When Machines Decide: The Promise and Peril of Living in a Data-Driven Society: Resource Materials

Honors 3700-002, Fall, 2016-Spring 2017 Thursdays 2:00 pm-5:00 pm MHC 1205

Weekly Resources


                  BIG DATA

The Human Face of Big Data,” PBS (February 25, 2016) available at https://www.youtube.com/watch?v=r6v15Z60eUI   (52 minutes in length)

 “What is Big Data and Why Should You Care? Forbes (April 22, 2016) available at https://www.youtube.com/watch?v=jGhRiwGHh30  (2:45 minutes in length)

“The Impact of Big Data on Business Efficiency,” insidebigdata.com (July 30, 2016) available at http://insidebigdata.com/2016/07/30/the-impact-of-big-data-on-business-efficiency/

Brian Naylor, “Firms Are Buying, Sharing Your Online Info. What Can You Do About It?” NPR (July 11, 2016) available at http://www.npr.org/sections/alltechconsidered/2016/07/11/485571291/firms-are-buying-sharing-your-online-info-what-can-you-do-about-it

“The Ethics of Data – Personal Data & Privacy” BBC Research & Development (March 16, 2016) available at https://www.youtube.com/watch?v=naaDBNSx610 (6:14 minutes in length)



Jennifer Golbeck, “How to Teach Yourself About Algorithms,” (February 9, 2016) Slate, available at  http://www.slate.com/articles/technology/future_tense/2016/02/how_to_teach_yourself_about_algorithms.html

Jacob Brogan, “What’s the Deal With Algorithms,” (February 2, 2016) Slate, available at http://www.slate.com/articles/technology/future_tense/2016/02/what_is_an_algorithm_an_explainer.html?wpsrc=sh_all_dt_tw_top

Suresh Venkat, “When An Algorithm Isn’t…,” October 2, 2015 available at  https://medium.com/@geomblog/when-an-algorithm-isn-t-2b9fe01b9bb5

Ed Finn, “Algorithms Aren’t Like Spock,” (February 22, 2016) Slate, available at http://www.slate.com/articles/technology/future_tense/2016/02/algorithms_are_like_kirk_not_spock.html

Jeff Hawkins & Donna Dubinsky, “What is Machine Intelligence vs. Machine Learning vs. Deep Learning vs. Artificial Intelligence?”, KD Nuggets (January 2016) available at http://www.kdnuggets.com/2016/01/what-is-machine-intelligence-ml-deep-learning-ai.html

Molly Galetto, “What is Big Data Analytics,” ngdata.com (July 5, 2016) available at http://www.ngdata.com/what-is-big-data-analytics/

Alex Hern, “Google says machine learning is the future so I tried it myself”, The Guardian (June 28, 2016). Available at https://www.theguardian.com/technology/2016/jun/28/google-says-machine-learning-is-the-future-so-i-tried-it-myself

Madeleine Clare Elish, “Algorithms Can Make Good Co-Workers,” (February 22, 2016) Slate, available at http://www.slate.com/articles/technology/future_tense/2016/02/algorithms_can_make_good_co_workers.html

Kenneth Cukier, “Big Data Dystopia,” Tedx Talks (April 14, 2014) available at https://www.youtube.com/watch?v=Z_HdhhzG-b0

“The Ethics of Data – Education & Self-management,” BBC Research & Development (March 16, 2016) available at https://www.youtube.com/watch?v=naaDBNSx610 (5:55 minutes in length)

David Ingold & Spencer Soper, “Amazon Doesn’t Consider the Race of its Customers. Should it,” Bloomberg News (April 21, 2016) available at http://www.bloomberg.com/graphics/2016-amazon-same-day/

Laura Sydell, “Can Computer Programs Be Racist & Sexist?” National Public Radio (March 15, 2016) available at http://www.npr.org/sections/alltechconsidered/2016/03/15/470422089/can-computer-programs-be-racist-and-sexist

Maciej Cegtowski, “Haunted By Data,”October 1, 2015   available at  http://idlewords.com/talks/haunted_by_data.htm

A Report on Algorithmic Systems, Opportunity and Civil Rights, Executive Office of the President (May 2016) available at https://www.whitehouse.gov/sites/default/files/microsites/ostp/2016_0504_data_discrimination.pdf



Sorelle A. Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, “On the (Im)possibility of Fairness,” (September, 2016) available at https://www.researchgate.net/researcher/13489648_Suresh_Venkatasubramanian

How big data is unfair. Moritz Hardt. Available at https://medium.com/@mrtz/how-big-data-is-unfair-9aa544d739de#.69j789w6z

Why Machines Discriminate---and How to Fix Them, Science Friday podcast (November 20, 2015) featuring Professor Venkat and Microsoft research Kate Crawford available at http://www.sciencefriday.com/segments/why-machines-discriminate-and-how-to-fix-them/

Hanna Wallach, “Big Data, Machine Learning and the Social Sciences: Fairness, Accountability and Transparency” (December 19, 2014) available at https://medium.com/@hannawallach/big-data-machine-learning-and-the-social-sciences-927a8e20460d

