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Special Topics in Technology Studies: Big Data: Critical Perspectives
MCC-GE 3150
Thursdays 2:00-4:50 PM
Spring 2016
Helen Nissenbaum, Department of Media, Culture, and Communication


As a cultural phenomenon, Big Data has not been around for very long. If one cares to attach a date, one might follow the New York Times columnist, Stephen Lohr, who called 2012 its breakout year, "as an idea." Data Science, arguably, its disciplinary counterpart has inspired countless departments, programs, institutes, and centers at major universities in North America and elsewhere in the world. Big Data, in the meantime, has assumed the force of an epistemological paradigm, a policy driver, and an investment rationale; it even has an ethics. While boosters are declaring this to be the "data age," a "revolution" in modes of knowing and production skeptics and social critics are questioning overblown claims to newness and point out the threats to justice, equality, freedom, autonomy, privacy, and more, associated with practices, assumptions, and applications of big data, particularly as relates to human subjects. The seminar will examine Big Data from several perspectives - societal, ethical, political, and humanistic. Because the field is not mature (and may, in fact, never mature into a coherent line of inquiry) readings are assembled from a range of literatures, from media reports and trade publications (in the genre of "hype" and booster-ism) to law and policy and philosophical, ethical, and political analysis. The seminar will also cover some basic technical readings (and expert guests) because many of the compelling questions emerge from specific technical capabilities, for example, algorithms, machine learning, sensor networks, and predictive analytics. Further, because many controversial issues associated with Big Data had emerged decades earlier in relation to information technologies and digital media, critical readings from those literatures will also be included. Further selections will be added as I pursue leads and settle on productive areas of focus.

Learning Methodology

My role as instructor is to stake out a landscape of readings, topics, issues, and questions. We will, however, learn together and the expectation is that students will be active in defining areas of particular interests to them. In other words, the seminar is designed for students who are independently motivated to explore the area and willing to engage actively in preparing for sessions and contributing to discussion.


Each student will design a project and term paper in consultation with me. The expectation is that students will select an issue of particular interest and conduct research into it with an eye to a normative recommendation for ethics, policy, or technology design. Given the newness of the area, the hope is for papers that might be worked into conference submissions. Milestones will be set throughout the semester to ensure timely completion of the various phases of project and write-up.


Participation: 20%
Term paper (including successful completion of milestones): 80%

Seminar Topics

General: Promise and Peril

Technology: Data Science; Databases; Machine Learning; Statistics; Data collection and construction

Issues: Data: making, taking, finding, selecting, massaging, cleaning, objective; Epistemology: Data as knowledge objectivity, bias, evidence-based; Algorithms: automation, decision-making, opacity/transparency, accountability, governance, due process; manipulation, autonomy; Social Justice: fairness, unfairness, discrimination, bias; Autonomy: filter bubble, personalization; Privacy: surveillance, use versus collection, contextual integrity

Applications: Online tracking; behavioral/targeted advertising; price discrimination; Human subject research online; Internet of Things; Predictive policing; National security: data/metadata; Financial sector: credit score, mortgage rates, insurance, fraud; Development

Seminar Bibliography (organized by course theme)

I. General: Great Promise or Dark Peril

Anderson, Chris. "The End of Theory: The Data Deluge Makes the Scientific Method Obsolete." WIRED, June 23, 2008.

Bryant, Randal E., Katz, Randy H., and Edward D. Lazowska. "Big-Data Computing: Creating Revolutionary Breakthroughs in Commerce, Science, and Society." Computing Community Consortium, December 22, 2008.

Brynjolfsson, Erik and Andrew McAfee. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York, London: W.W. Norton & Company, 2014.

Cukier, Kenneth Neil and Viktor Mayer-Schoenberger. "The Rise of Big Data: How It's Changing the Way We Think About the World." Foreign Affairs 92, no. 3 (May/June 2013): 28-40.

Davenport, T.H. and D.J. Patil. "Data Scientist: The Sexiest Job of the 21st Century." Harvard Business Review 90, no. 10 (October 2012): 70-76.

Howard, Philip N. Pax Technica: How the Internet of Things May Set Us Free Or Lock Us Up. New Haven: Yale University Press, 2015.

