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Radical Uncertainty by John Kay and Mervyn King, The Bridge Street Press, 2020.

People like the illusion of certainty, or at least a measure of control, especially over the future, that’s why charlatans are popular. In front of me is a Guardian article about an IFS study estimating that the Covid 19 disruption to young people’s education may cost them up to £360bn in lost lifetime-earnings. If you can’t see why this sort of thing deserves widespread ridicule, then read Kay and King’s book.

The book looks at the history of economic thought and marks the wrong turns along the way that have led economists to be entirely useless when we are most needed, busy fiddling with our graphs as the economy burns and malfunctions. They are particularly damning about our misuse of probability (Keynes, as always, was ahead of them, sadly no-one but us geeks has read his Treatise on Probability) as we apply spurious numbers inappropriately under the misapprehension that ‘I’m 82% confident that the FTSE will fall in 2022’ is somehow more accurate than ‘I’ve got a really bad feeling about this’1.

They start with the bedrock of economics: that people engage in optimising behaviour in order to maximise something e.g. profit or utility. Samuelson modified this to show that this optimisation needn’t be conscious but if people acted ‘as if’ optimising, the models would be workable. The problem is that whilst this may work over the very short term, once it is scaled up to the future it becomes useless. Worse, it gives an illusion of knowledge and predictability where none exists.

Kay and King rediscover the critical difference between risk and uncertainty: risks are things we know about and can predict, not perfectly, because it’s the future, but good enough to be able to build them into decision-making e.g. my car insurance is much cheaper than any teenager’s because statistically middle-aged women are much safer drivers than teenagers, the occasional outlier doesn’t invalidate the broad model.

Radical Uncertainty is about ‘unknown unknowns’, stuff we don’t even know we don’t know, e.g. how would you have predicted the 2021 sales of iPhones in 1990? It’s also about ‘known unknowns’, stuff we know we are ignorant of or, at best, have huge gaps in our knowledge about. It’s this area where a bit of humility might improve our decision-making. Kay and King argue that, whilst numbers are hugely helpful in some contexts, spurious numbers attached to outcomes about which we have huge areas of ignorance give an illusion of certainty where none exists and lead to mistakes in decision-making. Instead they argue for the return of narrative and judgement, openly acknowledging the dangers and possibilities inherent in ignorance and for flexibility and adaptation in the light of new information rather than blinkered ‘computer model says ‘‘no’’’ approaches combined with quasi-hysterical cries of ‘U-turn’ when someone alters policy in the light of more information.

They finish optimistically, so shall I. Covid19 has been horrible and we all know many of the downsides and some of the positives (vaccine scientists, selfless volunteers etc take a bow). Radical uncertainty means that more downsides but also huge positives may yet emerge from this, we simply don’t know and thus bleak despair is truly irrational behaviour. It might be that Captain Sir Tom was right and today and even tomorrow might be a good day after all. It will certainly be different we just don’t know how yet in what way, neither do the IFS and the Guardian. Read this book and tell your young people that the world isn’t safe but it is full of possibilities.

Ruth Corderoy

Reference

  1. Fun task: get your better students to explain why you can calculate the probability of 13 red on a roulette wheel highly accurately but not accurately predict the chances that a particular ‘flu virus outbreak in a Chinese province would paralyse the world economy in a given year.

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