University of Maryland

INST 801: Theoretical and Epistemological Foundations in Information Studies 

Credits: 3

Pursuing a doctorate in information studies involves the scholarly examination of the interaction between people, information, technology, and society. There are, however, as many ways to examine the interaction of people, information, technology, and society as there are researchers and ways of understanding what counts as evidence and knowledge in different components of the field. Students will be introduced to the diverse scholarly traditions that comprise information studies. Students will explore why there are so many ways of knowing and methods of discovery within the field, in order to help them identify the social theory and methods that will support their path through information scholarship.

INST 639T: Social and Psychological Impacts of AI 

Credits: 3

This HCI graduate course explores human-AI interaction from a social science perspective. We focus on understanding how humans perceive, interact with, and are influenced by AI systems, drawing on social scientific theories from psychology, communication, social computing, and beyond. In this course, we engage with a wide range of scholarly venues that reflect both the theoretical and applied dimensions of human-AI interaction. The course covers AI anthropomorphism, AI’s persuasive power, explainable AI, AI for information seeking, human-centered AI in health, AI and human confidence and creativity, AI aversion and overreliance, AI and misinformation, AI reasoning and biases, and AI for social scientific research. This class is best suited for students who are interested in 1) learning about the social science foundations and theory applications in HCI, or 2) conducting academic research studies in the field, or 3) translating academic research insights into practical AI design solutions and developing evidence-based design implications for human-AI interaction.