Class Description

Fall 2020

INF 385T Special Topics in Information Science : Human-AI Interaction

Unique ID: 27204 Min Kyung Lee
3:00 pm - 6:00 pm Syllabus

DESCRIPTION

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.

PREREQUISITES

Graduate standing.

SCHEDULE NOTES

Synchronous class meetings conducted online.

RESTRICTIONS

Some seats reserved for graduate students in the School of Information