Taylor Owen, “The Violence of Algorithms: Why big data is only as smart as those who generate it.” (May 25, 2015) Foreign Affairs. Available at https://www.foreignaffairs.com/articles/2015-05-25/violence-algorithms

Jonathan Zittrain, “Automation and Algorithms in the Digital Age,” World Economic Forum, (February 24, 2015) available at https://www.youtube.com/watch?v=I6gD7Yq-_jk (6:03 minutes in length)

“Professor Sorelle Friedler on Discriminatory Machine Learning,” Data & Society Research Institute (November 30, 2015) available at https://www.youtube.com/watch?v=8qXCi41jNvs&list=PLRQQwX_klyfx_SVTC1tbDJt67wzoia2ET&index=9 (6:16 minutes)

Robyn Caplan & laura Reed, “Who Controls the Public Sphere in an Era of Algorithms: Case Studies,” Data & Society (May 16, 2016) available at http://www.datasociety.net/pubs/ap/CaseStudies_PublicSphere_2016.pdf

Code Dependent: Pros and Cons of the Algorithmic Age, Pew Research Center Report (February 8, 2017) available at http://www.pewinternet.org/2017/02/08/code-dependent-pros-and-cons-of-the-algorithm-age/

Will Knight, “The Dark Secret at the Heart of AI,” MIT Technology Review (April 11, 2017) available at https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/



“Big Data: A Tool for Inclusion or Exclusion?” Federal Trade Commission Report (January 2016) available at https://www.ftc.gov/system/files/documents/reports/big-data-tool-inclusion-or-exclusion-understanding-issues/160106big-data-rpt.pdf

Joshua A. Kroll, et al. “Accountable Algorithms,” Univ. of Penn. L. Rev., Vol 165, (2017 forthcoming) available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2765268

John k. Higgins, “FTC Issues Regulatory Warning on Big Data Use,” Ecommerce Times (January 20, 2016) available at http://www.ecommercetimes.com/story/83004.html

Nicholas Diakopoulos, “How to Hold Governments Accountable for the Algorithms They Use,” Slate.com (February 11, 2016) available at http://www.slate.com/articles/technology/future_tense/2016/02/how_to_hold_governments_accountable_for_their_algorithms.html    

Metcalf, Jacob, Emily F. Keller, and Danah Boyd, “Perspectives on Big Data, Ethics, and Society.” Council for Big Data, Ethics, and Society. (May 23, 2016)  http://bdes.datasociety.net/council-output/perspectives-on-big-data-ethics-and-society/.

Omer Tene & Jules Polonetsky, “Beyond IRB’s: Ethical Guidelines for Data Research,” Washington and Lee Law Review Online (June 7, 2016) available at http://scholarlycommons.law.wlu.edu/cgi/viewcontent.cgi?article=1044&context=wlulr-online

Julia Angwin, “Make Algorithms Accountable”, New York Times (August 1, 2016) available at http://www.nytimes.com/2016/08/01/opinion/make-algorithms-accountable.html

Joshua A. Kroll, Joanna Huey, Solon Barzas, Edward W. Felten, Joel R. Reidenberg, David G. Robinson & Harlan Yu, “Accountable Algorithms,” (March 31, 2016) available at http://balkin.blogspot.com/2016/03/accountable-algorithms.html

Cathy O’Neil, “The Ethical Data Scientist,” Slate (February 4, 2016) available at http://www.slate.com/articles/technology/future_tense/2016/02/how_to_bring_better_ethics_to_data_science.html



“How Predictive Policing Software Works,” The Verge (February 3, 2016) available at https://www.youtube.com/watch?v=YxvyeaL7NEM  (2:04 minutes)

Jason Tashea, “Websites and Apps for Sharing Crime and Safety Have Become Outlets for Racial Profiling,” ABA Journal (August 1, 2106) available at http://www.abajournal.com/magazine/article/crime_safety_website_racial_profiling/?utm_source=maestro&utm_medium=email&utm_campaign=tech_monthly

“Is Predictive Policing the Law-Enforcement Tactic of the Future?” Wall Street Journal (April 24, 2016) available at http://www.wsj.com/articles/is-predictive-policing-the-law-enforcement-tactic-of-the-future-1461550190

Hector Chaidez, “Interactive Predictive Policing Program in South Pasadena, California,” (July 25, 2016) available at https://www.youtube.com/watch?v=LqoFk0Y3XXg (11:26 minutes)

Thomas H. Davenport, “How Big Data is Helping the NYPD Solve Crimes Faster,” Fortune.com (July 17, 2016) available at http://fortune.com/2016/07/17/big-data-nypd-situational-awareness/

“Algorithms in the Criminal Justice System,” Electronic Privacy Information Center available at https://epic.org/algorithmic-transparency/crim-justice/

Julia Angwin, Jeff Larson, Surya Mattu, Lauren Kirchner, “Machine Bias,” ProPublica (May 23, 2016) available at https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing

Response to ProPublica article by developer of computer program available at https://www.documentcloud.org/documents/2998391-ProPublica-Commentary-Final-070616.html

