Designing and detecting lies by reasoning about other agents.

How do people detect lies from the content of messages, and design lies that go undetected? Lying requires strategic reasoning about how others think and respond. We propose a unified framework underlying lie design and detection, formalized as recursive social reasoning. Senders design lies by inferring the likelihood the receiver detects potential lies; receivers detect lies by inferring if and how the sender would lie. Under this framework, we can predict the rate and content of lies people produce, and which lies are detected. In Experiment 1, we show that people calibrate the extremeness of their lies and what lies they detect to beliefs about goals and the statistics of the world. In Experiment 2, we present stronger diagnostic evidence for the function of social reasoning in lying: people cater their lies to their audience, even when their audience's beliefs differ from their own. We conclude that recursive and rational social reasoning is a key cognitive process underlying how people communicate in adversarial settings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Integration by Parts: Collaboration and Topic Structure in the CogSci Community.

Is cognitive science interdisciplinary or multidisciplinary? We contribute to this debate by examining the authorship structure and topic similarity of contributions to the Cognitive Science Society from 2000 to 2019. Our analysis focuses on graph theoretic features of the co-authorship network-edge density, transitivity, and maximum subgraph size-as well as clustering within the space of scientific topics. We also combine structural and semantic information with an analysis of how authors choose their collaborators based on their interests and prior collaborations. We compare findings from CogSci to abstracts from the Vision Science Society over the same time frame and validate our approach by predicting new collaborations in the 2020 CogSci proceedings. Our results suggest that collaboration across authors and topics within cognitive science has become increasingly integrated in the last 19 years. More broadly, we argue that a formal quantitative approach which combines structural co-authorship information and semantic topic analysis provides inroads to questions about the level of interdisciplinary collaboration in a scientific community.