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Are Bayesian Decisions Artificially Intelligent? The Effect of Task and Personality on Conservatism in Probabilistic Inference NICHD

Author(s):
Alker, Henry A.; Hermann, Margaret G.
Publication Year:
1970
Report Number:
RB-70-27
Source:
ETS Research Bulletin
Document Type:
Report
Page Count:
35
Subject/Key Words:
National Institute for Child Health and Human Development (NICHD), College Students, Decision Making, Males, Mathematical Models, Predictor Variables, Probability, Responses

Abstract

A 2 x 3 design was used to explore the effects of complexity and importance of decision on conservatism in probabilistic inference. 120 undergraduate males considered either two or three alternatives for one of three problems differing in perceived importance. Upon receiving certain information, subjects indicated which of the several alternative explanations for their problem was more or most probable. These probability statements were compared with "optimal" probabilities arrived at using Bayes' theorem. The more important and complex the decisions were perceived to be, the more conservative the subjects were when compared to "optimal" Bayesian values (p < .01). Seven individual difference variables measuring adequacy in processing information were unrelated to conservatism. A process analysis suggested that strongly held initial opinions can limit the judged relevance of subsequent information and, in turn, affect the "optimal" Bayesian decision.

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