INF 385T Special Topics in Information Science : Responsible Data Management
Explore common data collection, management, and sharing practices in information technology and emerging technologies. Students will examine the human, social, and ethical impact of these practices and work on group projects to design data systems that are centered around broader impact and social responsibilities.
This course will explore common data collection, management, and sharing practices in information technology and emerging technologies, such as search engines and AI systems. Students will read papers and engage in discussions about the pros and cons of established data practices and learn about the three main components of responsible data management: 1) consent and ownership, 2) privacy and anonymity, and 3) broader impact. Students will also practice how to design ethical data-driven products through group projects as UX designers, researchers, and data scientists. The course will bring in interdisciplinary perspectives with guest speakers from archive science, engineering, and responsible AI, to provide a holistic view of broader data ecosystems and infrastructures. Students will learn the pros and cons of different data collection, management, and sharing practices. Students will gain hands-on experience with designing data-driven products or systems as UX designers, researchers, and data scientists. Students will also be exposed to interdisciplinary research on important ethical considerations about data, e.g. privacy and consent.
Restricted to graduate students in the School of Information through registration periods 1 and 2. Outside students will be permitted to join our waitlists beginning with registration period 3.