Two types of exponential bias

Exponential growth bias (EGB) is one of a long list of cognitive biases identified by psychologists and perceptions of it and its prevalence have come to play a significant role in the development of policy responses to Covid-19. 

In brief, the bias is seriously to underestimate the future values of something that is growing at a constant proportionate rate. Its existence has been well attested in research stretching back over several decades and a classic illustration is an ancient puzzle:  Put one grain of wheat/sand on the first square of a chess board, double it on the second, keep doubling until the 64th square and then ask how many grains there will be on that last square. The numbers just race upwards in a way that most people cannot get their heads around.

At the opening of the encounter between the British public policy making establishment and the SARS-CoV-2 virus, a view was formed that the public would significantly underestimate the rate of spread of the virus and hence underestimate its risks.  In effect, there was an assumption that the public would exhibit EGB.  From this it was deduced that risk-avoiding social conduct taken of their own volition would be too low for the good of the community: the public would be insufficiently fearful.

The view that was adopted lacked any strong evidential support — it was not science as we know it.  It was an assumption/pre-judgment, but there were some justifying reasons for it. Most of the population are not familiar with exponential curves and their rather special properties.  Nor have they encountered repetitive exposure to contexts in which something or other is growing exponentially, from which experiences they might have (inductively) developed rules of thumb that could guide them in relevant circumstances (as coastal dwellers did in charting the tides & linking them to lunar cycles long before the arrival of Newton’s theory of gravitation).

However, these reasons were well short of sufficient for safe adoption of the assumption.  There are psychological studies that indicate tendencies to over-estimate risks in particular contexts, for example risks of criminal harm perceived by older citizens, or, more generally, risks of rare and unfamiliar events that are characterised by adverse and vivid consequences that grip the mind (‘sensational events’). And perhaps the crucial observation in all this is that, back in March, Covid-19 certainly did appear to grip the minds of those charged with its management: the fear was almost tangible.

More self-aware policymakers would have recognised that there is a familiar motes and beams issue here:  an assumption that the high level of fear of the ‘managers’ was appropriate, but that what the managers perceived (without much in the way of evidence) to be the fears of the hoi polloi were inappropriately low. But, not for the first time in human history, the beam was not spotted. The resulting, narrow and unbalanced assessment of the various cognitive biases that might be in play led the British Government, under the guidance of people identified as scientists, to deliberately adopt a policy of inducing greater fear of the effects of SARS-Cov-2 among the general public.

If the narrow goal was to enhance fear to a level judged appropriate by the fearful, the policy was spectacularly successful in achieving it: in comparative international studies Britons are now assessed as the most fearful of peoples.  Judged against wider goals, however, it has been a spectacular failure, a policy folly: Britain stands very high in the international league for excess death rates and in the bottom reaches of the league for adverse economic impacts. Moreover, a former judge of the UK Supreme Court, Lord Sumption, has characterised the effects of policy as “… the greatest invasion of personal liberty in our entire history” – and that is a long history, not free of a tyrant or two.

In reality, and like sorrows, cognitive biases tend not to come as single spies, but in battalions. Most of us are subject to several, but there is one, hitherto largely unidentified bias that appears highly relevant for understanding our current situation.  I will refer to it as Type 2 Exponential Growth Bias, to distinguish it from the familiar EGB (henceforth Type 1 EGB).  It is simply defined as a tendency tosee’ or infer an exponential curve (or something broadly similar, a curve that is rising and bending upwards) where no exponential curve exists or is likely to exist

An immediate implication of this definition is that it is a bias whose incidence is likely to be limited to that class of people who have some familiarity with, although not necessarily a full understanding of all, the properties of these curves/functions. To imagine an exponential where none exists it is necessary first to have some view of what an exponential curve looks like, and possession of such a vision is not ubiquitous,

I first became aware of the phenomenon back in 2007 when conducting a piece of research on obesity policy and hence was looking at a stack of data on the matter, as well as rifling through recent papers on the topic. Among the latter there was an editorial piece in a medical journal that contained a chart showing a hypothetical projection of obesity prevalence over time.  Given the availability of data, it was odd in that there were no units shown on the axes (not quite science as we know it), but even odder in being a rather sharply rising exponential curve. 

How could that be?  Percentage prevalence of obesity, however measured, is bounded above at 100%: that’s where the feasible per-cents run out.  If the rate of increase has gone up – as it had in the 1990s – it must later come down again, as it has done since circa 2005 on UK metrics. 

History rhymes, and almost daily in the papers over the past few days there have been accounts of medical ‘scientists’ in Britain warning, like the obesity medics of fifteen years ago, of exponential growth (or something approximating it) in infections to come. And today (20th September 2020) we have the Chief Scientific Adviser to the Government saying that infections are doubling around every seven days and conjuring up visions of 50,000 infections a day by mid-October unless, by a familiar recourse to politicians’ logic, something is done about it.

There could hardly be a more illuminating display of Type 2 EGB and I hope its vividness registers with Parliamentarians and the Public. In point of fact, there is no exponential curve to be found in the data and no such curve is predicted to exist by the epidemiological models. 

What is going on here is a probably a familiar phenomenon.  Type 2 EGB can be viewed as a variant of the more widely studied confirmation bias.  We see what we want to see or find it convenient to see, for one or more of a mix of motivations:  money, status, power, fifteen minutes of fame, ideology, economy of cognitive effort (the brain being a large energy sink of the human body), avoidance of discomforting cognitive dissonance, not being shown to have been wrong about something, and so on. 

‘Seeing’ an exponential hobgoblin can serve these purposes for some, including those with an interest in scaring people towards conduct that is congruent with the seer’s own agenda. For the rest of us though, Type 2 EGB is a dangerous cognitive bias for anyone in authority to possess, arguably more dangerous to human welfare in the round than the physical virus that is SARS-CoV-2. 

Physicians, rid thyselves of this delusional affliction is an appropriate conclusion.  Adjust your views to the changing evidence, don’t try to adjust reality to your preferred belief system.  The latter is the path of tyrants, not scientists.

Author: gypoliticaleconomyblog

Lifetime student of political economy, retired academic and regulator.

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