We don’t know what the future holds, but we still need to make far reaching decisions.  Unlike F. A. Hayek, who said the he preferred true but imperfect knowledge to a pretence of exact knowledge that is likely to be false, we seek certainties that don’t exist and invent knowledge that we can’t have to support our decision-making.

In Radical Uncertainty, John Kay and Mervyn King, two well-known British economists, state that rather than trying to understand the ever-changing, uncertain and ambiguous environment by trying to understand “what’s going on here”, the economics profession has become dominated by an approach to uncertainty that requires a comprehensive list of possible outcomes with well-defined numerical probabilities attached to them. Drawing widely on philosophy, anthropology, economics, cognitive science, and strategic management and organisation scholarship, the authors present an argument that probabilistic thinking gives us a false understanding of our power to make predictions and a false illusion of utility-maximising behaviour. Instead of trying to produce probability calculations to fill the unknown gaps in our knowledge, we should embrace uncertainty by adopting robust and resilient strategies and narratives to consider alternative futures and deal with unpredictable events.

Kay and King frame their impressive tome within the debate that defined the future of economics in the second half of the 20th century – John Maynard Keynes and Frank Knight in one corner and Frank Ramsey and Jimmie Savage in the other. Keynes and Knight believed in the ubiquity of “radical uncertainty” that is based on the premise that we do not know what is going to happen, and we have a very limited ability to even describe the things that might happen. Keynes and Knight made a distinction between risk which could be quantified with probability calculations and real uncertainty that is unquantifiable. In Knight’s world, radical uncertainties give rise to entrepreneurial opportunities which are the cornerstone and dynamic of a capitalist economy, although Keynes considered these uncertainties as a source of instability. In contrast, Ramsey and Savage – and later Milton Friedman – insisted that all uncertainties could be described probabilistically, and economic agents were able to undertake rational, utility-optimising calculations to guide their decision-making.

Ramsey and Savage, and what became known as the Chicago School of Economics, won the argument, perhaps because the probabilistic world was convenient as it could be described axiomatically and mathematically. Having settled the argument, the practice of economics and scholarship became dominated by a concept of rationality that is not based on observation or introspection, but a priori axioms, and where uncertainty has been reduced into a quantifiable risk. Having tamed uncertainty and made the assumption of perfect rationality, economics came increasingly to resemble physical sciences with fundamental laws of physics such as gravity. Kay and King write (p. 133):

“This way of thinking we will describe as ‘axiomatic rationality’. It has the logical consequence that there is something which might be described as ‘subjective expected utility’ which individuals who are ‘rational’ are maximising. Obedience to these axioms, it was claimed, defined ‘rational’ behaviour.” 

Hence, businesses were assumed to maximise shareholder value, policy-makers social welfare, and you and I were claimed to rationally maximise our happiness or utility. Drawing from their own academic and practical experience Kay and King state (pp. xiv-xv):

“Although much can be learnt by thinking this way, our own practical experience was that none of these economic actors were trying to maximise anything at all … injunction to maximise shareholder value, or social welfare, or household utility, is not a coherent guide to action. Business people, policy-makers and families could not even imagine having the information needed to determine the actions that would maximise shareholder value, social welfare, or household utility. Or to know whether they had succeeded in doing so after the event.”

The authors’ “radical uncertainty” is not about “long tails” (for example, imaginable and well-defined events whose low probability can be estimated). The authors emphasise the vast range of possibilities that lie in between the world of unlikely events which can nevertheless be described with the aid of probability distributions, and the world of the unimaginable.  This is the world of uncertain futures and unpredictable consequences, about which there is necessary speculation and inevitable disagreement which often will never be resolved. In real life this is the world which we mostly encounter, and it extends to individual and collective decisions, as well as financial, economic and political ones.

Decision-making under “radical uncertainty” requires a wide range of skills that can rarely be found in a single individual. Successful decision-making under such conditions is a result of collaborative processes, collective intelligence and judgment. Kay and King advance the argument that the use of the narrative and respect for diverse views can generate a better understanding of “what’s going on here” than an overreliance on rigid econometric models. This does not mean that we should toss out the models entirely as they can give us a sense of direction and insight, but the sole reliance on them may not allow us to see the wood for the trees and understand the nature of the real issue.

Kay and King’s book is a thoughtful and welcome call for economists and policymakers to accept “radical uncertainty” and start rethinking their models. A broader perspective is needed to understand “what’s going on here” and what may happen next, not only with the economy and markets, but other political, social and technological developments and disruptions.

 

 

Kay, J. and King, M. (2020) Radical Uncertainty: Decision-making for an unknowable future. London: The Bridge Street Press.