Data c104 / History c184d: Human Contexts and Ethics of Data
Why this course?
Data-driven services and artificial intelligence-powered devices now shape innumerable aspects of our lives. Beneath the surface of these technologies, computational and increasingly autonomous techniques that operate on large, ever-evolving datasets are revolutionizing how people act in and know the world. These new tools, systems, and infrastructures have profound consequences for how we think of ourselves, relate to one another, organize collective life, and envision desirable futures.
This course teaches you to use the tools of applied historical thinking and Science, Technology, and Society (STS) to recognize, analyze, and shape the human contexts and ethics of data. It prepares you to engage as a knowledgeable, skillful, and responsible citizen and professional in the varied arenas of our datafied world. You will learn to address:
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How does data science transform how people live and how societies function?
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How do cultures and values inform how data-driven tools are developed and deployed?
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What assumptions do data-enabled algorithms and tools carry with them?
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What projections does AI make on the future?
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How can we shape the outcomes we want to see?
If you intend to major in Data Science, the course meets the Human Contexts and Ethics requirement of Berkeley’s Data Science major. It gives you systematic exposure and reflective practice in the human choices and social structures that intrinsically shape your work.
If you don’t intend to major in Data Science, the course will jumpstart your knowledge and strengthen your capacity to take part in guiding our datafied world. The course carries the broad, inclusive spirit of Berkeley’s Data Science curriculum into the area of human society and collective choices.
Fall 2020, MWF 3 - 4pm, plus sections / On-line, with synchronous and asynchronous components
Instructors: Margo Boenig-Liptsin, Ari Edmundson
1.1 Welcome and Overview: University Education in a World of Data
(Margo Boenig-Liptsin & Ari Edmundson)
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S. Jasanoff, The Ethics of Invention: Technology and the Human Future (W.W. Norton and Company, Inc., 2016), Ch. 1 ("The Power of Technology(link is external)"), pp. 1-30. [Links to PDF in bCourses]
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K. Piper, "The UK used a formula to predict students' scores for canceled exams. Guess who did well(link is external)" Vox, August 22, 2020.
- S. Swauger, "Our Bodies Encoded: Algorithmic Test Proctoring in Higher Education(link is external)," Hybrid Pedagogy, April 2, 2020.
1.2 What makes the world datafied - STS analytical lenses
(Margo Boenig-Liptsin)
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L. Winner, "Do Artifacts Have Politics?(link is external)" Daedalus,109 (1): 121-136 (Winter 1980) [Links to PDF in bCourses]
Optional Reading:
- G.C. Bowker and S.L. Star, Sorting Things Out: Classification and Its Consequences (Cambridge, MA: MIT Press, 2000), Introduction: "To Classify is Human," pp. 1-13. [Links to PDF in bCourses]
1.3 Getting oriented in the datafied world -- Facial Recognition Technologies
(Ari Edmundson)
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R. Benjamin, Race After Technology: Abolitionist Tools for the New Jim Code (Polity, 2019), Ch. 3 “Coded Exposure,” pp. 67-94. [Links to PDF in bCourses]
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J. Buolamwini “The Coded Gaze”(link is external) YouTube, 2016, Video
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Take a few minutes to explore Buolomwini and Gebru's Gender Shades online project: http://gendershades.org/(link is external)
- L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Duke University Press, 2020) Introduction: Politics and Ethics in the Age of Algorithms,” pp. 15-18. [Links to PDF in bCourses]
Optional Reading:
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J. Buolamwini and T. Gebru “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification”(link is external)Proceedings of Machine Learning Research, 81, (2018): 1-15.
- X. Wu and X. Zhang, “Automated Inference on Criminality using Face Images”(link is external)Arxiv, November 21st, 2016.
1.4 Thinking-in-time about the datafied world I: Biometrics, physiognomy and scientific racism, 1880-1920
(Ari Edmundson)
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S. Chinoy, “The Racist History Behind Facial Recognition” (link is external)The New York Times, July 10, 2019
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S. Browne, Dark Matters: On the Surveillance of Blackness (Duke University Press, 2015), Chapter 3, “B®anding Blackness: Biometric Technology and the Surveillance of Blackness,” pp. 89-130.
