CAREER: SocioCulturally Competent Agents to Study and Improve Human-AI interaction

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).

Artificial Intelligence (AI) systems have become ubiquitous in society; people constantly interact and cooperate with AI systems to accomplish tasks. Whether it is interacting with an AI agent in an online virtual environment or deciding where to eat next with the help of a virtual assistant, AI systems are increasingly integrated into our everyday lives. With such wide-spread deployment, understanding how a person's context affects their interaction with AI systems is vital to designing and developing competent and ethical AI systems. AI systems should be able to interact as appropriately with someone who is stressed or has been marginalized by societal structures as well as it does with someone free of stress or has not been subject to socio-cultural structures that systematically marginalize them. This research will advance the understanding of how one can create AI systems that can adapt to differences in people (and the social structures that might mediate these differences), while also advancing the understanding of how a person's context affects the way they perceive and cooperate with an AI system. The research in this project is complemented with multiple educational thrusts, including a plan to develop a pre-orientation program that targets incoming first year undergraduates from traditionally marginalized groups. The program will help undergraduate students be critically reflective how their own context affects the way they might design, develop, and implement AI systems.

The goal of this work is to develop a process-based multilevel computational theory that describes how human socio-cultural knowledge can positively affect the design, development, and interaction with AI agents. The project aims to understand how one can develop competent AI agents that can account for differing socio-cultural perspectives and their effects. Products of this work include an extended computational cognitive architecture and new cognitive AI agents that will be useful for the development of other AI systems. These products will also be useful for general computational models that simulate human behavior. The project will result in a computational model of interactions between physiological, affective, and cognitive systems that modulate human behavior, as well as an account for socio-cultural knowledge that affords certain uses of these systems and processes during human-AI interaction. The computational model will connect areas related to human behavior and AI on several time scales to make the modeling, simulation, and study of human-AI interaction more tractable. In concert with the computational models and tools, the investigator will conduct studies that provide a deeper understanding of how socio-cultural perspectives and knowledge affects and is used by people while cooperating with AI agents during tasks. Results from these studies will inform the computational model. The work will result in a deeper qualitative and quantitative and under-standing of the processes and knowledge that mediate human-AI interaction, the development of more competent AI agents, and open-source computational tools to continue to expand upon this understanding.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.