Thinking About, and Interacting with Living and Mechanical Agents

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Recent advances in artificial intelligence and robotics are confronting individuals of all ages with a series of category-defying entities that combine features of living and nonliving things. As such, these entities increasingly challenge people's basic understanding of mind and intelligence. The goal in this project is to explore adults' and children's beliefs about a range of living and mechanical agents, and to test how these beliefs affect people's ability to track, remember, and understand mechanical agents in two specific computer interfaces. First, it will explore a computer interface designed to allow a human operator to interact with and control a set of semi-autonomous robots. The second environment will be a teachable agent system in which middle school children learn about complex science phenomena, such as river ecosystems, by actively teaching an animated software agent.This project represents one of the few research programs to empirically test people's understanding of living and artificial agents, and it will employ a conceptual framework that starts with naïve understandings of mind (e.g. "Theory of Mind") and applies them to engineered environments where these understandings are used. This framework describes the conditions under which participants apply different agent concepts, and can help understand how these beliefs might change over time as people interact with novel agents. Although the framework is not yet a complete theory, it represents a broadened approach to reasoning about both typical and novel living and mechanical agents that goes beyond existing dual-process models of Theory of Mind. These experiments also make links between concepts about agents, and the deployment of these concepts in realistic high-load perceptual tasks, so they can make an important contribution to our basic understanding of how knowledge affects vision.The findings from this project may have important implications for educating both children and adults to deal with novel intelligent decision making technologies that move beyond the simple command-and-response cycle inherent to most current computer applications. Previous research by the PIs has already documented ways in which different people vary in their approach to these technologies (e.g. older and younger adults seem to have subtly different beliefs about the nature of computer intelligence), so this project may help improve the accessibility of novel agent-technologies to a wide range of different populations. More generally, because this research uses interactive educational tools and realistic robot-command systems to explore agent-understanding, it has the potential to improve user interfaces supporting social learning environments that focus on self-regulated learning, and that facilitate the effectiveness of human-machine emergency response teams. These technologies confront users with challenges to their most basic understandings of intelligence and thinking, and our research has the potential to guide both children and adults as they become successful users and creators of the interactive technologies of the future.