Optional Reading:
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B. Aguera y Arcas et al. “Physiognomy’s New Clothes,”(link is external)Medium, May 20, 2017.
- J. Finn, Capturing the Criminal Image: From Mug Shot to Surveillance Society (University of Minnesota Press, 2009), “Picturing the Criminal: Photography and Criminality in the Nineteenth Century”, pp. 1-30. [Links to PDF in bCourses]
1.5 Thinking-in-time about the datafied world II: The Cold War, computing, and cybernetics, 1945-1965
(Ari Edmundson)
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P. Erickson et al. How Reason Lost its Mind (University of Chicago Press, 2013), Chapter 1, "Enlightenment Reason, Cold War Rationality, and the Rule of Rules," pp. 27-50. [Links to PDF in bCourses] [focus on pages 27-32]
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O. Halpern, Beautiful Data: A History of Vision and Reason Since 1945 (Duke University Press, 2014) [selections] Chapter 1, "Archiving: Temporality, Storage, and Interactivity in Cybernetics," pp. 39-48, 61-66, and Chapter 4, “Governing: Designing Information and Reconfiguring Population circa 1959” pp. 199-207.
Optional Reading:
- R. Kline, The Cybernetics Moment: Or, Why We Call Our Age the Information Age (Johns Hopkins University Press, 2015) Introduction, pp. 1-8. [Links to PDF in bCourses]
1.6 What makes data?
(Margo Boenig-Liptsin)
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G.C. Bowker and S.L. Star, Sorting Things Out: Classification and Its Consequences (Cambridge, MA: MIT Press, 2000), Ch. 6 ("The Case of Race Classification and Reclassification Under Apartheid(link is external)"), pp. 195-225. [Links to PDF in bCourses]
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M. Angrist, "Do You Belong to You?"(link is external) Genome, January 2, 2018.
1.7 Data futures -- perspectives from past and present
(Ari Edmundson)
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G. Orwell, 1984 (Harcourt, 2003 [1949]), pp.122-137(link is external) [Selections]. [Links to PDF in bCourses]
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V. Savov, "Google's Selfish Ledger is an unsettling vision of Silicon Valley social engineering(link is external)," The Verge, May 17, 2018. Please watch the video.
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M. Hildebrandt, Smart Technologies and the End(s) of Law: Novel Entanglements of Law and Technology (Elgar, 2015), "Introduction: Diana's OnLife World(link is external)" [selection], pp. 1-10. [Links to PDF in bCourses]
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Yuval Noah Harari, "'Homo sapiens is an obsolete algorithm': Yuval Noah Harari on how data could eat the world(link is external)," Wired, September 6, 2016
Optional Reading:
- S. Cave and K. Dihal, “The Whiteness of AI,” Philosophy & Technology (2020)
2.1 Ethics and professional practice
(Ari Edmundson)
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L. Stark and A.L. Hoffmann, “Data Is the New What? Popular Metaphors and Professional Ethics in Emerging Data Culture” Cultural Analytics, 1(1) 2019, pp. 1-22.
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Review the American Statistical Association (ASA)(link is external) and Association for Computing Machinery (ACM)(link is external) codes of ethics
Optional Readings:
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S. Barocas and d. boyd (2017) "Engaging the Ethics of Data Science in Practice(link is external)," Communications of the ACM, Vol. 60 No. 11, Pages 23-25.
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A. Saltelli et al. “Five Ways to Ensure Models Serve Society,”(link is external)Nature, June 24, 2020.
- K. Shilton, “Value levers: Building ethics into design(link is external),” Science, Technology, & Human Values 38(3) (2013): 374-397
2.2 Responsible institutions and challenges
(Margo Boenig-Liptsin)
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"The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research(link is external)" 1979. Read Sections "Ethical Principles and Guidelines for Research Involving Human Subjects," and "Part B: Basic Ethical Principles"
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M. Zook, S. Barocas, d. boyd, K. Crawford, E. Keller, S.P. Gangadharan, et al. (2017) "Ten simple rules for responsible big data research.(link is external)" PLoS Comput Biol 13(3).