ProPublica rejoinder to developer’s response available at https://www.propublica.org/article/propublica-responds-to-companys-critique-of-machine-bias-story

David Gershgorn, “Software Used to Predict Crime Can Now be Scoured for Bias” Quartz (March 22, 2017) available at https://qz.com/938635/a-predictive-policing-startup-released-all-its-code-so-it-can-be-scoured-for-bias/

Jason Tashea, “Courts Are Using AI to Sentence Criminals. That Must Stop Now, Wired (April 17, 2017) available at https://www.wired.com/2017/04/courts-using-ai-sentence-criminals-must-stop-now/



Ben Dickson, “How Artificial Intelligence is Changing Education, Tech Talks (March 9, 2017) available at https://bdtechtalks.com/2017/03/09/artificial-intelligence-education-edtech/

Candace M. Thille, “As Big Data Companies Come to Teaching, a Pioneer Issues a Warning,” Chronicle of Higher Education (February 23, 2016) available at http://chronicle.com/article/As-Big-Data-Companies-Come-to/235400

Bridget Burns, “Big Data’s Coming of Age in Higher Education,”Forbes.com (January 29, 2016) available at http://www.forbes.com/sites/schoolboard/2016/01/29/big-datas-coming-of-age-in-higher-education/#2f6ba732a325

Mikaela Pitcan, “Real Life Harms of Student Data,” Data & Society Research Institute (June 16, 2016) available at https://points.datasociety.net/real-life-harms-of-student-data-956a30aaff32#.z185lmtuy

Elana Zeide, “19 Ways Data Analysis Empowered Students and Schools,” Future of Privacy Forum (March 16, 2016) available at https://fpf.org/wp-content/uploads/2016/03/Final_19Times-Data_Mar2016-1.pdf

Goldie Blumenstyk, “As Big Data Comes to College, Officials Wrestle to Set New Ethical Norms”, The Chronicle of Higher Education (June 28, 2016) available at http://chronicle.com/article/As-Big-Data-Comes-to-College/236934

Jeffrey R. Young, “This Chart Shows the Promise and Limits of ‘Learning Analytics’”, The Chronicle of Higher Education ( January 4, 2016) available at http://chronicle.com/article/This-Chart-Shows-the-Promise/234573



“A New York Startup Shakes up the Insurance Business,”  The Economist (March 9, 2017) available at http://www.economist.com/news/finance-and-economics/21718502-future-insurance-named-after-soft-drink-new-york-startup-shakes-up

 Lisa Morgan, Big Data: 6 Real-Life Business Cases, Information Week August 30, 2016) available at http://www.informationweek.com/software/enterprise-applications/big-data-6-real-life-business-cases/d/d-id/1320590?image_number=1

Bernard Marr, “The 18 Best Analytic Tools Every Business Manager Should Know,” Forbes.com (February 4, 2016) available at http://www.forbes.com/sites/bernardmarr/2016/02/04/the-18-best-analytics-tools-every-business-manager-should-know/#257deeae2c4a

Rob Marvin, “Predictive Analytics, Big Data, and How to Make Them Work for You,” pcmag.com (July 12, 2016) available at http://www.pcmag.com/article/345858/

Bernard Marr, “Four Ways Big Data Will Change Every Business,” Forbes.com September 8, 2015) available at http://www.forbes.com/sites/bernardmarr/2015/09/08/4-ways-big-data-will-change-every-business/#6c4956ff7900



Donna Marbury, “Making Sense of Big Data: Data Projects Spur Progress,” modernmedicine.com (July 3, 2016) available at http://managedhealthcareexecutive.modernmedicine.com/managed-healthcare-executive/news/making-sense-big-data-data-projects-spur-progress?page=0,0

Adam Tanner, “How Data Brokers Make Money Off Your Medical Records,” Scientific American (February 1, 2016) available at http://www.scientificamerican.com/article/how-data-brokers-make-money-off-your-medical-records/

Agata Kwapien, “Top 5 Examples of Big Data in Healthcare That Can Save Lives,” Datapine.com (February 24, 2016) available at http://www.datapine.com/blog/big-data-examples-in-healthcare/

Dylan Scott, What Does the Mormon Church have to do With Biden’s Cancer Moonshot?” Statnews.com (February 26, 2016 available at https://www.statnews.com/2016/02/26/biden-cancer-moonshot-utah/

John Russell, “Obama, NIH Asnnounce Big Data Gathering Push for Precision Medicine,” hpcwire.com (July 7, 2016) available at https://www.hpcwire.com/2016/07/07/obama-nih-announce-big-data-gathering-push-precision-medicine/

Tiffany Trader, “This Hospital Computer Knows When Your Days Are Numbered,” hpcwire.com (September 25, 2015) available at https://www.hpcwire.com/2015/09/25/this-hospital-computer-knows-when-your-days-are-numbered/  (read article and view embedded video)

Muqbil Ahmar, Big Data Analytics and IoT Can Solve Some of the Hardest Medical Problems,” techfirstpost.com (July 5, 2016) available at http://tech.firstpost.com/biztech/big-data-analytics-and-iot-can-solve-some-of-the-hardest-medical-problems-323803.html


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