that the infrastructure’s real-time professionals can help us better understand. It’s their alertness to survey, notwithstanding. “I don’t know that we answer until we’re in the event in a lot of cases, not that it hasn’t been thought through,” echoed a city infrastructure manager for water with respect to Cascadia M9. So too “coming to those answers” is something we should want to know more about before inadvertently lapsing into current risk analysis.

“Coping with risk” is a highly misleading characterization of this behavior when an important part of that “coping” is proactive improvisations and where the unit and level of improvisation is not risk, as bundles of adjustable Pfs and Cfs, but a provisional match between then-and-there tasks and then-and-there resources called “emergency response.”

Proposed framework

It is important that the analytic framework be based in (1) how experienced infrastructure and emergency management operators see Cascadia M9, (2) import no slippery slope to conventionalized risk analysis and (3) demonstrate the centrality of information-rich nonmeasurable uncertainties and disproportionate effects.

(My research colleague, Paul Schulman, has played the key role in developing the four element below and is in no way responsible for the Implications drawn.)

We identified four elements that our previous work on large interconnected infrastructures indicated were critical to emergency management: (1) the different types of interconnectivity (sequential, mediated, reciprocal, more) between and among infrastructures involved in immediate response and initial recovery for the backbone infrastructures of electricity, water, telecoms and roads; (2) the points (thresholds, phases, transitions) at which the types of interconnectivity shift during infrastructure failure, response and initial recovery; (3) the importance in immediate response of jointly undertaken improvisations around real-time system control variables–think electricity frequency and voltage for electricity, water pressure for potable water supplies and firefighting, water flows for ports and vessel traffic–relied upon by more than one of the backbone infrastructures—all of which are in turn managed to (4) a performance standard of requisite variety (that is, effectiveness in immediate response and initial recovery are measured against how well real-time task demands and real-time resources are matched then-and-there, if only temporarily).

If this weren’t already an overly long blog entry, I would now describe and justify each element. But at this point what is more crucial is that the reader recognize how difficult these four elements, individually and together, make it to revert to anything like the language of Pf’s and Cf’s, Bayesian or otherwise. It is also important to recognize how nonmeasurability and disproportionality are consistent with and foregrounded by having multiple, shifting interconnectivities, improvisations and the never-before-seen by experienced operators and emergency managers.

So, I apologize by cutting to the quick, on the principle that the proof is in the taste of the pudding. What are some of the important implications to be drawn from this framework when used to think through response and initial recovery with respect to Cascadia M9? Three immediate ones will have be illustrative.

Implications

First, removing oneself from Cascadia M9 interconnectivities, shifts, and need for just-on-time improvisations must be an important option. This ranges from moving out of coastal Oregon and Washington State beforehand to having better evacuation strategies during and afterwards. It’s not clear to me if the states’ emergency preparedness plans and education programs present “getting-out-of-Dodge” as an option.

Second and for those staying in the coastal and western parts of the states, there is clear priority in developing and testing continuity of operations plans (public sector), business continuity plans (private sector) and what are variously called devolution plans and orders of succession (i.e., who will do what when the positions for “being in charge” are suddenly vacated). It is not clear to me how current modeling and tabletops exercises around Cascadia M9 incorporate prototyping and ground-truthing very different scenarios for public and private continuity and succession arrangements.

Third, the framework calls for majorly rethinking the role of “improvisations.” To characterize something like topping off a fuel tank for a back-up as a one-off incidental or side work is to miss entirely the point, namely: Improvisations, especially those involving more than one infrastructure during immediate response, cannot be isolated from the interconnectivities and shifts they occur within and give arise to, especially because (not: “even if”) they revolve around momentary matches in requisite variety.

A last point, for now

Some readers will have objected by this juncture: “Whoa! Moving to and living in another area involves new risks and with it weighing. . .And what about the poor or vulnerable who can’t move? . .”

But you are not balancing risks or probabilities or consequences when choosing to move out because of Cascadia M9, at least from the experienced-based perspective of the framework. Risks are not the driver; from the experience base described here, the drivers are the interconnectivities and important shifts in nonmeasurable uncertainties and disproportionate effects.

So to be clear: Am I saying there are no low-probability-high-consequence events? No. Am I saying that Cascadia M9 is not one of those? Yes.

Better to say, I think, that, when acting like an experienced infrastructure operator and moving from the western part of the state to the eastern part, I do so by virtue of not knowing what M9 analogue, if any, exists on the eastern side. Nor could I know beforehand the interconnectivities and shifts I’m moving into as well as I know the set for Cascadia M9 and relevant backbone infrastructures. By extension, the same logic (e.g., move/not move) applies to other unimaginably bad catastrophes equated to “low probability, high consequence events.”

That those we interviewed appear not to be moving out of western Oregon and Washington State tells us, I think, a great deal about the professional reluctance to move into (another set of) unstudied or unstudiable conditions.

(Please also see newer blogs, “A whole cycle approach to infrastructure risk and uncertainty” and “Ongoing disaster, resilience and governance: really?”)

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