Optional Readings:
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Look at some of the Articles of the General Data Protection Regulation(link is external)
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Matthias Spielkamp's presentation of Algorithm Watch's "Automating Society: Taking Stock of Automated Decision-Making in EU" Report in European Parliament, January 29, 2019. Video(link is external), 8:10 - 24:00.
2.3 Data ethics today -- what it is and how we got here
(Margo Boenig-Liptsin)
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Watch any 20 minutes of Mark Zuckerberg's testimony in the Senate(link is external) or in Congress(link is external). You can watch from the beginning or pick any 20 minutes.
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"'I made Steve Bannon's psychological warfare tool': meet the data war whistleblower(link is external)," The Guardian, March 18, 2018.
2.4 Aiming for the 'good life' with data
(Margo Boenig-Liptsin)
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C. Fleddermann. Engineering Ethics (4th Edition), (Prentice Hall, 2012), "Chapter 3: Understanding Ethical Problems(link is external)," [selection], pp. 37-49.
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W. Keane, Four Lectures on Ethics: Anthropological Perspectives, (HAU Books, 2015), "Lecture 3: Varieties of Ethical Stance(link is external)," Sections "Ethical Affordances," "Giving an Account of Oneself," "Ethical Reflexivity and Its Historical Objects," "Fist, Second, and Third-Person Stances," "Ethical Stances, Distant ant Committed"
Optional reading:
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P. Ricoeur, Oneself as Another (University of Chicago Press, 1994 [1990]), "Seventh Study: The Self and the Ethical Aim(link is external)," [selection], pp. 169-180.
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L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Duke University Press, 2020) Introduction: Politics and Ethics in the Age of Algorithms,” pp. 1-20.
2.5 Co-producing technical and social order
(Margo Boenig-Liptsin)
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M.C. Elish, "Moral Crumple Zones: Cautionary Tales in Human-Robot Interactions(link is external)," SSRN, April 3, 2016.
Optional reading:
- S. Jasanoff, The Ethics of Invention: Technology and the Human Future (W.W. Norton and Company, Inc., 2016), Ch. 2 ("Risk and Responsibility(link is external)"), pp. 31-58.
2.6 What is critique?
(Ari Edmundson)
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Flamethrowers and Fire Extinguishers – a review of “The Social Dilemma” (link is external)Librarian Shipwreck, September 17th, 2020.
Optional reading:
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L. Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Duke University Press, 2020) Ch. 5 “The Doubtful Algorithm: Ground Truth and Partial Accounts”, pp. 133-153. [Links to PDF in bCourses]
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R. Ochigame, “The Invention of Ethical AI: How Big Tech Manipulates Academia to Avoid Regulation(link is external),” The Intercept, December 20, 2019.
3.1 Personal origins of data
(Margo Boenig-Liptsin)
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J. Radin, "'Digital Natives': How Medical and Indigenous Histories Matter for Big Data(link is external)," OSIRIS 2017, 32: 43-64. [Links to PDF in bCourses]
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T. Hansen and J.Keeler, “The NIH Is Bypassing Tribal Sovereignty to Harvest Genetic Data From Native Americans”(link is external)Motherboard, Dec 21. 2018.
Optional Reading:
- Look at the National Institutes of Health (NIH) US Precision Medicine Initiative(link is external)
3.2 Selfhood in the age of data and social media
(Ari Edmundson)
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D. Haraway,The Donna Haraway Reader (Routledge, 2004)“A Manifesto for Cyborgs: Science, Technology, and Socialist Feminism in the 1980’s” pp. 7-13. [Links to PDF in bCourses]
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C. Koopman, How We Became Our Data: A Genealogy of the Information Person (University of Chicago Press, 2019) Introduction, “Informational Persons and Our Information Politics,” pp. 1-8. [Links to PDF in bCourses]
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G. Wolf, in D. Nafus, Ed., (Cambridge, MA: MIT Press, 2016), Quantified: Biosensing Technologies in Everyday Life, Ch. 4 ("The Quantified Self: Reverse Engineering(link is external),") pp. 67-72. [Links to PDF in bCourses]
Optional Reading:
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S. Hong, Technologies of Speculation: The Limits of Knowledge in a Data-Driven Society (NYU Press, 2020) Chapter 4, “Data’s Intimacy,” pp. 76-113.
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K. McCurdy, “When Data Renders Invisible Illnesses Visible,”(link is external)Medium, July 21, 2020.
