The SocialAI School: Insights from Developmental Psychology Towards Artificial Socio-Cultural Agents
This work aims to engage the AI community in studying social intelligence for creating agents that can enter and benefit from human culture, but it is incremental as it builds on existing psychological theories without presenting new SOTA results.
The paper tackles the problem of developing artificial socio-cultural agents by proposing that AI research should be informed by developmental psychology, specifically theories from Michael Tomasello and Jerome Bruner, and introduces The SocialAI school as a tool with customizable environments to simplify experiments with RL agents and Large Language Models.
Developmental psychologists have long-established the importance of socio-cognitive abilities in human intelligence. These abilities enable us to enter, participate and benefit from human culture. AI research on social interactive agents mostly concerns the emergence of culture in a multi-agent setting (often without a strong grounding in developmental psychology). We argue that AI research should be informed by psychology and study socio-cognitive abilities enabling to enter a culture too. We discuss the theories of Michael Tomasello and Jerome Bruner to introduce some of their concepts to AI and outline key concepts and socio-cognitive abilities. We present The SocialAI school - a tool including a customizable parameterized uite of procedurally generated environments, which simplifies conducting experiments regarding those concepts. We show examples of such experiments with RL agents and Large Language Models. The main motivation of this work is to engage the AI community around the problem of social intelligence informed by developmental psychology, and to provide a tool to simplify first steps in this direction. Refer to the project website for code and additional information: https://sites.google.com/view/socialai-school.