8
Sailing Through the Dark
Insight
Nishith Hegde, the winner of the ‘Best Writer’ prize, explores how the presence of uncertainty affects decision-making and economic policy. We possess neither the ability nor the technology to perfectly know everything about our world, and yet find ourselves with no choice but to navigate it, directed only by fragments of information that we use to illuminate and infer the path ahead as though sailing a ship through the ocean guided only by the stars. This state of partial information, uncertainty, is what couches every action we take, and every perception we form. When it comes to decision-making, therefore, two problems arise. Firstly, we are almost always making decisions under false assumptions – or rather, under a simulacrum of the truth that is merely an imperfect impression. Put simply, we misunderstand the world we live in, and, in response, select options that therefore lead to negative outcomes. But the second is even more fundamental: even when the first problem is solved by just giving us the full information we require, when we’re given hard statistics, or dealing with perfect hypotheticals that pose no risk to us personally and cannot be affected by unforeseen factors, the mere presence of uncertainty creates infuriatingly inconsistent decision-making. The foundational pillars of modern economics rely upon the economic agent being rational and utility-maximising. In reality, this archetypal economic agent cannot even consistently determine their own preferences. Our decisions entail important consequences. They shape our behaviour and our interactions – They are the difference between a happy day and a depressing one, between winning big and losing it all, between a guilty verdict and an acquittal. But moreover, they have severe implica-
tions for policymaking. Widespread, false, assumptions create perverse electoral pressures for legislators, producing ill-suited policy. But there are additional consequences to this irrational tendency: a framing bias affects the testing of different policy options, and even well-suited policies are limited in their effectiveness. Economic models may have all the answers – but they remain ineffective when their consumers themselves are stubbornly imperfect. So why does the presence of uncertainty encourage these behaviours? And are there solutions to accommodate them in policymaking? Slowly, our understanding of both is starting to advance.
HEURISTICS
Ultimately, this behaviour is caused by our use of shortcuts. In order to save precious mental processing power, and form decisions quickly, we adhere to a set of rules of thumb in order to form conclusions about the world. These are known as heuristics. Here’s an example: studies repeatedly show that groups of test subjects demonstrate a tendency to prioritise perceptions over evidence. A key 1974 study by Amos Tversky and Daniel Kahneman demonstrated that when a company with 30 engineers in it, and 70 lawyers, was described, and then some characteristics of a particular employee (meek, isolated, introverted) given, a significant proportion of test subjects believed the employee to be an engineer. The probability of being an engineer was registered by subjects as close to 50%, even though the real probability, absent stereotypes, is 30%. The really interesting finding came when they compared these outcomes across groups who were
given different information. With no characteristics at all, groups correctly identified that the likelihood of this employee being an engineer was 30%. But when told irrelevant characteristics (no children, unmarried, or demonstrating promise) that were completely outside of the stereotypes of engineers and lawyers, test subjects reverted to their previous prediction of close to 50%: a partial information set led to less accurate decision-making than no information at all. What this suggests is that in the presence of even the smallest uncertainty, our decision-making switches from rational to heuristic. Further to this, have you ever wondered why restaurants stock incredibly overpriced wines that are clearly poor value, and that almost no-one buys? One reason may be the compromise effect. If presented with two distinct options, a cava for £10 a bottle and prosecco for £15, you may find yourself preferring the lowerpriced cava. But in the presence of an alternative, for example a £35 champagne, there is a strong tendency to choose the middle-price wine ahead of the lowest: people outright reverse previous preferences for no reason other than the presence of another alternative. This shows how even our own preferences become incredibly context-dependent, and subject to a framing effect; while the restaurant takes in an extra fiver in revenue. Likewise, there is strong evidence that individuals exhibit an anchoring effect. This effect essentially says that estimations and predictions are not rationally and independently determined; rather we take some initial ‘anchor’ and shift that value upward or downward. This again leads to a number of problems. For example, adjustment is often insufficient