Loss Aversion and Horizon

3 Mar

Like a lot of people I watched Horizon’s report on decision making last week, and really enjoyed it. The research was presented in a skewed but entertaining way and it’s motivated me to write down my thoughts on loss aversion as a cognitive bias as it provides a great illustration of the tension between a bias and a heuristic in decision making. For the purposes of this article I’ll define loss aversion quite crudely as people’s strong preference for avoiding losses over achieving gains. This preference can result in people turning down options or risks which would yield gains but end up being declined if the risk\ option is framed in terms of losses- you stand a 10% chance of losing 70% of what you have for example.

Cognitive bias itself is a systematic error, which is reliably predictable, when a decision is made (and if the decision maker lacks the necessary information to frame the question appropriately). A heuristic is more or less its opposite, a rule of thumb, an imperfect but good enough short cut which works well most of the time in a particular domain. In a very simple form we can think of bias as a mistake and a heuristic as a rule of thumb. Loss aversion, I would argue, is something which has become a bias. The reason for this, I think, is that loss aversion began life as a heuristic which became a bias as a result of changes in the human risk domain.

And this is why –

Way back in our history survival was dependent upon meeting our most basic needs- food, shelter, warmth. If you were able to secure yourself a cave (for example) with some furs and fire for warmth, and some food, you were more likely to survive, at least in the short term. The subtraction of these items meant that you were far less likely to survive. So, once these items were secured, holding onto them was essential, it paid to be loss averse. If you were able to hold onto these items it would also allow you to minimise future risk taking, further increasing your survival chances since the risk consequences were very often life and death. In a domain defined by scarce recourses and securing these recourses carries great risk, then loss aversion operates as a heuristic.

Back to today, when you have a surplus of warmth, shelter and food (in some economies and only in sections within them) you can probably afford to take a few well thought out risks to try and get a little extra due to changes in the risk domain. But the old heuristic operates as a bias because when you are faced with a loss, or a perceived loss, even from a relative position of strength or security (your risk domain) you’ll still short cut default to avoid losing anything- unless you know the risk domain which enables you to frame decisions more appropriately and reverse the bias. So, why is it important to point out that bias used to be a heuristic? I think it’s important because the role of information and environment in shaping perception is crucial. Knowing the boundary conditions for when a heuristic can become a bias and vice versa is essential to making a decision involving different or changing domains; and especially when seeking to transfer expertise from one domain to another. In short, knowledge of the risk domain is crucial to framing decisions appropriately, if you don’t remain sensitive to changes in risk a heuristic could easily become a bias, and sometimes with disastrous consequences.

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