Prompting for Socially Intelligent Agents with ChatGPT

Ana Antunes, Joana Campos, Manuel Guimarães, João Dias, Pedro A. Santos

Abstract: Socially Intelligent Agents (SIAs) have become increasingly popular in various contexts, including education and entertainment. However, creating complex social scenarios tailored to a designer's specific goals remains a significant challenge. The authoring burden can be substantial, limiting the potential of SIAs to deliver rich, engaging experiences. In this work, we propose leveraging the extensive knowledge stored within Large Language Models and use theory-driven prompting to extract social practices and identify appropriate social affordances for a scenario description. Our prompting approach aims to guide the system into considering the essential components (beliefs and desires) necessary to produce intentions, actions, and emotions1. Results show that our approach produces large amounts of accurate and new information that can add value to the scenario. However, the process can introduce inaccuracies without human supervision.