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S. Turkle (2012) "Connected, but alone?(link is external)" TedTalk.
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Dan Bouk, “The History and Political Economy of Personal Data over the Last Two Centuries in Three Acts” Osiris 32 (1), 85-106
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John Cheney-Lippold, We Are Data: Algorithms and the making of our digital selves (NYU Press, 2017). Selection
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Rogers Brubaker, “Digital Hyperconnectivity and the Self,” Theory and Society (2020)
3.3 Privacy
(pre-recorded lecture: Richmond Wong's lecture from Spring 2020 + optional live discussion during regular lecture time)
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Timothy Ivory Carpenter, Petitioner v. United States(link is external), Opinion of the Court, pp. 1-23. [Links to PDF in bCourses]
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C. Dwork and DK. Mulligan (2013) "It’s not privacy, and it’s not fair.(link is external)" Stanford Law Review Online 66: 35–40.
Optional Reading:
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Daniel J. Solove, Understanding Privacy, ch. 1, “Privacy: A concept in disarray(link is external),” pp. 1-8. [Links to PDF in bCourses]
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S. Igo, “Me an d My Data,” Historical Studies in the Natural Sciences 4(5) November 2018: 616-626
3.4 Analytics of personal data
(Margo Boenig-Liptsin)
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Kate Crawford, “The Trouble with Bias(link is external)”, NIPS conference keynote, December 2017 (especially minutes 14:00 - 38:00)
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Read about the rights of "data subjects" under the GDPR, "My Rights(link is external)" European Commission, especially, "What are my rights?(link is external)" and "Can I be subjected to automated individual decision-making, including profiling?(link is external)"
Optional reading:
- Nikolas Rose, Inventing Our Selves: Psychology, Power, and Personhood. "Introduction."
4.1 Populations and states
(Ari Edmundson)
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James C. Scott, Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed (New Haven, CT: Yale University Press, 1998), [selections] Ch. 1 ("Nature and Space") and Ch. 3 ("Authoritarian High Modernism") pp. 22-33, 87-102(link is external)
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Michelle Murphy, The Economization of Life (Duke University Press, 2017) Chapter One, “Economy as Atmosphere,” pp. 17-34.
4.2 Surveillance and security
(Ari Edmundson)
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"NSA Whistleblower Edward Snowden: 'I don’t want to live in a society that does these sorts of things(link is external),'" The Guardian, June 9, 2013.
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J. Lanchester, “Document Number Nine,”(link is external)London Review of Books, October 10, 2019
4.3 Predictive policing
(Ari Edmundson)
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V. Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin’s Press, 2017) Chapter 4,“The Allegheny Algorithm,” pp. 127-173.
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C. Haskins, “Dozens of Cities Have Secretly Experimented With Predictive Policing Software,”(link is external)Motherboard February 6, 2019.
Optional Reading:
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K. Lum, "Understanding the Context and Consequences of Pre-trial detention(link is external)," ACM FAT Conference, 2018, Video: min 0:00 - 9:00
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R. Lemov, “An Episode in the History of PreCrime(link is external),” Historical Studies in the Natural Sciences 48(5), 637-647
4.4 Making arguments with data
(Ari Edmundson)
- T. Porter, Trust in Numbers: The Pursuit of Objectivity in Science and Public Life (Princeton University Press, 1995) Chapter 4, "The Political Philosophy of Quantification(link is external)," pp. 73-86.
4.5 Choice, influence, manipulation, and governance
(Ari Edmundson)
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Michael Wintroub, “Sordid genealogies: a conjectural history of Cambridge Analytica’s eugenic roots” Humanities and Social Sciences Communications 7(1), 1-16.
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OR Marion Fourcade and Fleur Johns, “Loops, ladders and links: the recursivity of social and machine learning,” Theory and Society (2020).
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Kramer et al. “Experimental evidence of massive-scale emotional contagion through social networks”(link is external)PNAS June 17, 2014 111 (24) pp. 8788-8790.
Optional Readings:
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O. Halpern et al. “The Smartness Mandate: Notes toward a Critique” Grey Room 68 (2017), pp. 106-129. [Links to PDF in bCourses]
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Julie Cohen, "The Regulatory State in the Information Age(link is external),” Theoretical Inquiries in Law, 17, 2 (2016).
