| Unit 1: Making the Datafied World | Week 1: Foundations |
Wed
Aug 28 | 1. Making the Datafied World 1 | - Langdon Winnner, "Do Artifacts Have Politics," Daedalus
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Fri
Aug 30 | 2. Making the Datafied World 2 | - Donald MacKenzie and Judy Wajcman, “Introductory Essay,” The Social Shaping of Technology
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| Week 2: Making Data |
Mon
Sep 02 | 3. Labor Day - No Class | No Readings |
Wed
Sep 04 | 4. Making Data | - G.C. Bowker and S.L. Star, “To Classify is Human,” Sorting Things Out: Classification and Its Consequences
- Bay Area Air Quality Management District (BAAQMD)
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Fri
Sep 06 | 5. Making Personal Data | - Colin Koopman, “Informational Persons and Our Information Politics,” How We Became Our Data: A Genealogy of the Informational Person
- Ruha Benjamin, “Coded Exposure,” Race After Technology: Abolitionist Tools for the New Jim Code
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| Week 3: Making Knowledge |
Mon
Sep 09 | 6. Making Science | - Thomas Kuhn, “Introduction: A Role for History”, The Structure of Scientific Revolutions
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Wed
Sep 11 | 7. Making Objectivity with Numbers | - Theodore Porter, “Objectivity and Authority: How French Engineers Reduced Public Utility to Numbers," Poetics Today
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Fri
Sep 13 | 8. Making Decisions, Making Choices | No Readings |
| Week 4: Narratives about Human-Technology Futures |
Mon
Sep 16 | 9. Making Futures | - George Orwell, 1984
- Mireille Hildebrandt, “Introduction: Diana's OnLife World,” Smart Technologies and the End(s) of Law: Novel Entanglements of Law and Technology
- Vlad Savov, “Google's Selfish Ledger is an unsettling vision of Silicon Valley social engineering,” The Verge
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Wed
Sep 18 | 10. Making Cyborgs | - Laura Forlano and Danya Glabau, “Chapter Five: A Manifesto for Cyborgs,” Cyborg
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Fri
Sep 20 | 11. Making Value with Data - Data Capitalism | - Jathan Sadowski, “Chapter 2: A Universe of Data,” Too Smart: How Digital Capitalism is Extracting Data, Controlling Our Lives, and Taking Over the World
- Billy Perrigo, “OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic,” Time Magazine
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| Unit 2: Histories of the Datafied World | Week 5: States |
Mon
Sep 23 | 12. States and Populations | - James C. Scott, “Nature and Space,” Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed
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Wed
Sep 25 | 13. Eugenics and Statistics | - Aubrey Clayton, “How Eugenics Shaped Statistics,” Nautilus
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Fri
Sep 27 | 14. Global Data | - Andrew Brooks, “Why Are Certain Countries Poor? Dismantling Comparative Models of Development,” Bullshit Comparisons
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| Week 6: Capitalism |
Mon
Sep 30 | 15. Silicon Valley, Part 1 | - Lee Vinsel and Andrew Russel, “Hail the maintainers,” Aeon
- Eisenhower Speech
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Wed
Oct 02 | 16. Silicon Valley, Part 2 | - Leif Wenar, “The Deaths of Effective Altruism,” Wired
- John D. Skrenty, “The Precariousness of the STEM Job,” Wasted Education: How We Fail Our Graduates in Science, Technology, Engineering, and Math
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Fri
Oct 04 | 17. No Class | No Readings |
| Unit 3: Governance | Week 7: Surveillance and Privacy |
Mon
Oct 07 | 18. Surveillance and Security | - Michel Foucault, “Panopticism,” Discipline and Punish
- Gaby Del Valle, “The Most Surveilled Place in America,” The Verge
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Wed
Oct 09 | 19. Privacy Foundations | - Nathan Malkin, “Contextual Integrity, Explained: A More Usable Privacy Definition,” IEEE Security & Privacy
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Fri
Oct 11 | 20. Privacy in the World | - Joanna Radin, “Digital Natives: How Medical and Indigenous Histories Matter for Big Data,” Osiris
- Jen Caltrider et al, “It's Official: Cars Are the Worst Product Category We Have Ever Reviewed For Privacy,” Mozilla Foundation
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| Week 8: Governing with Algorithms |
Mon
