An individual decides to drive home after an evening out despite being knowingly over the legal alcohol limit; before completing their journey they are stopped by the police and charged with driving under the influence. In a parallel universe, the same scenario occurs but with one key difference – prior to being pulled over by the police the individual’s intoxication leads to an accident that causes serious injuries for passengers in another car. How should we view the perpetrator in these two incidents?
Our reaction from an ethical[i], and legal, standpoint is often to judge the second version more harshly – because the consequences were far more severe, but should this be the case? In both cases the main failing is identical – the initial flawed decision to drive after excessive alcohol intake. The relative results, however, are due to luck; the individual in the first instance experienced good luck (comparatively), and the other bad. Such judgements are often heavily influenced by the results, even if they are reliant on chance; an example of outcome bias[ii].
Our tendency to judge the quality of a decision by the ultimate consequence is a simple concept. In many instances it is also a prudent one; results often provide a useful gauge of the value of the actions that led to them. However, as with many things, once you add a healthy dose of randomness things start to become problematic.
“A good decision cannot guarantee a good outcome. All real decisions are made under uncertainty. A decision is therefore a bet, and evaluating it as good or not must depend on the stake and the odds, not on the outcome”[iii] (Ward Edwards)
More here – Behavioural Investment