Lohr, Steve. "The Origins of 'Big Data': An Etymological Detective Story." New York Times, February 1, 2013. Accessed December 28, 2015. http://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/?_r=0.

Lohr, Steve. "How Big Data Became So Big." New York Times, August 11, 2012. Accessed December 28, 2015. http://www.nytimes.com/2012/08/12/business/how-big-data-became-so-big-unboxed.html?_r=0.

Silver, Nate. The Signal and the Noise: Why So Many Predictions Fail - But Some Don't. New York: Penguin Books, 2012.

Strauss, Stefan. "Datafication and the Seductive Power of Uncertainty - A Critical Exploration of Big Data Enthusiasm." Information 6, no. 4 (2015): 836-847.

White House. "Big Data: Seizing Opportunities, Preserving Values." Executive Office of the President (May 2014): 1-79. https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_may_1_2014.pdf.

World Economic Forum. "Big Data, Big Impact: New Possibilities for International Development." World Economic Forum, 2012. Accessed December 28, 2015. http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf.

II. Technology

a. Data mining, Databases, Data, Statistics, Machine learning, Algorithms

Bowker, Geoffrey C. "The Theory/Data Thing." International Journal of Communication 8 (2014): 1795-1799.

Burrell, Jenna. "How the Machine 'Thinks': Understanding Opacity in Machine Learning Algorithms." SSRN Draft, revised September 30, 2015.

Dean, Jeffrey and Sanjay Ghemawat. "MapReduce: Simplified Data Processing on Large Clusters." Communications of the ACM 51, no. 1 (January 2008): 107-113.

Gitelman, Lisa. "Raw Data" is an Oxymoron (Infrastructures). Boston: The MIT Press, 2013. (Selections.)

Hand, David. "Classifier Technology and the Illusion of Progress." Statistical Science 21, no. 1 (February 2006): 1-14.

Kitchin, Rob. The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. London, Thousand Oaks, New Delhi, Singapore: Sage Publications, 2014 (chapters 1-6).

Provost, Foster and Tom Fawcett. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. Sebastopol: O'Reilly Media, 2013.

Schutt, Rachel and Cathy O'Neill. Doing Data Science: Straight Talk from the Frontline. Sebastopol: O'Reilly Media, 2014.

III. Issues

a. Privacy

Barocas, Solon and Helen Nissenbaum. "Big Data's End Run Around Anonymity and Consent." In Privacy, Big Data and the Public Good: Frameworks for Engagement. J. Lane, V. Stodden, S. Bender, and H. Nissenbaum (Eds.) Cambridge: Cambridge University Press, 2015.

Beckett, Lois. "Everything We Know About What Data Brokers Know About You." ProPublica, June 13, 2014. Accessed January 1, 2016. https://www.propublica.org/article/everything-we-know-about-what-data-brokers-know-about-you.

Harvard Law Review's Note. "Privacy and Efficient Government: Proposal for a National Data Center." Harvard Law Review 82, no. 2 (1968): 400-417.

Horvitz, Eric and Deirdre Mulligan. "Data, Privacy, and the Greater Good." Science 349, no. 6245 (July 17, 2015): 253-255.

Kosinski, Michal, Stillwell, David and Thore Graepel. "Private Traits and Attributes are Predictable from Digital Records of Human Behavior." Proceedings of the National Academy of Sciences 110, no. 15 (April 9, 2013): 5802-5805.

Narayanan, Arvind and Vitaly Shmatikov. "Privacy and Security: Myths and Fallacies of 'Personally Identifiable Information'." Viewpoints 53, no. 6: 24-26.

Nissenbaum, Helen. Privacy in Context: Technology, Policy, and the Integrity of Social Life. Stanford: Stanford University Press, 2010.

Ohm, Paul. "Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization." UCLA Law Review 57 (2010): 1701-1777.

Rubinstein, Ira. "Big Data: The End of Privacy or a New Beginning." International Data Privacy Law 3, no. 2 (2013): 74-87.

