In the late 1960s and early 1970s, a series of papers by Amos Tversky and Daniel Kahneman revolutionized academic research on human judgement. The central idea of the "heuristics and biases" program - that judgement undeer uncertainty often rests on a limited number of simplifying heuristics rather than extensive algorithmic processing - soon spread beyond academic psychology, affecting theory and research across a rance of disciplines including economics, law, medicine, and political science. The message was revolutionary in that it simultaneously questioned the descriptive adequacy of ideal models of judgement and offered a cognitive alternative that explained human error without invoking motivated irrationality. The initial papers and a variety of related work were collected in a 1982 volume, Judgment under Uncertainty: Heuristics and Biases (Kahneman, Slovic, & Tversky, 1982). In the time since, research in the heuristics and biases tradition has prospered on a number of fronts, each represented by a section of the current volume. In this opening chapter, we wish to put the heuristics and biases approach in historical context and discuss some key issues that have been raised since the 1982 book appeared.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education