THE PSYCHOLOGY OF JUDGMENT AND DECISION MAKING

Excerpted From: Hastie, R. (2001). Problems for Judgment and Decision Making,
Annual Review of Psychology, 52, 653-683.

What is the field of judgment and decision making about?

The focus of research is on how people (and other organisms and machines) combine desires (utilities, personal values, goals, ends, etc) and beliefs (expectations, knowledge, means, etc) to choose a course of action. The conceptual (perhaps defining) template for a decision includes three components:

1. courses of action (choice options and alternatives);
2. beliefs about objective states, processes, and events in the world (including outcome states and means to achieve them); and
3. desires, values, or utilities that describe the consequences associated with the outcomes of each action-event combination.

Decision making and judgment are domains that need to be integrated with the psychology of reasoning and problem solving. One needs to know how to perform and how to evaluate possible courses of action in order to maximize the likelihood of success. (es)

Judgment

For judgment researchers, the central empirical questions concern the processes by which as-yet-obscure events, outcomes, and consequences could be inferred (or, speaking metaphorically, "perceived"): How do people integrate multiple, fallible, incomplete, and sometimes conflicting cues to infer what is happening in the external world?

Decision making

How do people choose what action to take to achieve labile, sometimes conflicting goals in an uncertain world? These models are often expressed axiomatically and algebraically, in the tradition established for measurement theories in physics and economics. Here the standards used to evaluate the quality of decisions usually involve comparisons between behavior and the prescriptions of rational, normative models, which often take the form of tests for the coherence of expectations, values, and preferences or the achievement of ideal optimal outcomes.

At the center of all these frameworks is a basic distinction between information about what the decision maker wants (often referred to as utilities) and what the decision maker believes is true about the situation (often called expectations). The heart of the theory, sometimes called the rational expectations principle, proposes that each alternative course of action or choice option should be evaluated by weighting its global expected satisfaction-dissatisfaction with the probabilities that the component consequences will occur and be experienced.

There are two important limits on the expected utility framework. First, it is incomplete. Many aspects of the decision process lie outside of its analysis. For example, the framework says nothing about how the decision situation is comprehended or constructed by the decision maker: Which courses of action are under consideration in the choice set? In addition, the theory says nothing about the sources of inputs into the decision process: What should the trade-off be between adaptive flexibility and the precise estimation of optimal choices by a realistic computational system (the human brain) in a representatively complex, nonstationary environment? Where does information about alternatives, consequences, and events come from in the first place, and how is it used to construct the representation on which the expected values/expected utilities are computed? Finally, how are personal values, utilities, and satisfactions inferred, predicted, and known?

The second limit on the expected utility framework is that it does not provide a valid description of the details of human decision-making processes. Today a myriad of qualifications is applied to the basic expected utility model when it is used to describe everyday decision-making behavior. As the saying goes, Compared to the assumptions of the rational model, people are boundedly rational and moderately selfish, and they exercise limited self-control (Jolls et al 1998).

However, even with its limitations, subjective expected utility has been the dominant conceptual framework for rational and empirical studies of decision making for the past 2 or 3 centuries. Therefore, many research problems concerning judgment and decision making are best conceptualized and stated in the context of this overarching theoretical framework. Furthermore, there is some sensible reason for most behaviors (Anderson 1990, March 1978, Newell 1982; see Oaksford & Chater 1998 for a sample of applications of rational models to cognitive achievements). Even when people appear to be making systematically biased judgments or irrational decisions, it is likely that they are trying to solve some problem or achieve some goal to the best of their abilities. The behavioral researcher is well advised to look carefully at his or her research participant's behavior, beliefs, and goals to discern "the method in the apparent madness" (Becker 1976, Miller & Cantor 1982).

Anderson JR. 1990. The Adaptive Character of Thought. Hillsdale, NJ: Erlbaum
Becker GS. 1976. The Economic Approach to Human Behavior. Chicago, IL: Univ. Chicago Press
Edwards W, ed. 1992. Utility Theories: Measurements and Applications. Boston, MA: Kluwer Acad.
Jolls C, Sunstein CR, Thaler R. 1998. A behavioral approach to law and economics. Stanford Law Rev. 50:1471-550
March JG. 1978. Bounded rationality, ambiguity, and the engineering of choice. Bell J. Econ. 9:587-608
Miller GA, Cantor N. 1982. Review of the book Human Inference: Strategies and Shortcomings of Social Judgment. Soc. Cogn. 1:83-93
Miyamoto JM. 1988. Generic utility theory: measurement foundations and applications. J. Math. Psychol. 32:357-404
Newell A. 1982. The knowledge level. Artif. Intel. 18:87-127
Oaksford M, Chater N, eds. 1998. Rational Models of Cognition. Oxford, UK: Oxford Univ. Press
Copyright © 2001 by Annual Reviews, Inc., Palo Alto, California, USA. All Rights Reserved.

Psychology Department, University of Colorado, Boulder, Colorado 80309-0345; 
e-mail: reid.hastie@colorado.edu
back to Induction