Causal schemas in judgments under uncertainty

This paper develops the thesis that the impact of evidence on intuitive judgements of probabilities depends critically on whether it is perceived as causal, diagnostic or incidental, and shows that people assign greater impact to causal data than to diagnostic data of equal informativeness.

Abstract

Many of the decisions we make, in trivial as well as in crucial matters, depend on the apparent likelihood of events such as the keeping of a promise, the success of an enterprise, or the response to an action. Since we generally do not have adequate formal models to compute the probabilities of such events, their assessment is necessarily subjective and intuitive. The manner in which people evaluate evidence to assess probabilities has aroused much research interest in recent years, e.g., W. Edwards (1968, 25); Kahneman and Tversky (1979a, 30); Slovic (1972a); Slovic, Fischhoff, and Lichtenstein (1977); Tversky and Kahneman (1974, 1). This research has identified several judgmental heuristics which are associated with characteristic errors and biases. The present paper is concerned with the role of causal reasoning in judgments under uncertainty and with some biases that are associated with this mode of thinking.