Trustworthy AI for Mental and Behavioral Health

Artificial intelligence is increasingly being used to provide information, support, and guidance in mental and behavioral health settings. However, inaccurate or misleading responses can have serious consequences when people rely on AI during moments of vulnerability. This project explores whether teams of AI agents can work together to improve the accuracy, reliability, and safety of communication, helping build AI systems that users can trust in high-stakes situations.

Building Trust in Autonomous Systems

As autonomous technologies become more common in transportation, aerospace, and other complex environments, understanding when and why they should be trusted becomes increasingly important. This project investigates how trustworthiness can be defined, measured, and evaluated in AI-enabled autonomous systems. Initial research focuses on autonomous engineered systems inspired by challenges encountered in crewed space operations.

Defining Trustworthy AI

Trustworthy AI means different things to different communities, disciplines, and institutions. This project brings together researchers from law, computer science, the social sciences, and the humanities to examine how concepts such as trust, fairness, accountability, and justice are understood and applied. The goal is to develop a stronger foundation for evaluating AI systems and ensuring they serve the needs of diverse communities.

Humanistic Approaches to Understanding AI

The future of AI should be shaped not only by technical experts but also by the communities it affects. This project uses Digital Humanities approaches to explore how storytelling, ethics, culture, and lived experience can inform the design and governance of trustworthy AI. Through workshops and community engagement activities, participants examine issues of AI literacy, accountability, fairness, access, and responsible implementation.