Yakowitz, Jane. "Tragedy of the Data Commons." Harvard Journal of Law and Technology 25, no. 1 (Fall 2011): 1-67.

b. Accountability, Transparency and Due Process

Citron, Danielle K. and Frank Pasquale. "The Scored Society: Due Process for Automated Predictions." Washington Law Review 89, no. 1: 1-34.

Crawford, Kate and Jason Schultz. "Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harms." Boston College Law Review 55 (2014): 93-128.

Federal Trade Commission. "Data Brokers: A Call for Transparency and Accountability." Federal Trade Commission, May 2014. Accessed January 1, 2016. https://www.ftc.gov/system/files/documents/reports/data-brokers-call-transparency-accountability-report-federal-trade-commission-may-2014/140527databrokerreport.pdf.

Hildebrandt, Mireille and Katja de Vries. Privacy, Due Process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology. London: Routledge, 2015. (Chapters 2,6,8,9)

Zarsky, Tal. "The Trouble with Algorithmic Decisions: An Analytic Road Map to Examine Efficiency and Fairness in Automated and Opaque Decision Making." Science, Technology and Human Values 41, no. 1 (2016): 118-132.

c. Social Justice

Barocas, Solon and Andrew D. Selbst. "Big Data's Disparate Impact." California Law Review 104 (forthcoming).

boyd, danah and Kate Crawford. "Critical Questions for Big Data: Provocations for a Cultural, Technological and Scholarly Phenomenon." Information, Communication and Society 15, no. 5 (2012): 662-679.

Crawford, Kate. "The Hidden Biases of Big Data." Harvard Business Review, April 1, 2013. Accessed February 26, 2016. https://hbr.org/2013/04/the-hidden-biases-inbig-data/.

Federal Trade Commission. "Big Data: A Tool for Inclusion or Exclusion?" Federal Trade Commission, January 2016. Accessed January 7, 2016. https://www.ftc.gov/system/files/documents/reports/big-data-tool-inclusion-or-exclusion-understanding-issues/160106big-data-rpt.pdf.

Hardt, Moritz. "How Big Data Is Unfair: Understanding Sources of Unfairness in Data-Driven Decision Making." Medium, September 26, 2014. Accessed February 26, 2016, https://medium.com/@mrtz/how-big-data-is-unfair-9aa544d739de.

Hardy, Quentin. "Big Data for the Poor." New York Times, July 5, 2012. Accessed January 5, 2016. http://bits.blogs.nytimes.com/2012/07/05/big-data-for-the-poor/.

Pasquale, Frank. The Black Box Society: The Secret Algorithms That Control Money and Information. Boston: Harvard University Press, 2015.

Robinson, David, Yu, Harlan and Aaron Rieke. "Civil Rights, Big Data and Our Algorithmic Future." Upturn, September 2014. Accessed February 2, 2016. https://bigdata.fairness.io/

Sweeney, Latanya. "Discrimination in Online Ad Delivery." Communications of the ACM 56, no. 5 (May 1, 2013): 44-54.

Zarsky, Tal Z. "Understanding Discrimination in the Scored Society." Washington Law Review 89, no. 4: 1375-1412.

d. Objectivity

Bowker, Geoffrey C. "The Theory/Data Thing." International Journal of Communication 8 (2014): 1795-1799.

IV. Applications

a. National Security and Policing

Amoore, Louise. "Data Derivatives: On the Emergence of a Security Risk Calculus for Our Times." Theory, Culture, and Society 28, no. 6: 2011.

Angwin, Julia, Larson, Jeff, Mattu, Surya and Lauren Kirchner. "Machine Bias: There's Software Used Across the Country to Predict Future Criminals. And it's Biased against Blacks." ProPublica, May 23, 2016. Accessed June 22, 2016. http://bits.blogs.nytimes.com/2012/07/05/big-data-for-the-poor/.

Angwin, Julia, Larson, Jeff, Mattu, Surya and Lauren Kirchner. "What Algorithmic Injustice Looks Like in Real Life." ProPublica, May 25, 2016. Accessed June 22, 2016. https://www.propublica.org/article/what-algorithmic-injustice-looks-like-in-real-life.

