1. David Segal, “Mugged by a Mug Shot Online,” The New York Times,2013,

  2. Barry Schwartz, “Google Launches Fix to Stop Mugshot Sites FromRanking: Google’s MugShot Algorithm,” Search Engine Land, 2013,

  3. Lawrence Lessig, “Code is Law,” Harvard Magazine, 2000,

  4. Batya Friedman and Helen Nissenbaum, “Bias in Computer Systems.,” ACMTransactions on Information Systems, no. 3 (2005).

  5. “Algorithm,” Merriam Webster,

  6. Peter J Denning, “Computing is a Natural Science,” Communications of theACM (CACM), no. 7 (2007).

  7. Michael Flowers, “Beyond Open Data: The Data-Driven City,” BeyondTransparency: Open Data and the Future of Civic Innovation, 2013,

  8. Walter Perry and Brian McInnis, Predictive Policing: The Role of CrimeForecasting in Law Enforcement Operations (, 2013),

  9. Joseph Walker, “State Parole Boards Use Software to Decide Which Inmatesto Release,” Wall Street Journal, 2013,

  10. Anil Kalhan, “Immigration Policing and Federalism Through the Lens ofTechnology, Surveillance, and Privacy,” Ohio State Law Journal (2013).

  11. Sharon Otterman, “Court Says Teacher Rankings Should Be Public,” TheNew York Times, 2011,

  12. “How ContentID Works,”

  13. Andy Baio, “Copyright Kings Are Judge, Jury, and Executioner on YouTube,”Wired, 2012,

  14. Felicitas Kraemer, Kees van Overveld, and Martin Peterson, “Is there anethics of algorithms?” Ethics and Information Technology, no. (3) (2011).

  15. IBM White Paper, “Outsmarting the Social Services Fraudster,” 2013.

<<<<<<< HEAD

16. Eli Pariser, The Filter Bubble: How the New Personalized Web Is ChangingWhat We Read and How We Think (Penguin Press, 2011).Tow Center for Digital Journalism

  1. Eli Pariser, The Filter Bubble: How the New Personalized Web Is ChangingWhat We Read and How We Think (Penguin Press, 2011).


  2. Li Hui and Megha Rajagopalan, “At Sina Weibo’s censorship hub, China’sLittle Brothers cleanse online chatter,” Reuters, 2013,

  3. Archon Fung, Mary Graham, and David Weil, Full Disclosure: The Perilsand Promise of Transparency (Cambridge University Press, 2009).

  1. “42 USC 2000ee3-Federal agency data mining reporting,”

  2. Office of the Director of National Intelligence, “2012 Data Mining Report,”

  3. Frank Pasquale, “Restoring Transparency to Automated Authority,” Journalon Telecommunications & High Technology Law, no. (235) (2011).

  4. “Goodhart’ss Law,”’s_law.

  5. Eldad Eilam, Reversing: Secrets of Reverse Engineering (Wiley, 2005).

  6. Elliot Chikofsky, “Reverse engineering and design recovery: a taxonomy,”IEEE Software, no. 1 (1990).

  7. Ramandeep Singh, “A Review of Reverse Engineering Theories and Tools,”International Journal of Engineering Science Invention, no. 1 (2013).

  8. Nicholas Diakopoulos, “Sex, Violence, and Autocomplete Algorithms,” Slate,2013,

  9. Michael Keller, “The Apple ‘Kill List’: What Your iPhone Doesn’t WantYou to Type,” The Daily Beast, 2013,

  10. Jeff Larson and Al Shaw, “Message Machine: Reverse Engineering the 2012Campaign,” ProPublica, 2012,

  11. Jennifer Valentino-DeVries, Jeremy Singer-Vine, and Ashkan Soltani, “Web-sites Vary Prices, Deals Based on Users’ Information,” Wall Street Journal, 2012,

  12. Jeremy Singer-Vine, Ashkan Soltani, and Jennifer Valentino-DeVries, “Howthe Journal Tested Prices and Deals Online,” Wall Street Journal, 2012,

  13. Aniko Hannak et al., “Measuring Personalization of Web Search,” 2013,

  14. Susan Pulliam and Rob Barry, “Executives’ Good Luck in Trading OwnStock,” Wall Street Journal, 2012,

  15. Latanya Sweeney, “Discrimination in Online Ad Delivery,” Communicationsof the ACM, no. (5) (2013).

  16. Mukherjee and Arjun et al., “What Yelp Fake Review Filter Might Be Do-ing?” 2013.

  17. Ken Shirriff, “How Hacker News Ranking Really Works: Scoring, Controversy, and Penalties,” righto(blog), 2013,

  18. Saikat Guha, Bin Cheng, and Paul Francis, “Challenges in Measuring OnlineAdvertising Systems,” 2010,

  19. Paul Baker and Amanda Potts, “Why do white people have thin lips?Google and the perpetuation of stereotypes via auto-complete search forms,”Critical Discourse Studies, no. (2) (2013).

  20. Paul Rosenbloom, On Computing: The Fourth Great Scientific Domain.(MIT Press, 2013).

  21. Nicholas Diakopoulos, “Algorithmic Defamation: The Case of the ShamelessAutocomplete,” Tow Center for Digital Journalism, 2013,


  23. Eilam, Reversing: Secrets of Reverse Engineering.

  24. Helen Nissenbaum, “From Preemption to Circumvention: If Technology Reg-ulates, Why Do We Need Regulation (and Vice Versa)?” Berkeley Technology LawJournal, no. (3) (2011).

  25. “18 USC 1030-Fraud and related activity in connection with computers,”

  26. Peter Ludlow, “Hacktivists as Gadflies,” The New York Times, 2013,

  27. Fung, Graham, and Weil, Full Disclosure: The Perils and Promise of Trans-parency.

  28. Kelly McBride and Tom Rosenstiel, The New Ethics of Journalism: Princi-ples for the 21st Century (CQ Press, 2013).

  29. Tim O’Reilly, “Open Data and Algorithmic Regulation,” Beyond Trans-parency: Open Data and the Future of Civic Innovation, 2013,

  30. Danielle Keats Citron, “Technological Due Process,” Washington UniversityLaw Review (2007

results matching ""

    No results matching ""