Differences Between Human and Non-Human Primate Theory of Mind: Evidence from Computational Modeling

Abstract Can non-human primates (NHPs) represent other minds? Answering this question has been historically difficult because primates can fail experimental tasks due to a lack of motivation, or succeed through simpler mechanisms. Here we introduce a computational approach for comparative cognition that enables us to quantitatively test the explanatory power of competing accounts. We formalized a collection of theories of NHP social cognition with varying representational complexity and compared them against data from classical NHP studies, focusing on the ability to determine what others know based on what they see. Our results uncovered that, while the most human-like models of NHP social cognition make perfect qualitative predictions, they predict effect sizes that are too strong to be plausible. Instead, theories of intermediate representational complexity best explained the data. At the same time, we show that it is possible for human-like models to capture non-human primate behavior (NHP), as long as we assume that NHPs rely on these representations only about one third of the time. These results show that, in visual perspective taking tasks, NHPs likely draw upon simpler social representations than humans, either in terms of representational complexity, or in terms of use.