Abstract
Alexandra Kirsch proposed a general formal model of decision making. She proposed it as a model both of human psychology and of artificial intelligence. As one might expect, and as Don Ross explicated, this is a challenging, albeit fascinating, position to occupy. In this comment, I sketch my own view of the bind and speculate on how to get out of it. In one sentence, my description of the bind is: How to build models for the wild? By models, I mean formal (mathematical, computer-based, precise conceptual) models, and by the wild, I mean “large worlds,” which are situations where uncertainty cannot be meaningfully reduced to well-developed devices such as probability. I discuss solutions for getting out of the bind proposed in the cognitive science of decision making. And I discuss how another discipline, operations research, has attempted to get out of the bind.
Highlights
Models for the wild in cognitive science?. In his comment on Kirsch’s article, Ross delineates the methodologies of psychology and economics in studying decision making: Psychology is meant to study the actual heuristics used by people, whereas economics is meant to start from the idea that human behavior is optimal and builds formal models of optimization problems and derive their solutions
Kirsch (2019) proposed a general formal model of decision making and Ross (2019) pointed out that her endeavor, and its reception by us reviewers, showed that cognitive modeling is in a bind
The bind is: How to build models for the wild? Models are formal constructions, and the wild is situations where uncertainty cannot be reduced to probability
Summary
Alexandra Kirsch (2019) proposed a general formal model of decision making. She proposed it as a model both of human psychology and of artificial intelligence (AI). A brief summary of the comment is provided in "Summary" section In his comment on Kirsch’s article, Ross delineates the methodologies of psychology and economics in studying decision making: Psychology is meant to study the actual heuristics used by people (as produced by natural selection and social pressures), whereas economics (neoclassical, behavioral; see Katsikopoulos 2014) is meant to start from the idea that human behavior is optimal and builds formal models of optimization problems and derive their solutions. Operations research models might be more human than those developed in the human sciences, because they need to be used by humans While such models could lack the precise specification of underlying processes that cognitive science should strive for, they might constitute good starting points for building cognitive models for the wild
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