Hannah's work investigates how people detect limitations in AI and algorithmic systems, how they adapt their technology use in response, and what these adaptation patterns mean for building more effective sociotechnical systems.
Hannah Overbye-Thompson is a PhD Candidate in the Department of Communication at the University of California, Santa Barbara. Her research examines how biases in artificial intelligence shapes human behavior, perception, and technology adoption. Working at the intersection of media effects, human-computer interaction, and decision making, her current research spans three interconnected areas: (1) the diffusion of biased algorithms across groups, (2) human detection and response to algorithmic bias, and (3) the psychological and social mechanisms through which algorithmic systems perpetuate inequality. Collectively, these lines of research forward an understanding of how algorithmic bias operates as a sociotechnical phenomenon, revealing not just when and how bias occurs, but how individuals detect, workaround, and adapt to biased systems in ways that can either perpetuate or challenge existing inequalities.
B.S. (2019), University of Illinois Urbana-Champaign, Psychology, Communication
M.A. (2023), University of California, Santa Barbara, Communication
Advanced to Candidacy (2025), University of California, Santa Barbara, Communication