Graves, James T., Acquisti, Alessandro, and Nicholas Christin. "Big Data and Bad Data: On the Sensitivity of Security Policy to Imperfect Information." The University of Chicago Law Review 83, no. 1 (2016): 117-137.

Lynch, Jennifer. "How Private DNA Data Led Idaho Cops on a Wild Goose Chase and Linked an Innocent Man to a 20-year-old Murder Case." Electronic Frontier Foundation, May 1, 2015. Accessed January 1, 2016. https://www.eff.org/deeplinks/2015/05/how-private-dna-data-led-idaho-cops-wild-goose-chase-and-linked-innocent-man-20.

Perry, Walter L., McInnis, Brian, Price, Carter C., Smith, Susan C. and John S. Hollywood. "Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations." RAND Corporation, 2013. Accessed February 4, 2016. http://www.rand.org/content/dam/rand/pubs/research_reports/RR200/RR233/RAND_RR233.pdf

Scahill, Jeremy and Glenn Greenwald. "The NSA's Secret Role in the U.S. Assassination Program." The Intercept, February 10, 2014. Accessed June 22, 2016. https://theintercept.com/2014/02/10/the-nsas-secret-role/.

b. Advertising, Marketing, Sales

Clifford, Stephanie. "Shopper Alert: Price May Drop for You Alone." New York Times, August 9, 2012. Accessed January 5, 2016. http://bits.blogs.nytimes.com/2013/06/19/using-data-to-stage-manage-paths-to-the-prescription-counter/.

Couldry, Nick and Joseph Turow. "Advertising, Big Data and the Clearance of the Public Realm: Marketers' New Approaches to the Content Subsidy." International Journal of Communication 8 (2014): 1710-1726.

Duhigg, Charles. "How Companies Learn Your Secrets." New York Times, February 16, 2012. Accessed January 5, 2016. http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html.

Team, Trefis. "Here's Why Oracle Paid Over $1.2 Billion for Acquiring Datalogix." Forbes, February 20, 2015. Accessed January 1, 2016. http://www.forbes.com/sites/greatspeculations/2015/02/20/heres-why-oracle-paid-over-1-2-billion-for-acquiring-datalogix/.

Valentino-DeVries, Jennifer, Singer-Vine, Jeremy, and Ashkan Soltani. "Websites Vary Prices, Deals, Based on Users' Information." Wall Street Journal, December 24, 2012. Accessed February 26, 2016. http://www.wsj.com/articles/SB10001424127887323777204578189391813881534.

c. Profiles and Personalization

Anderson, CW. "Between Creative and Quantified Audiences: Web Metrics and Changing Patterns of Newswork in Local US Newsrooms." Journalism 12, no. 5 (2011): 550-566.

Clifford, Stephanie. "Using Data to Stage-Manage Paths to the Prescription Counter." New York Times, June 19, 2013. Accessed January 5, 2016. http://bits.blogs.nytimes.com/2013/06/19/using-data-to-stage-manage-paths-to-the-prescription-counter/.

Gillespie, Tarleton. "The Relevance of Algorithms." In Media Technologies: Essays on Communication, Materiality, and Society. Edited by Tarleton Gillespie, Pablo J. Boczkowsky, and Kirsten A. Foot. Cambridge: MIT Press, 2014.

Hildebrandt, Mireille and Katja de Vries. Privacy, Due Process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology. London: Routledge, 2015. Chapters 2, 6, 8, 9.

Hildebrandt, Mireille and Serge Gutwirth, eds. Profiling the European Citizen: Cross-Disciplinary Perspectives. Berlin, Heidelberg: Springer: 2008. Chapter 2, 6

Moretti, Franco. "Style, Inc. Reflections on Seven Thousand Titles (British Novels, 1740-1850)." Critical Inquiry 36, no. 1 (Autumn 2009): 134-158.

Ramsay, Stephen. Reading Machines: Toward an Algorithmic Criticism. Champaign: University of Illinois Press, 2011.

Schilperoort, Hannah M. "Feminist Markup and Meaningful Text Analysis in Digital Library Archives." Digital Commons at University of Nebraska, Lincoln, December 12, 2015. Accessed June 22, 2016. http://digitalcommons.unl.edu/libphilprac/1228/.

