Risk Homeostasis

A Theory about 

Risk Taking Behaviour

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Gerald J.S. Wilde Ph.d

  RiskAbout Risk Homeostasis

A Theory about Risk Taking Behaviour

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Finding the balance - Risk Homeostasis in a Tiny Nutshell

As there is no decision with total certainty of outcome, all decisions contain an element of risk. Living organisms must choose a level of riskiness in their decisions such that the net expected benefit of the behaviour chosen is maximal. This net benefit depends on four utility factors. More risk will be taken when (1) the expected benefits of risky behaviour alternatives are higher, (2) when their expected disadvantages (costs) are lower, (3) the expected benefits of cautious behaviour alternatives are lower, and  (4) their expected disadvantages greater.

The balance of these factors determines the level of risk that people are willing to take: This is their target risk, and this concept applies to all behaviour domains, such as food intake, drinking, smoking, love life, finance management, social relations, mobility (traffic) and moral, ethical dilemmas, and sports

The term target risk does not imply that people take risks for the sake of risks, but that it is tolerated/desired/accepted for the satisfaction of other motives, motives that are in incompatible with health and safety. Similarly, the term target risk does not imply that people arrive at it on the basis of careful weighing of the relevant risk factors. In most situations, the magnitude of these risk factors is unknown and only allow decision making on affective and intuitive grounds (which is not necessarily inferior to detailed analysis and calculation). In traffic with its time pressure, people must make their decisions on the basis of what, given the circumstances, seems best or "feels good."

It is obvious that the actual decisions made determine the accident rate in the population. The homeostatic element in the theory of risk homeostasis is located in the notion that there is a feedback loop between the population accident rate and the level of perceived accident risk: changes in the accident rate are followed by changes in the level of risk perceived and thus cause subsequent changes in behaviour, as well as vice versa.

This may be illustrated by the following. When Swedish road traffic changed from left to right-hand traffic, from one day to the next in 1967, perceived levels of risk soared to uncommon heights and exceeded the target risk by far (see Utility Factor 3 above). Consequently people became extremely cautious and the accident rate dropped significantly. After some time road users became aware of this drop and felt less of a need for great caution; the result of this was that the accident rate climbed again to a level before the change-over.

Sometimes, the feedback loop operates much faster as in the case of the famous experiment with Munich taxi drivers. Some of the cars were outfitted with ABS, other cars were not but in all other respects identical. The drivers anticipated the effect of ABS on the controllability of their vehicles and thus their safety, and adapted their behaviour accordingly. No effect on safety could be seen, and the taxi company did not score a reduction in the accident rate until after the drivers were told they would be made responsible for part of any accident damage to their vehicles (amounting to an increase in Utility Factor 4 above).

"Spontaneous" that is unintended effects on the target level of risk may also occur. Periods of economic recession and increased unemployment lead to a drop in Utility Factor 1 and an increase in Factor 2 and show substantial reductions in the accident rate. It goes up when the economy is flourishing.

The same mechanism also explains that the introduction of incentives for accident-free operation (increase in Factor 3) leads to substantial improvements in safety, as has been demonstrated in many companies and in many countries. The promise of a reward for being safe contribute to a positive anticipation of the future and thus to greater caution with life and limb by the population ("expectationism").