Marewski,J.N.
Gaissmaier,W.
Gigerenzer,G.

In their comment on Marewski et al. (good judgments do not require complex cognition, 2009) Evans and Over (heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer, 2009) conjectured that heuristics can often lead to biases and are not error free. This is a most surprising critique. The computational models of heuristics we have tested allow for quantitative predictions of how many errors a given heuristic will make, and we and others have measured the amount of error by analysis, computer simulation, and experiment. This is clear progress over simply giving heuristics labels, such as availability, that do not allow for quantitative comparisons of errors. Evans and Over argue that the reason people rely on heuristics is the accuracy-effort trade-off. However, the comparison between heuristics and more effortful strategies, such as multiple regression, has shown that there are many situations in which a heuristic is more accurate with less effort. Finally, we do not see how the fast and frugal heuristics program could benefit from a dual-process framework unless the dual-process framework is made more precise. Instead, the dual-process framework could benefit if its two “black boxes” (Type 1 and Type 2 processes) were substituted by computational models of both heuristics and other processes.

Marewski, J. N., Gaissmaier, W., & Gigerenzer, G. (2010). We favor formal models of heuristics rather than lists of loose dichotomies: A reply to Evans and Over. Cognitive Processing, 11, 177-179. doi:10.1007/s10339-009-0340-5 (Full text)

Publication year	2010
Document type:	Article
Publication status:	Published
External URL:	http://library.mpib-berlin.mpg.de/ft/jm/JM_We_2010.pdf View
Categories:	Forecasting
Keywords: