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).
|Title of host publication||36th Annual Meeting of the Cognitive Science Society|
|Subtitle of host publication||Cognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts|
|Place of Publication||Austin, Texas, USA|
|Publisher||Cognitive Science Society|
|Publication status||Published - 2014|
|Event||36th 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 2014 → 26 Jul 2014
|Conference||36th annual meeting of the Cognitive Science Society|
|Abbreviated title||CogSci 2014|
|Period||23/07/14 → 26/07/14|
Johnson, S. G. B., & Rips, L. J. (2014). Predicting behavior from the world: Naïve behaviorism in lay decision theory. In 36th Annual Meeting of the Cognitive Science Society: Cognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts (pp. 695-700). Cognitive Science Society.