Note: All readings will be finalized one week prior to when they are due (Midnight on the prior Wednesday). All readings posted here ahead of that timeline are for guidance purposes only.
Week 1: Introduction (March 29 + 31)
Note: This week will be an unusual one. We’ll be doing an an introduction to the course and a quick primer on societal context in addition to discussion on Friday
Discussion Leaders: Prof. Hecht
- Russell, Stuart, Daniel Dewey, Max Tegmark, Janos Kramar, and Richard Mallah. “Research Priorities for Robust and Beneficial Artificial Intelligence.” Future of Life Institute, 2015. [medium]
- Obama White House: Executive Office of the President National Science and Technology Council Committee on Technology. 2016. Executive Summary: Preparing for the Future of Artificial Intelligence. [short]. Note: Be sure to ONLY read the executive summary!
- Hecht, B. 2016. HCI and the U.S. Presidential Election: A Few Thoughts on a Research Agenda. [short]
- Due Friday: Complete the course onboarding survey
- Reading Quiz: https://goo.gl/forms/0bkzIyNAdEqU3ZzP2
Week 2: Sharing Economy (April 5 + 7)
Discussion Leaders: Prof. Hecht
- Journalist’s Resource. 2017. Uber, Airbnb and consequences of the sharing economy: Research roundup. Note: No need to read all the abstracts, just the summary! [Short]
- Badger, E. 2015. Now we know how many drivers Uber has — and have a better idea of what they’re making. [Short]
- Center for Economic and Policy Research. 2017. Ubernomics. [Short]
- Thebault-Spieker, J., Terveen, L., and Hecht, B. 2017. Towards a Geographic Understanding of the Sharing Economy: Systemic Biases in UberX and TaskRabbit. ACM Transactions on Computer-Human Interaction (TOCHI). In press. [Long] Note: You may want to skim some of the methods sections.
- Malhotra, Arvind, and Marshall Van Alstyne. “The Dark Side of the Sharing Economy … and How to Lighten It.” Commun. ACM 57, no. 11 (October 2014): 24–27. doi:10.1145/2668893. [Short]
- Schor, J. 2014. Debating the Sharing Economy. Essay. [Short]
- Dillahunt, Tawanna R., et al. “Uncovering the Values and Constraints of Real-time Ridesharing for Low-resource Populations.”. In Proceedings of the ACM 34th international conference on Human factors in computing systems (CHI 2017). [Long]
- Due Wednesday night: E-mail Prof. Hecht w/ final discussion leadership information (filter bubble people need to do this earlier).
- Reading quiz: http://bit.ly/2p9xwoE.
- Additional reading discussed in class:
- Schelling, T. Dynamic Models of Segregation. 1971. [via Ramish]
Week 3: The “Filter Bubble” (April 12 + 14)
- Eli Pariser. 2011. Beware online “filter bubbles”. Ted Talk. [short]
- NPR. 2008. “‘The Big Sort’: Red and Blue Divide Neighbors, Too”. [short]
- Nguyen, T.T., Hui, P.M., Harper, F.M., Terveen, L. and Konstan, J.A., 2014. Exploring the filter bubble: the effect of using recommender systems on content diversity. WWW ‘14. ACM. [long]
- Barberá, P., Jost, J.T., Nagler, J., Tucker, J.A. and Bonneau, R., 2015. Tweeting from left to right: Is online political communication more than an echo chamber?. Psychological science, 26(10), pp.1531-1542.
- Bakshy, E., Messing, S. and Adamic, L.A., 2015. Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), pp.1130-1132. [short]
- Munson, Sean A., Stephanie Y. Lee, and Paul Resnick. Encouraging Reading of Diverse Political Viewpoints with a Browser Widget. ICWSM. 2013.
- Resnick, Paul, et al. Bursting your (filter) bubble: strategies for promoting diverse exposure. Proceedings of the 2013 conference on Computer supported cooperative work companion. ACM, 2013.
- Garimella, Kiran, et al. Reducing Controversy by Connecting Opposing Views. Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. ACM, 2017.
- Five Tips to Break Through Your Filter(s). Harvard Business Review . 2011.
- Reading quiz: http://bit.ly/2pAW5e4.
Week 4: Algorithms and Bias (April 19 + 21)
Note: On 4/21 there will be a substitute “Prof. Hecht”. The real “Prof. Hecht” will be in Washington D.C. doing scientific service.
- ACM. 2017. Statement on Algorithmic Transparency and Accountability.
- Kay, Matthew, Cynthia Matuszek, and Sean A. Munson. “Unequal Representation and Gender Stereotypes in Image Search Results for Occupations.” In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 3819–3828. ACM CHI ’15. [Long]
- Johnson, I., McMahon, C., Schöning, J., and Hecht, B. (2017) The Effect of Population and “Structural” Biases on Social Media-based Algorithms – A Case Study in Geolocation Inference Across the Urban-Rural Spectrum. Proceedings of the 35th Annual ACM Conference on Human Factors in Computing Systems (CHI 2017). New York: ACM Press. [Long]
- Hecht, B. and Gergle, D. 2010. The Tower of Babel Meets Web 2.0: User-Generated Content and Its Applications in a Multilingual Context. Proceedings of CHI 2010, pp. 291–300. New York: ACM Press. [Long]
- Wattenberg et al. 2017. Attacking discrimination with smarter machine learning. Interactive feature to accompany this paper.
- Bolukbasi, Tolga, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, and Adam T. Kalai. Man is to computer programmer as woman is to homemaker? debiasing word embeddings. In Advances in Neural Information Processing Systems, pp. 4349-4357. 2016.
