Uncertainty and understanding behaviour

From Cameron Murray on the trolley problem:

In Scenario A a trolley is barreling down the tacks toward five people who will be killed unless the trolley is stopped. Luckily, there is a fork in the tracks, and by simply pulling a lever, the trolley can be diverted onto a second set of tracks. Unfortunately there is a single person in the path of the tolled on this track who will be killed if you pull the lever.

The dilemma is whether you should pull the lever and save five people by sacrificing one? In surveys most people say they would.

In Scenario B you find yourself on a bridge next to a fat man where below the same dilemma is playing out, with a trolley hurtling down the tracks towards five people. The question here is whether it is permissible to pushing the person next to you onto the tracks if you knew it would stop the trolley and save the five people.

Most people in this scenario would not push the man off the bridge, even though the same welfare gains in terms of lives saved would be the same as Scenario A (so you know, 68.2% of philosophers would push the man to save the five). …

Fundamentally the incompatibility of these two outcomes arises because we are presented with a dilemma in terms of risk, or knowable probabilities. …

Let us now look at the question in terms of uncertainty. For a start, how do we know the trolley is out of control? Is it possible to delay the decision to get more information?

… [I]n Scenario A, switching the tracks leads to a new situation that opens up the set of possible choices … while eliminating others. Switching the trolley onto the side track buys time and keeps options open without killing anyone.

In Scenario B, most people choose not to push the fat man. Here what the are doing is buying time before anyone gets killed. Even after the decision is made not to push the man, there will be time available for many other as-yet-unknowable situations to arise. …

The whole rationale of making decisions in a world of uncertainty revolves around keeping options for desirable outcomes open, and often this involves buying time by not making a decision at all.

A couple of practical examples:

In criminal behaviour, Becker’s expected utility framework has been called into question due to the radical difference between human behaviour in a world of uncertainty versus a world of risk. Increasing chances of being caught and increasing punishment if caught are substitute methods for changing probability distributions of expected outcomes in a world of risk, but in a world of uncertainty they will have far different effect on criminal decisions.

The same logic of uncertainty can be applied in social psychology to understand the bystander effect. The bystander effect is the label given to the occasionally observed inverse relationship between the number of people witnessing a victim in need, and the number of people offering help. Various reasons for this empirical phenomena have emerged, with the idea of a diffusion of responsibility dominating explanations.

But when we dig a little deeper we can see the logic of uncertainty at play. Repeated experiments on the bystander effect show that the degree of ambiguity is a crucial determinant of the willingness to assist, with reaction times being much slower in the presence of more ambiguous situations.

Read his full post.

One comment

  1. The parsimonious hypothesis is that evolution has selected us not to kill people to save strangers. The evolutionary logic is pretty straight forward. Killing the fat man will lead to his brothers and uncles seeking revenge.

    Granted this is a just so story until such time as somebody empirically verifies it somehow. But that said, it would be my working hypothesis.

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