Trumpener, Katie. "I. Paratext and Genre System: A Response to Franco Moretti." Critical Inquiry 36, no. 1 (Autumn 2009): 159-171.

d. Digital Humanities

Gitelman, Lisa. "Raw Data" is an Oxymoron (Infrastructures). Boston: The MIT Press, 2013. (Selections.)

e. Health

Nafus, Dawn and Jamie Sherman. "This One Does Not Go Up To 11: The Quantified Self Movement as an Alternative Big Data Practice." International Journal of Communication 8 (2014): 1784-1794.

Terry, Nicholas P. "Big Data Proxies and Health Privacy Exceptionalism." Health Matrix: Journal of Law-Medicine 24, no. 1 (2014): 65-108.

Walker, Joseph. "Data Mining to Recruit Sick People." Wall Street Journal, December 17, 2013. Accessed January 5, 2016. http://www.wsj.com/articles/SB10001424052702303722104579240140554518458.

f. Smart Cities

Mulligan, D. K., Wang, L., and A. J. Burstein. "Privacy in the Smart Grid: An Information Flow Analysis." Report prepared by the UC Berkeley School of Information for the California Institute for Energy and Environment (CIEE), March 2011.

g. Open Data

Janssen, Marijn and Jeroen van den Hoven. "Big and Open Linked Data (BOLD) in Government: A Challenge to Transparency and Privacy?" Government Information Quarterly 32 (2015): 363-368.

h. My Data: Small Data, Quantified Self

Nafus, Dawn and Jamie Sherman. "This One Does Not Go Up To 11: The Quantified Self Movement as an Alternative Big Data Practice." International Journal of Communication 8 (2014): 1784-1794.

i. Workplace and Workforce

Barocas, Solon and Karen Levy. "Refractive Surveillance: New Data Ecologies in the Workplace." Talk at Theorizing the Web, April 15, 2016. Accessed June 22, 2016. http://livestream.com/internetsociety2/ttw16/videos/119699545.

Frey, Carl Benedikt and Michael A. Osborne. "The Future of Employment: How Susceptible are Jobs to Computerisation?" Oxford Martin School, September 17, 2013. Accessed June 22, 2016. http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf.

Hardy, Quentin. "Workday to Put Employees Through a Big Data Analysis." New York Times, November 5, 2014. Accessed January 5, 2016. http://bits.blogs.nytimes.com/2014/11/05/workday-to-put-employees-through-a-big-dataanalysis/.

Kantor, Jodi and David Streitfeld. "Inside Amazon: Wrestling Big Ideas in a Bruising Workplace." New York Times, August 15, 2015. Accessed June 22, 2016. http://nyti.ms/1TFqcOG.

Levy, Karen E. C. "The Contexts of Control: Information, Power, and Truck-Driving Work." Information Society 31, no. 2 (2015): 160-174.

Rosenblat, Alex and Luke Stark. "Uber's Drivers: Information Asymmetries and Control in Dynamic Work." Workshop Paper prepared for the Winter School "Labour in the on-demand economy" at the Centre for European Policy Studies (CEPS) in Brussels, Belgium November 23-25, 2015.

Scholz, Trebor. "Platform Cooperativism vs. the Sharing Economy." Medium, December 5, 2014. Accessed June 22, 2016. https://medium.com/@trebors/platform-cooperativism-vs-the-sharing-economy-2ea737f1b5ad#.z4duj89kw.

Silverman, Rachel Emma. "Bosses Harness Big Data to Predict Which Workers Might Get Sick; Wellness Firms Mine Personal Information, Seeking to Anticipate Employee Health Needs, Minimize Cost." Wall Street Journal, February 16, 2016. Accessed February 18, 2016. http://www.wsj.com/articles/bosses-harness-big-data-topredict-which-workers-might-get-sick-1455664940".

Walker, Joseph. "Meet the New Boss: Big Data." Wall Street Journal, September 20, 2012. Accessed January 5, 2016. http://www.wsj.com/articles/SB10000872396390443890304578006252019616768.

j. Development

Arora, Payal. "The Bottom of the Data Pyramid: Big Data and the Global South." International Journal of Communication 10 (2016): 1681-1699.

