Catalog Description
Instructor Description
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 collect data, make data-driven decisions, and design 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 respponsible AI, to provide a holistic view of broader data ecosystems and infrastructures.
Prerequisites
Graduate standing.
Scheduled and Upcoming Classes for this Course
Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
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INF 385T: Special Topics in Information Science: Responsible Data Management
Hanlin Li |
Spring Term 2025 |
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Past Classes for this Course
Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
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INF 385T: Special Topics in Information Science: Responsible Data Management
Hanlin Li Syllabus |
Spring Term 2024 |
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