can we rely on the predictions and projections of experts, and when are policymakers
simply forced to deal with uncertainty? In the latter event, how should
uncertainty be handled? I recently discussed these questions, and many more,
with Lord Mervyn King.
Mervyn is a professor of both economics and law at New York University, and he is a former governor of the Bank of England. He is also the co-author, along with John Kay, of Radical Uncertainty: Decision-Making beyond the Numbers.
Pethokoukis: In the 2020 election, it seems that the polls overestimated Biden’s support. Is this an example of the kind of radical uncertainty that the book addresses?
King: Yes. Radical uncertainty lies between events that we can happily use the laws of probability to describe — events which are repeatable so we can compute the probabilities — and events in which the probability is unimaginable.
The 2020 election was an example of the latter. It was a one-off race — it was not going to be repeated. So the predictive models tended to confuse rather than help us think about the outcome. The issue is that these models assume a great deal about human behavior, and these things change from election to election. For instance, in the 2016 Brexit referendum, young people did not vote. So in 2017, the modelers assumed they could give less weight to young people. That assumption turned out to be wrong when young people did come out and vote that year.
People’s behavior changes from one period to the next. So the models — not just in this area, but economic models and COVID-19 epidemiological models, for that matter — are bad at predicting the future. So the lesson is to keep options open and wait until you know the outcome.
Even if models and projections can be inaccurate, you don’t believe that we should just tune out experts and disregard their supposed expertise, right?
I certainly don’t want to give up on the use of experts. If you contract a disease, you want to talk to a qualified doctor. But there’s a big difference between using experts to understand what is going on versus making predictions.
A good example is what’s happened in many countries with COVID-19. Experts can tell us about the nature of viruses, because they understand epidemics. Their insights are very important in thinking about how to tackle an epidemic. But the epidemiological models are not good at predicting the path of any given epidemic. We’ve seen that very clearly since March. The forecasts made about the number of cases and deaths were often way off.
That’s partly because experts disagree about some of the key parameters, but in large part, it’s because some of the crucial parameters that determine an epidemic’s spread are about human behavior. And those are not scientific constants that you can measure and feed into a model. They are assumptions that modelers are making, and those assumptions can be wrong. And there are just many things about the phenomenon of COVID-19 that we don’t understand. That is not to reject experts, but it’s to warn us that we can’t rely on experts to give us the answer.
Whether it’s epidemiologists or economists, should we view them more as framers of choices rather than forecasting machines?
That’s a better way to view them. When governments say, “We’re just doing what the science tells us to do,” that is very foolish, because the science doesn’t tell us what we must do. It informs the judgments that our political leaders have to make about difficult trade-offs. So, when we’re confronted with any situation that’s radically uncertain, the right question to ask is simply, “What is going on here?” And experts can help us understand what may be going on so that we can think more clearly about the question. They also tell us what we need to know more about. It’s this role — helping us think through a problem — that’s important, not the pretense that the expert has the answer.
Politicians, in the long run, lose credibility by making claims and forecasts that are simply not borne out. A much more humble approach would actually benefit politicians, because people’s belief in their credibility responds to honesty and openness and not to a belief in false predictions.
What is the role, then, of experienced-based intuition and judgment? Once you’ve heard the analysis and it’s time to make a decision, how do you make that leap? Should you rely on your “gut” instincts?
There’s something to that, but I think it’s actually important not just to rely on gut instinct.
An ideal expert’s role is to conduct a cost-benefit analysis
and to come back with a handful of numbers that really matter. Keep it simple.
Don’t complicate it, and don’t try to wrap up the answer in terms of something
that only a computer can calculate.
Then, experience comes in: It gives you a strong feel for what things you should be suspicious of when people produce calculations and forecasts — and what things you think you can rely on. But you should always ask yourself the question, “What is going on here?” Look for potential weaknesses in arguments and actually challenge the narratives going into decisions before you take them — that’s really important.
So the last thing you want to do is to outsource the decision to a group of so-called experts, but just relying on one’s own gut instinct can also be dangerous.
The book is about uncertainty, but it shouldn’t be our goal to squeeze out all of the uncertainty in life. It’s not necessarily a bad thing, is it?
No, it isn’t — uncertainty is to be embraced! Uncertainty is the source of almost everything good in life. It enables entrepreneurs to create new products that people hadn’t imagined before, making it the driving force behind a market economy that boosts our living standards over time. So from a purely economic point of view, that degree of uncertainty is fundamentally important.
Serendipity is the most wonderful thing. You meet people you didn’t know, you go to places that you hadn’t seen before and didn’t imagine, you read books or listen to music that you hadn’t thought about before. These are the uncertainties that make life exciting, which is why humans have evolved to be pretty good at coping with uncertainty. We can’t predict, but we don’t want to be able to predict everything that’s going to happen to us. Otherwise, we would be bored to tears. So we should embrace uncertainty while at the same time taking careful steps to manage the risks that we face.