The future appears alien to us. It differs from the past most notably in that the earth itself is the relevant unit with which to frame and measure that future. Discriminating issues that shape the future are all fundamentally global. We belong to one inescapable network of mutuality: mutuality of ecosystems; mutuality of freer movement of information, ideas, people, capital, goods and services; and mutuality of peace and security. We are tied, indeed, in a single fabric of destiny on Planet Earth. (Peter Senge)
As humanity strives to overcome an arguable polycrisis and polities attempt to chart a coherent future, every policy-maker at every level (and indeed, private decision-makers dealing with the far-reaching implications of their local decisions) must come to terms with Senge’s “inescapable network of mutuality”. Indeed, arguably the most critical challenges to the commons today are both global and highly contextual. Issues like climate change or pandemics are obviously relevant to everyone, yet policies must be set locally, and the relevant data points, constraints and objectives form an enormously complex web.
The activity of progressively and adaptively making sense of this web is a process that systems thinkers have dubbed building mental models. Mental models are the “water of systems change”: in the words of Donella Meadows,
… from shared social agreements about the nature of reality, come system goals and information flows, feedbacks, stocks, flows, and everything else about systems.
From the deep interconnectivity of this web, we can conclude that every instance of contextual understanding and decision-making needs to integrate worldviews and mental models across the entire spectrum of generality and abstraction, from broad “paradigmatic” assumptions all the way down to context-specific, local/situated (and often embodied/tacit) knowledge is needed. Further, this integration must be two-way; just as local knowledge is informed by top-down constraints, global paradigms must and do derive their legitimacy from bottom-up validation against the sharp edge of reality and practice.
However, the crucial task of global integrative sensemaking has been delegated throughout the 20th century to a host of centralized, bureaucratic policy and science institutions. These institutions - whether national or global, governmental or self-authorizing - are simply unable to internalize all this complexity; their conclusions and reports may be dressed in the mantle of authority and the jargon of science and data, but it’s becoming increasingly clear that this appearance is neither a guarantee of good science nor of timely, effective policy-making.
For example, the United Nations’ climate science center has, in the past, produced reports with egregious technical errors that, rather than being easy to paper over due to the ticking time-bomb nature of climate change, have seriously impacted its credibility, damaging the underlying policy cause for years. More recently, the UN’s World Health Organization has experienced significant pushback to its messaging and policy measures to mitigate the COVID-19 pandemic. Whatever the ultimate scientific value of these criticisms, the fact remains that “global science” is quickly losing its efficacy as the hallmark of sane global policy, posing serious danger to the latter’s legitimacy — and this despite the great need for policy that takes effective action in these arenas. Absent a replacement shared sensemaking framework as a safety net, the very social fabric that’s needed to make policy relevant is threatened. As Gordon Brander puts it:
The cost of forking realities has dropped below the Coasean floor, and there’s little incentive to merge realities. We fractally fragment understandings, then algorithmically amplify the confusion to maximize engagement. The most effective coordination mechanisms left seem to be memes and conspiracy theories.
There’s a painful need for better solutions. However, tackling this will not be a simple matter of replacing institutions, or even of building incentive systems. Rather, the very primitives of collective sensemaking must be upgraded for the exponential age.
Every good regulator must contain a model of the system. (Roger C. Conant and W. Ross Ashby)