- Caliskan, A. 2017. Semantics derived automatically from language corpora contain human-like biases. Science.
- Dwork, Cynthia, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. Fairness through awareness. In Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, pp. 214-226. ACM, 2012.
- PBS. 2016. Bias? In My Algorithms? A Facebook News Story
Week 5: Algorithms and #FakeNews (April 26 + 28)
- Morris, M.R., Counts, S., Roseway, A., Hoff, A., and Schwarz, J. 2012. Tweeting is Believing? Understanding Microblog Credibility Perceptions. Proceedings of ACM CSCW 2012.
- Kollanyia, B. et al. 2016. Bots and Automation over Twitter during the U.S. Election.
- Starbird, Kate. 2017. Information Wars: A Window into the Alternative Media Ecosystem.
- Snopes. 2017. Google Adds Fact-Check Info to Search Results. [very short]
- Kakutani, M. 2016. NY Times. ‘How Propaganda Works’ Is a Timely Reminder for a Post-Truth Age. [short]
- Ruchansky, N. et al. 2017. arXiv. CSI: A Hybrid Deep Model for Fake News. [medium] (arXiv post on fake news week? we’ll discuss!)
- Note: One more reading may be coming. If it does, it will happen no later than Wednesday.
- A story on liberal fake news: https://townhall.com/tipsheet/guybenson/2017/04/17/fake-news-liberals-cant-stop-sharing-this-false-meme-about-trump-n2314316
- Fake news around the world: https://www.theguardian.com/media/2016/dec/02/fake-news-facebook-us-election-around-the-world.
- Making fake news: http://www.chicagotribune.com/news/nationworld/ct-fake-news-yellow-journalists-20161121-story.html.
- Facebook and Information Operations (include fake/false news): https://fbnewsroomus.files.wordpress.com/2017/04/facebook-and-information-operations-v1.pdf.
- Shane, S. 2017. From Headline to Photograph, a Fake News Masterpiece. New York Times.
Week 6: Algorithmic Management (May 3 + 5)
- Lee, M.K., Kusbit, D., Metsky, E. and Dabbish, L., 2015. Working with machines: The impact of algorithmic and data-driven management on human workers. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 1603-1612). ACM.
- Kittur, A., Nickerson, J.V., Bernstein, M., Gerber, E., Shaw, A., Zimmerman, J., Lease, M. and Horton, J., 2013, February. The future of crowd work. In Proceedings of the 2013 conference on Computer supported cooperative work (pp. 1301-1318). ACM.
- Bederson, B. and Quinn, A. 2011 Web workers unite! addressing challenges of online laborers. alt.chi.
- Ashkar, A. Create a Crowd Competition That Works.
- Suzuki, Ryo, Niloufar Salehi, Michelle S. Lam, Juan C. Marroquin, and Michael S. Bernstein. “Atelier: Repurposing Expert Crowdsourcing Tasks as Micro-internships.” In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 2645-2656. ACM, 2016.
Week 7: Algorithms and Income Inequality [Part I] (May 10 + 12)
Discussion Leaders: Prof. Hecht
Note: No class on 5/10. Prof. Hecht (and a number of students) will be at ACM SIGCHI 2017 on 5/10. We will report back on the latest state-of-the-art in this area.
- Brynjolfsson, Erik, and Andrew McAfee. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. 1 edition. W. W. Norton & Company, 2016.
- McMahon, C., Johnson, I., and Hecht, B. (2017) The Substantial Interdependence of Wikipedia and Google – A Case Study on the Relationship Between Peer Production Communities and Intelligent Technologies. Proceedings of AAAI ICWSM 2017. Menlo Park, CA: AAAI Press.
- If possible: Video of Prof. Hecht’s panel at ACM SIGCHI 2017
Week 8: Algorithms and Income Inequality [Part II] (May 10 + 12)
Discussion Leaders: Prof. Hecht Note: Potentially no class on 5/17 due to AAAI ICWSM 2017
No additional reading relative to the prior week.
Week 9: Algorithmic Transparency (May 24 + 26)
- M. Eslami, A. Rickman, K. Vaccaro, A. Aleyasen, A. Vuong, K. Karahalios, K. Hamilton, and C. Sandvig. I always assumed that I wasn’t really that close to her: Reasoning about invisible algorithms in the news feed, CHI 2015.
- Diakopoulos, N., 2016. Accountability in algorithmic decision making. Communications of the ACM, 59(2), pp.56-62.
- Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2016. Why Should I Trust You?. ACM Press, 1135–1144.
- Kim Zetter. 2016. Researchers sue the government over computer hacking law. WIRED, 1–11. Retrieved May 16, 2017 from
- Christian Sandvig, Kevin Hamilton, Karrie Karahalios, and Cedric Langbort. 2014. Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms. 64th Annual Meeting of the International Communication Association: 1–23.
- Due Friday night: Your project status update! See the projects page for instructions and submission info.
Week 10: Algorithms, Privacy, and Security (May 31 + June 2)
- Kang, R., Dabbish, L., Fruchter, N. and Kiesler, S., 2015. “My data just goes everywhere:” user mental models of the internet and implications for privacy and security. In Symposium on Usable Privacy and Security (SOUPS).
- Krumm, J., 2007, May. Inference attacks on location tracks. In International Conference on Pervasive Computing (pp. 127-143). Springer Berlin Heidelberg.
Finals Week: Project Presentations
- No reading