Predicting behavior from the world: Naïve behaviorism in lay decision theory

Samuel G. B. Johnson, Lance J. Rips

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

6 Citations (SciVal)

Abstract

Life in our social world depends on predicting and interpreting other people’s behavior. Do such inferences always require us to explicitly represent people’s mental states, or do we sometimes bypass such mentalistic inferences and rely instead on cues from the environment? We provide evidence for such behaviorist thinking by testing judgments about agents’ decision-making under uncertainty, comparing agents who were knowledgeable about the quality of each decision option to agents who were ignorant. Participants believed that even ignorant agents were most likely to choose optimally, both in explaining (Experiment 1) and in predicting behavior (Experiment 2), and assigned them greater responsibility when acting in an objectively optimal way (Experiment 3).
Original languageEnglish
Title of host publication36th Annual Meeting of the Cognitive Science Society
Subtitle of host publicationCognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts
Place of PublicationAustin, Texas, USA
PublisherCognitive Science Society
Pages695-700
ISBN (Print)9781634391160
Publication statusPublished - 2014
Event36th annual meeting of the Cognitive Science Society: Cognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts - Quebec City, Canada
Duration: 23 Jul 201426 Jul 2014

Conference

Conference36th annual meeting of the Cognitive Science Society
Abbreviated titleCogSci 2014
Country/TerritoryCanada
CityQuebec City
Period23/07/1426/07/14

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