Data and Ethics in Society

Description: Seminar, four hours; discussion, one hour. Exploration of moral, social, political, and ethical ramifications of choices we make at different stages in social construction of data. Includes cultivating critical analysis of processes of data collection, data mining, data storage, and deployment of data affected by variety of different communities, publics, nation-states, and individuals. Students learn basics of ethical and socially just frameworks to assess range of data-driven projects and platforms. Students gain understanding of social, historical, and political dilemmas of big data, algorithmic decision-making, predictive analytics, and distinct challenges associated with ethical, civil-, human-, and sovereign-rights models of engaging modern digital information era. Letter grading.

Units: 0.0
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Overall Rating 5.0
Easiness 4.0/ 5
Clarity 4.0/ 5
Workload 4.0/ 5
Helpfulness 5.0/ 5
Most Helpful Review
Winter 2021 - I'm surprised no one has any reviews on Professor Noble yet — she's actually a legend. Not only is she well-established in her field, seminar formats & smaller class sizes mean you really get to "walk among giants," so to speak. INFO 118 is capped to about 30 people, and that means the class has a lot of group discussion, deep dives, and opportunities for Prof. Noble to speak about her work and that of her colleagues. Despite the remote format, I think the structure of her Zooms worked well to re-create that seminar feel, and Professor Noble is actually one of the nicest and most responsive professors I've met. INFO 118 is a Data Ethics course, but it also focuses on Tech Ethics, tech's role as an ICT, and also features concepts from sociology and critical theory. There's a lot of reading, mostly papers, podcasts, and the occasional film, but it's manageable, and the grading is very fair. Winter 2021 was actually the first time the course met — and I think the mix of upperclassmen from many disciplines and grad students created an interesting mix of lived experiences that really made this class unique. If you are a stats/CS/math of comp/etc. major, PLEASE take this course if you're considering a DS or CS career. I took it coming from a stats background, and it was definitely far from "home," but was such a good exposure to the personal and societal ramifications of some career choices I had considered. Criticizing Big Tech certainly isn't new, and is gaining steam — but this was eye-opening in a totally different way.
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