Hardy, Quentin. "Big Data for the Poor." New York Times, July 5, 2012. Accessed January 5, 2016. http://bits.blogs.nytimes.com/2012/07/05/big-data-for-the-poor/.

Hilbert, Martin. "Big Data for Development: A Review of Promises and Challenges." Development Policy Review 34, no. 1 (2016): 135-174.

Sojet, Andra Alarcon. "4 Questions for Internet.org as Internet for the Poor." ICTworks, May 8, 2015. Accessed June 22, 2016. http://www.ictworks.org/2015/05/08/4-questions-for-internet-org-as-internet-for-the-poor/.

US AID. "Development Data Library." US AID, last updated August 8, 2016. https://www.usaid.gov/data.

Vota, Wayan. "Be Honest: You Hate Free Basics Because it's Facebook." ICTworks, January 14, 2016. Accessed January 14, 2016. http://www.ictworks.org/2016/01/14/be-honest-you-hate-free-basics-because-its-facebook/.

Woodard, Josh. "How can We All Profit from Development Data?" ICTworks, March 18, 2015. Accessed June 22, 2016. http://www.ictworks.org/2015/03/18/how-can-we-all-profit-from-development-data/.

World Economic Forum. "Big Data, Big Impact: New Possibilities for International Development." World Economic Forum, 2012. Accessed December 28, 2015. http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf.

k. Other Relevant Readings

Apple. "A Message to Our Customers." Apple, February 16, 2016. Accessed October 24, 2016. http://www.apple.com/customer-letter/.

Arthur, Rob. "We Now Have Algorithms to Predict Police Misconduct: Will Police Departments Use Them?" FiveThirtyEight, March 9, 2016. Accessed October 24, 2016. http://fivethirtyeight.com/features/we-now-have-algorithms-to-predict-police-misconduct/.

Bass, Dina. "Clippy's Back: The Future of Microsoft is Chatbots." Bloomberg, March 30, 2016. Accessed October 24, 2016.

Calhoun, Adam J. "Punctuation in Novels." Medium, February 15, 2016. Accessed October 24, 2016. https://medium.com/@neuroecology/punctuation-in-novels-8f316d542ec4#.oxaqopkhe.

Cassano, Jay. "How Uber Profits Even While Its Drivers Aren't Earning Money." Motherboard, February 2, 2016. Accessed October 24, 2016. http://motherboard.vice.com/read/how-uber-profits-even-while-its-drivers-arent-earning-money.

DeFabio, Cara Rose. "This Artifical Intelligence Gives You the Best Emoji Tags for Your Photos." Fusion, February 3, 2016. Accessed October 24, 2016. http://fusion.net/story/263003/emojini/.

Eglash, Ruth. "Israeli Troops Relying on Waze App Blunder Into Palestinian Area; Clashes Follow." Washington Post, March 1, 2016. Accessed October 24, 2016. https://www.washingtonpost.com/world/middle_east/battles-erupts-after-israeli-soldiers-follow-apparent-gps-error-into-palestinian-zone/2016/03/01/940307ef-503f-4a98-8abb-01cf6357a850_story.html.

Frier, Sarah. "Facebook Wants You to Post More About Yourself." Bloomberg Technology, April 7, 2016. Accessed October 24, 2016. https://www.bloomberg.com/news/articles/2016-04-07/facebook-said-to-face-decline-in-people-posting-personal-content.

Ford, Matt. "Pleading for the Fourth." Atlantic, November 12, 2016. Accessed October 24, 2016. http://www.theatlantic.com/politics/archive/2015/11/justice-sotomayor-fourth-amendment/414948/.

Funnell, Antony. "Has Rampant Capitalism Hijacked the Promise of the Digital Age?" ABC, March 23, 2016. Accessed October 24, 2016. http://www.abc.net.au/radionational/programs/futuretense/has-rampant-capitalism-hijacked-the-promise-of-the-digital-age/7266210.