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Max Read, "Does Facebook Need a Constitution?(link is external)" NYMag, July 18, 2018.
4.6 Algorithmic sentencing
(Margo Boenig-Liptsin)
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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(link is external)," ProPublica, May 23, 2016.
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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(link is external)," Monkey Cage, The Washington Post, October 17, 2016.
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Jupyter notebook and data for ProPublica story(link is external), GitHub
5.1 Commercial content moderation and the election
(Ari Edmundson)
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TBD
Optional Readings:
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S. E. Garcia, “Ex-Content Moderator Sues Facebook, Saying Violent Images Caused Her PTSD,”(link is external)New York Times, September 25, 2018.
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T. Gillespie, Custodians of the Internet: Platforms, Content Moderation, and the Hidden Decisions that Shape Social Media (New Haven: Yale University Press, 2018) Ch. 6,“Facebook, Breastfeeding, and Living in Suspension,” pp. 141-172(link is external)
5.2 Elections
(Ari Edmundson)
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F. Turner, “Machine Politics: The Rise of the Internet and a New Age of Authoritarianism”(link is external)Harper’s, January, 2019. [PDF in bCourses]
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Ian Bogost and Alexis Madrigal, “How Facebook works for Trump,”(link is external)The Atlantic, April 18th, 2020.
5.3 The Public sphere in the datafied world
(Ari Edmundson)
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Z. Tufekci, Twitter and Tear Gas: The Power and Fragility of Networked Protest (Yale University Press, 2017) Chapter 1, “A Networked Public”(link is external) pp. 3-27 [Links to PDF in bCourses]
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d. boyd, "You Think You Want Media Literacy: Do You?(link is external)" Medium, March 9, 2018.
5.4 Expertise and democracy
(Ari Edmundson)
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S. Epstein, Impure Science: Aids, Activism, and the Politics of Knowledge (University of California Press, 1996) Introduction, "Controversy, Credibility, and the Public Character of AIDS Research" pp. 1-26. [Links to PDF in bCourses]
Optional Readings:
- S. Jasanoff, Science and Public Reason, "Judgment under Siege: The Three Body Problem of Expert Legitimacy,"(link is external) pp. 150-166.
5.5 Data, algorithms, and the law
(Margo Boenig-Liptsin)
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S. Jasanoff, “In a Constitutional Moment: Science and Social Order at the Millennium(link is external),” in B. Joerges and H. Nowotny, eds., Social Studies of Science and Technology: Looking Back, Ahead, (Dordrecht: Kluwer, 2003), pp. 155-180.
Optional Readings:
- S. Barocas and A. Selbst, “Big Data’s Disparate Impact(link is external),” 104 California Law Review 671 (2016). Especially section I. How Data Mining Discriminates and the Conclusion.
5.6 Public witnessing and measuring
(Margo Boenig-Liptsin)
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Look at The Guardian's "The Counted"(link is external) database and read about the project(link is external)
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Look at the website of the San Francisco Anti-Eviction Mapping Project(link is external).
5.7 Election debrief
(Ari Edmundson & Margo Boenig-Liptsin)
6.1 Transformations in the foundations of science
(Cathryn Carson and Fernando Perez)
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C. Titus Brown, “What is open science?(link is external)” Living in an ivory basement: Stochastic thoughts on science, testing, and programming, 24 Oct 2016.(link is external)
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"Jim Gray on eScience: A transformed scientific method(link is external)," ed. Tony Hey, Stewart Tansley, and Kristin Tolle, in The Fourth Paradigm: Data-Intensive Scientific Discovery (Redmond, WA: Microsoft Research, 2009).
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Michael Jordan, “Artificial intelligence -- The revolution hasn’t happened yet(link is external),” Medium, April 18, 2018.
6.2 Transformations in the disciplines
(Panel - TBD)
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Bin Yu and Karl Kumbier, “Three principles of data science: predictability, computability, and stability (PCS)(link is external),” preprint, 2019.
