I
My proposition is that these three statements are true–and majorly so–as far as they go: 1. The most difficult part of undertaking a conventional policy analysis is predicting the consequences of business as usual and our proposed alternatives; 2. More generally, the mess we are in today–and not just as policy analysts–is our inability to predict the future(a); and 3. When it comes to predicting, we often seem to lack the imagination to connect the policy and management “dots” right in front of us.
It is easy enough to quibble with the statements. My point here, however, is that even if the statements were true, they’d still need to be pushed further and the way to do that is to recast conventionalized understandings of prediction and imagination. Why rethink? Because in doing so, really-existing problems of prediction and imagination can become more tractable to policy and management.
No semantic magic is needed. To telegraph ahead, the issue is to find levels of granularity via recast issues (no guarantees these levels are there) that become more actionable in comparison to current definitions.
II
Let’s start with the following example by way of illustrating the last point:
Once an artificial island, the ancient site of Soline was discovered in 2021 by archaeologist Mate Parica of the University of Zadar in Croatia while he was analyzing satellite images of the water area around Korčula [Island].
After spotting something he thought might be human-made on the ocean floor, Parica and a colleague dove to investigate.
At a depth of 4 to 5 meters (13 to 16 feet) in the Mediterranean’s Adriatic Sea, they found stone walls that may have once been part of an ancient settlement. The landmass it was built upon was separated from the main island by a narrow strip of land. . . .
Through radiocarbon analysis of preserved wood, the entire settlement was estimated to date back to approximately 4,900 BCE.
“People walked on this [road] almost 7,000 years ago,” the University of Zadar said in a Facebook statement on its most recent discovery. . .”Neolithic artifacts such as cream blades, stone [axes] and fragments of sacrifice were found at the site,” the University of Zadar adds.
accessed online at https://www.sciencealert.com/road-built-7000-years-ago-found-at-the-bottom-of-the-mediterranean-sea)
This artificial island has also been part of an on-going installation work by German filmmaker and moving image artist, Hito Steyerl, and described in a recent article as: “submerged by rising waters that speak both to geological deep time and contemporary climate upheaval” (accessed online at https://aestheticamagazine.com/flooded-worlds-parallel-realities/).
After being so primed, you too can see the submerged island, its causeway to surface land, and imagine how the still-rising waters will inundate more settlements ahead in the climate emergency. The problem however arises when the preceding “imagine” is treated as a premature demand to shift from a further analysis from the granularity in front of you to a prediction about what is to happen more generally, now and ahead.
For take another look at the picture and reread the accompanying text and ask what that displayed level of granularity now enables you to: “But what about the presettlement template displaced by the Neolithic roadway and settlement and their own follow-on effects?” “Or for that matter, what about what’s been preserved here from having been submerged for so long? What does this tell us about how the retreat from rising sea level was managed, at least here and then?”
That is, in asking such questions you end up focusing on: “What happens next here and now?” I mean that literally: “What happens next at and around the submerged site? Are they to be protected (that is, why these sites and not other worthy candidates for protection in the face of the climate emergency)?”
More formally, you may think the above example lays the basis for predicting the need to do something with respect to the climate emergency elsewhere and over the longer haul. I am instead suggesting that really-existing accomplishments that happen over time and at that site–if you will, the track record of building on affordances provided by setbacks then and there–go to reframe the pertinent policy relevance. People already understand what are case-specific accomplishments and setbacks in ways that a broader “success or failure with respect to the climate emergency” can be understood by others only later on.
III
One consequence of “success and failure” being better understood only retrospectively is that predicting success ahead means not really understanding what has been predicted. In response, I’m speculating here that if we dial back the terminology to the more granular level of specific accomplishments and specific setbacks, we are in a better position to be more usefully abstract (less granular in our scenarios) about what’s ahead.
For example, surprise and contingency often produce the granular, if not idiographic, conditions and demands for improvising real-time management of critical infrastructures. Specific setbacks and specific accomplishments abound. This in turn produces two further findings, which however lack the same level of granularity with respect to prediction as in the preceding example: namely and more abstractly, what is predictably unimaginable and what is so taken for granted it is not even predicted.
1. The predictably unimaginable. It’s no surprise when experts predict disasters with unimaginable consequences because they cannot specify scenarios of sufficient granularity for action or not. But in practice this means we start with the worst-ever floods and earthquakes in the US and then argue that the Magnitude 9 earthquake off of the Pacific Northwest will be unimaginably worse. We don’t say, at least in my experience: As unimaginable disasters are indescribably catastrophic, we need to narrow our focus to something like a M9 earthquake. Why? Because that way we frame what we know and don’t about really-existing improvising and ingenuity with respect to the worst-ever floods and earthquakes that have happened here.
2. The taken for granted in no need of prediction. Stay with the assumption that a M9 earthquake in the Pacific Northwest will be unimaginably catastrophic. Indeed, it is taken for granted knowledge by many of our interviewees–so taken for granted, it isn’t a prediction as much as it is a given. But the necessity to improvise in any earthquake means there are no other givens. From the infrastructure control room and field operators perspective, nothing is predictably taken-for-granted in these conditions and thus prediction can be–and often is–besides the point.
In both of these cases of 1 & 2, there is no workaround for what is actually improvised because the level of granularity isn’t there to specify beforehand (or during) one or more such scenarios. What happens is accomplished even if later judged less as success, where a real-time setback isn’t automatically a failure though.
Where then are we to find the actionable granularity, if it exists?
IV
One answer is to start with those really-existing improvisations and cases of ingenuity in major disasters. Note here this means dialing back the terminology from “imagination” and “creativity” to quick fixes and just-in-time activities involving one but often more personnel. Efforts to restore critical infrastructures during immediate emergency response (e.g., through of mobile telecommunication towers) almost always entail real-time improvisation, within or across the infrastructures involved. Indeed, they may become the only key real-time interconnection between the systems during those times. This in turns puts a high priority on pre-disaster efforts to improve the joint restoration and recovery resilience across those interconnected critical infrastructures.
What does this mean practically? It means capitalizing on existing opportunities beyond the official emergency management structures and plans at the local, regional, state and federal levels there. The aim is to leverage existing initiatives that have already “seen the light, ” for example, vessel traffic services, marine exchanges, and harbor safety committees. The priority in focusing on those who actively acknowledge the centrality of interconnectivities is made all the more visible because these remain early days in thinking through emergency management in terms of infrastructural connectivities.
The core competency called for in more effective modeling, table-tops, real-time control room desks and the like is in the area of inter-infrastructural connectivities. These professionals are targeted because they already work outside their infrastructural or sectoral siloes. . . .Even when global factors such as climate and capitalism clearly influence major disasters, that acknowledgemetn needs to be pushed further, as variation in inter-infrastructural connectivities at the local and regional levels matter so often and so directly for policy and management. . . .
[To be continued]
WHEN COMPLEX IS AS SIMPLE AS IT GETS 