Oct 14 | 21. Algorithmic Governance, Risk and Fairness Part 1: The Standard Narrative | - J. Angwin, J. Larson, S. Mattu, and L. Kirchner, “Machine Bias: There's software used across the country to predict future criminals. And it's biased against Blacks,” ProPublica
- A. Feller, E. Pierson, S. Corbett-Davies, and S. Goel, “A computer program used for bail and sentencing decisions was labeled biased against Blacks. It's actually not that clear,” Monkey Cage
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Wed
Oct 16 | 22. Algorithmic Governance, Risk and Fairness Part 2: A Sociotechnical Critique | - Virginia Eubanks, “The Allegheny Algorithm,” Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor
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Fri
Oct 18 | 23. Algorithmic Governance, Risk and Fairness Part 3: A Historical-Political Critique | - Os Keyes, et al. “A Mulching Proposal: Analysing and Improving an Algorithmic System for Turning the Elderly into High-Nutrient Slurry,” CHI
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| Week 9: Data From Above, Data From Below |
Mon
Oct 21 | 24. Creating things we can't unsee… Using Social & Data Science to Inform Policy on Eviction & Racial/Gender Equity | No Readings |
Wed
Oct 23 | 25. Global Health Data | - Sara L. M. Davis, “Contested Indicators,” The Uncounted: Politics of Data in Global Health
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Fri
Oct 25 | 26. Midterm Exam | No Readings |
| Unit 4: Industry, Capitalism, and Labor | Week 10: Industrial Revolutions, Automation, and Labor |
Mon
Oct 28 | 27. Labor in the Datafied World | - Louis Hyman, “It's Not Technology That's Disrupting Our Jobs,” The New York Times
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Wed
Oct 30 | 28. Automation and Labor | - Kate Crawford, “Labor,” Atlas of AI
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Fri
Nov 01 | 29. The Tech Workplace, Part 1 | - A. Wiener, “Uncanny Valley,” n+1
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| Week 11: Environmental Externalities and the Tech Workplace |
Mon
Nov 04 | 30. The Tech Workplace, Part 2 | - Alex Hanna, “On Racialized Tech Organizations and Complaint: A Goodbye to Google,” Medium
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Wed
Nov 06 | 31. Regulation | - Maxwell Zeff, “The lawmaker behind California’s vetoed AI bill, SB 1047, has harsh words for Silicon Valley,” Tech Crunch
- Cecilia Kang, “California Governor Vetoes Sweeping A.I.,” The New York Times
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Fri
Nov 08 | 32. Environmental Contexts and Consequences of Data | - Kate Crawford and Vladan Joler, “Anatomy of an AI System”
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| Unit 5: Sites of Data Ethics Today | Week 12: Ethics as Institutions |
Mon
Nov 11 | 33. No Class | No Readings |
Wed
Nov 13 | 34. Professional Ethical Codes | - Luke Munn, “The Uselessness of AI Ethics,” AI Ethics
- Langdon Winner, “Brandy, Cigars, and Human Values,” The Whale and the Reactor: A Search for Limits in an Age of High Technology
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Fri
Nov 15 | 35. Research Ethics - Checklists, Duties, and Routines | - UC Berkeley Committee for Protection of Human Subjects, “About CPHS/OPHS”
- UC Berkeley Committee for Protection of Human Subjects, “Guide to the IRB Review Process”
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| Week 13: Ethics as Philosophy, Ethics as World-Making |
Mon
Nov 18 | 36. Moral Philosophy | - Madeleine Clare Elish, “Moral Crumple Zones: Cautionary Tales in Human-Robot Interactions,” Engaging Science, Technology, and Society
- MIT Moral Machine
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Wed
Nov 20 | 37. AI Ethics | - Amia Srinivasan, “Stop the Robot Apocalypse,” London Review of Books
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Fri
Nov 22 | 38. Ethics as World-Making | - Feminist Data Manifest-No
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| Thanksgiving Break |
Mon
Nov 25 | 39. Thanksgiving Break, No Class | No Readings |
Wed
Nov 27 | 40. Thanksgiving Break, No Class | No Readings |
Fri
Nov 29 | 41. Thanksgiving Break, No Class | No Readings |
| Week 14: Ethics as Cultures of Data Practice |
Mon
Dec 02 | 42. Working in the Open | - Denisse Alejandra, “Reimagining Open Science Through a Feminist Lens,” Medium
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Wed
Dec 04 | 43. Making Robust Knowledge | No Readings |
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Fri
Dec 06 | |
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