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J. Kitzes, D. Turek, & F. Deniz (Eds.). The Practice of Reproducible Research(link is external): Case Studies and Lessons from the Data-Intensive Sciences. (Oakland, CA: University of California Press, 2018) [Selections]. Read Front Matter, Preface, and Introduction, plus at least one other section or case study of your choice.
Optional Readings:
- E. Lazowska, “How to encourage data-driven discovery(link is external),” Chronicle of Higher Education, March 4, 2018.
7.1 Making Silicon Valley
(Cathryn Carson)
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"Historical Tour of Silicon Valley(link is external)" in pictures, by Piero Scaruffi
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L. Vinsel and A. Russel, "Hail the maintainers(link is external)," Aeon, April 7, 2016.
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E. Ullman, "Gender Binary(link is external)," Harper's Magazine, July 2017.
Optional Readings:
- S. Frenkel et al., “Delay, Deny, and Deflect: How Facebook’s Leaders Fought through Crisis(link is external),” New York Times, 14 November 2018.
7.2 Industrial revolutions
(Ari Edmundson)
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Steven Weber and Richmond Y. Wong, “The new world of data: Four provocations on the Internet of Things(link is external),” First Monday, February 6, 2017.
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M. Fourcade and K. Healy, “Seeing Like a Market,” Socioeconomic Review 15 (1), 2016.
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N. Kulwin, “Shoshana Zuboff Talks Surveillance Capitalism’s Threat to Democracy,”(link is external) NY Magazine, Feb. 22, 2019
Optional Readings:
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S. Zuboff, “Big Other: Surveillance Capitalism and the Prospects for an Information Civilization(link is external),” Journal of Information Technology 30 (2015): 75-89 [Links to PDF in bCourses]
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Duncan McCann and Miranda Hall, “Blocking the Data Stalkers(link is external),” New Economic Foundation, December 28, 2018.
7.3 Environmental Contexts and Consequences of Data
(Margo Boenig-Liptsin)
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Zero Cool, "Oil is the New Data(link is external)," Logic (9). December 7, 2019.
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N. Ensmenger, "The Environmental History of Computing(link is external)," Technology and Culture (59). October 2018. Pp. S7-S33.
7.4 Transformations of labor
(Ari Edmundson)
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C. Maiers. "Predictive data and I experiential knowledge in the neonatal intensive care unit(link is external)," Work in Progress, July 6, 2017.
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M. McClelland. "I Was a Warehouse Wage Slave.(link is external)" Mother Jones, 2012.
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L. Hyman, "It's Not Technology That's Disrupting Our Jobs(link is external)," The New York Times, August 18, 2018.[PDF in bCourses here(link is external)]
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S. Kessler, “Companies Are Using Employee Survey Data to Predict — and Squash — Union Organizing”(link is external)Medium, July 30, 2020.
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Target's Delivery App Workers to Be Paid by a Blackbox Algorithm Nationwide(link is external) (9/11/2020)
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Sareeta Amrute, “Of techno-ethics and techno-affects” Feminist Review 123, 56-73
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Lily Irani, “Justice for Data Janitors”(link is external) Public Books, January 15th, 2015.
8.1 The tech workplace
(Ari Edmundson)
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A. Wiener, "Uncanny Valley(link is external)," n+1, Issue 25: Slow Burn, Spring 2016. [Also on bCourses(link is external)]
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Claire Stapleton et al., “We’re the Organizers of the Google Walk Out. Here are Our Demands,(link is external)” The Cut, 1 November 2018.
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“After 20,000 workers walked out, Google said it got the message. The workers disagree(link is external),” Recode, 21 November 2018.
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“Community Defense: Sarah T. Hamid on Abolishing Carceral Technologies” (link is external)Logic Magazine, Issue 11 Care, 2020.
8.2 Making worlds together
(Margo Boenig-Liptsin)
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E. Ullman, Life In Code: A Personal History of Technology (Farrar, Straus and Giroux, 2017) "Boom Two: A Farewell,(link is external)" pp. 272-303. [Links to PDF in bCourses]
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H. Arendt, The Human Condition, (University of Chicago Press, 1958) “Prologue,” pp. 1-6.
8.3 Recap: STS analytical lenses and thinking in time
(Margo Boenig-Liptsin & Ari Edmundson)
UC Berkeley students can access full syllabus and course materials on bCourses(link is external).