Human Factors in AI Systems is a research group dedicated to understanding how artificial intelligence shapes human thinking, emotions, decisions, and social interactions. The group, lead by Dr. Magdalena Wischnewski, investigates how people perceive, evaluate, trust, and engage with AI systems, with a particular focus on human-centered trustworthy AI.

Our research examines topics such as trust calibration, trust assessments, cognitive and social attributions toward AI, and the auditing of AI systems through mechanisms such as AI seals of trust. A central goal is to better understand when trust in AI systems is appropriate, how AI influences human behavior and decision-making, and how trustworthy AI systems can be designed and governed in ways that meaningfully support people.

By combining perspectives from psychology, computer science, and human–computer interaction, the group takes an interdisciplinary approach to the societal and cognitive dimensions of AI. As a psychology-driven research group, we primarily rely on quantitative and empirical methods, with a strong focus on experimental research designs to investigate human responses to AI in controlled and real-world contexts.

Beyond analyzing current challenges, the group aims to develop frameworks and practical recommendations for the human-centered development, evaluation, and deployment of AI systems. Our work contributes to a broader understanding of trustworthy technology by placing human experience, perception, and social behavior at the center of AI research.