INF 385T - Special Topics in Information Science: Human-AI Interaction
Graduate standing. Additional prerequisites may vary with the topic.
Study of the properties and behavior of information. Technology for information processing and management.
Three lecture hours a week for one semester.
May be repeated for credit when the topics vary.
Advances in artificial intelligence (AI) have changed the way decisions are made in organizations, governments, and everyday life. This course will provide an introduction to combining human and machine intelligence to benefit people and society. Students will learn cutting-edge research on a number of topics related to human-AI interaction, including the psychological and societal impacts of AI, AI biases and fairness, transparency and explainability, mixed-initiative interaction, human-in-the-loop decision-making, embodied and natural language based AI, and design guidelines and methods for AI user experiences. These topics will be explored in the context of real-world applications, including online social media and labor platforms, algorithmic management tools for worker hiring and evaluation, and decision-support tools for public administrative decisions on risk assessment and resource distribution. Students will form interdisciplinary teams and learn through projects how to critically analyze existing AI systems, study their human impact, and design new systems to be human-centered.
Note: This course is about human-centric theories and methods for envisioning AI systems and will provide no technical insight on machine learning, data-mining, or statistical pattern recognition. Prior experience with programming, AI/machine learning, human-computer interaction or interaction design, or user research is not required but will be helpful. The methodological skills required for projects will be covered in the class.