Less-is-more effects in knowledge-based heuristic inference

Beaman, C. P. ORCID: https://orcid.org/0000-0001-5124-242X, Smith, P. and McCloy, R. ORCID: https://orcid.org/0000-0003-2333-9640 (2010) Less-is-more effects in knowledge-based heuristic inference. In: CogSci 2010 - 32nd Annual Conference of the Cognitive Science Society, August 11th - 14th 2010, Portland, Oregon, USA, pp. 1014-1019.

Abstract/Summary

Inference on the basis of recognition alone is assumed to occur prior to accessing further information (Pachur & Hertwig, 2006). A counterintuitive result of this is the “less-is-more” effect: a drop in the accuracy with which choices are made as to which of two or more items scores highest on a given criterion as more items are learned (Frosch, Beaman & McCloy, 2007; Goldstein & Gigerenzer, 2002). In this paper, we show that less-is-more effects are not unique to recognition-based inference but can also be observed with a knowledge-based strategy provided two assumptions, limited information and differential access, are met. The LINDA model which embodies these assumptions is presented. Analysis of the less-is-more effects predicted by LINDA and by recognition-driven inference shows that these occur for similar reasons and casts doubt upon the “special” nature of recognition-based inference. Suggestions are made for empirical tests to compare knowledge-based and recognition-based less-is-more effects