Structuring decision problems and the ‘bias heuristic’

Abstract

This paper examines our understanding of the decomposition of immediate acts when structuring decision problems. Seven different types of uncertainties are identified, and four of these are shown to be taken explicitly into account in models within the province of decision theory, described in terms of four interlocking systems interfaced with semantic memory (a core act-event system, and systems buffering utilities, probabilities and events, respectively). Requisite decision modeling is shown to require that the remaining three types of uncertainty (procedural uncertainty; how the decision maker will feel about subsequent acts; agency for changing subsequent states of the world) are also resolved. Methods for 'fixing' structure are discussed in terms of aiming at a common understanding about the 'small world' in which a decision problem is located. Difficulties in resolving uncertainties in doing this are described. An alternative approach, common in studies invoking 'behavioural decision theory' is contrasted: imposing structure, assuming common understanding. The latter approach is shown to involve (i) the 'naturalisation' of the small world in which the decision problem is located, and (ii) the utilisation of normative models as 'ideal types', leading to the use of the 'bias' argument in discussing subjects' performance in decision tasks. Using this argument reflexively, the operation of the 'bias heuristic' is identified in a survey of published papers referencing this approach to the study of decision making. Effects identified are: availability of tasks, subjects and explanations; representativeness of findings; and anchoring and adjustment of explanations. Implications for practice are discussed throughout the paper.