Week 9: Mar. 4, 2022
Machine Learning & AI
You’ll learn how ubiquitous machine learning is right now and consider just a few of the issues it raises for the information professions.
Read, view, and listen
- People’s Guide to Artificial Intelligence (pamphlet, 67 min.; it’s OK to skim)
- “Responsible Operations: Data Science, Machine Learning, and AI in Libraries” (32 min.)
- “Automating Inequality” (video, 29 min.)
Further reading
David Bamman, a professor of information studies at UC Berkeley, has published his syllabus for Deconstructing Data Science, a course that introduces students both to detailed understandings of statistical analysis and a consideration of ethical issues
In-class activities
- Slides: machine learning & bias
- Teachable Machine
- In-class assignment
- Colab notebook: Intro to machine learning
(A few) Organizations looking at bias in AI/ML
- Algorithmic Justice League
- Stop LAPD Spying
- ACM Conference on Fairness, Accountability, and Transparency (FAccT)
- Alliance for Public Interest Technology
- Past and upcoming workshops and events
- AI Now Institute at NYU
- Data & Society
- Oxford Internet Institute
- Algorithm Watch
- Center for Critical Internet Inquiry (C2I2) at UCLA