Goodfellow, Ian. "Deep Learning Adversarial Examples - Clarifying Misconceptions." KDnuggests, July 2015. Accessed October 24, 2016. http://www.kdnuggets.com/2015/07/deep-learning-adversarial-examples-misconceptions.html.

Kirn, Walter. "If You're Not Paranoid, You're Crazy.” Atlantic, November 2015. Accessed October 24, 2016. http://www.theatlantic.com/magazine/archive/2015/11/if-youre-not-paranoid-youre-crazy/407833/.

Kittler, Friedrich A. "The City is a Medium." In The Truth of the Technological World: Essays on the Genealogy of the Present, 138-151. Translated by Erik Butler. Stanford: Stanford University Press, 2013.

Kodjak, Alison. "A Fitbit Saved His Life? Well, Maybe." NPR, April 11, 2016. Accessed October 24, 2016. http://www.npr.org/sections/health-shots/2016/04/11/473393761/a-fitbit-saved-his-life-well-maybe.

Manning, Chelsea. "Why We Need to Support Apple's Battle Against the Feds." Advocate, February 22, 2016. Accessed October 24, 2016. http://www.advocate.com/commentary/2016/2/22/why-we-need-support-apples-battle-against-feds.

Paczkowski, John and Chris Geidner. "FBI Admits It Urged Change of Apple ID Password for Terrorist's iPhone." Buzzfeed, February 19, 2016. Accessed October 24, 2016. https://www.buzzfeed.com/johnpaczkowski/apple-terrorists-appleid-passcode-changed-in-government-cust?bftwnews&utm_term=.lgZ4nz9nW#.nk59Q1ZQR.

Pasquale, Frank. "How Fitness Trackers Make Leisure More Like Work." Atlantic, March 2, 2015. Accessed August 24, 2016. http://www.theatlantic.com/business/archive/2016/03/how-trackers-make-leisure-like-work/471864/.

Price, Rob. "Microsoft is Deleting its AI Chatbot's Incredibly Racist Tweets." Business Insider, March 24, 2016. Accessed October 24, 2016. http://www.businessinsider.com/microsoft-deletes-racist-genocidal-tweets-from-ai-chatbot-tay-2016-3.

Rosenberg, Matthew. "Osama bin Laden Feared Wife's Tooth Held a Tracking Device." New York Times, March 1, 2016. Accessed October 24, 2016. http://www.nytimes.com/2016/03/02/world/middleeast/osama-bin-laden-materials-declassified.html?_r=0.

Satell, Greg. "Is Digital Technology Making Us Any Better Off? One Prominent Economist Says No And He May Be Right." Forbes, March 13, 2016. Accessed October 24, 2016. http://www.forbes.com/sites/gregsatell/2016/03/13/is-digital-technology-making-us-any-better-off-one-prominent-economist-says-no-and-he-may-be-right/#5ad49ae12fa0.

Smith, Matthew Noah. "An iPhone is an Extension of the Mind." Slate, February 29, 2016. Accessed October 24, 2016. http://www.slate.com/articles/technology/technology/2016/02/apple_and_the_fbi_think_iphones_are_safes_a_philosopher_explains_what_they.html.

Timm, Trevor. "The Government Just Admitted It Will Use Smart Home Devices for Spying." Guardian, February 9, 2016. Accessed October 24, 2016. https://www.theguardian.com/commentisfree/2016/feb/09/internet-of-things-smart-devices-spying-surveillance-us-government?CMP=edit_2221.


1/28 Introduction
2/4 General: Promise and Peril I
2/11 General: Promise and Peril II
2/18 No class
2/25 Issue: Privacy
3/3 Technology: Data and Databases
Guest: Prof. Jinyang Li, Computer Science
3/10 Technology: Data Mining
Guests: Prof. Foster Provost, Stern & Data Science; Prof. Julia Lane, Wagner & CUSP
3/17 Spring Break
3/24 Issues: Social Justice I
3/31 Issues: Social Justice II
4/7 Technology: AI
Guest: Prof. David Sontag, Computer Science
4/14 Issues: Profiles and Personalization
4/21 Applications: Policing and National Security
4/28 Applications: Workplace and Workforce
5/5 Term Project Presentations

Last Updated: January 15, 2016
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