It’s me, @professorcasey. Credentials: I’m an assistant professor in information science. PhD/JD. I research and teach in the areas of technology ethics and governance, online communities/social media, and transformative fandom.
TikTok-based Tech Ethics & Policy class
the 60-second at a time version of my class – read/watch along!
data privacy & reproductive rights proposed legislation: Pass the “My Body, My Data” Act (EFF) | Wyden, Paul and Bipartisan Members of Congress Introduce The Fourth Amendment Is Not For Sale Act | Warren proposes sweeping ban on location and health data sales (The Verge) | Democrats in Congress Introduce Bill to Crack Down on Fake Clinics and Anti-Abortion Disinformation (Ms Magazine) | In post-Roe America, your cell phone is now a reproductive privacy risk by Tiffany Li (MSNBC)
from HHS re: HIPAA: HHS Issues Guidance to Protect Patient Privacy in Wake of Supreme Court Decision on Roe | HIPAA Privacy Rule and Disclosures of Information Relating to Reproductive Health Care | Protecting the Privacy and Security of Your Health Information When Using Your Personal Cell Phone or Tablet
Fear, Uncertainty, and Period Trackers AND Okay, Fine, Let’s Talk About Period Tracking: The Detailed Explainer by Kendra Albert, Maggie Delano, and Emma Weil | beginner guide to secure messaging app Signal | Digital Defense Fund guide on abortion privacy
Wade, Kandrea, Jed R. Brubaker, and Casey Fiesler. “Protest privacy recommendations: An analysis of digital surveillance circumvention advice during black lives matter protests.” In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems, pp. 1-6. 2021.
advice for PhD applicants (YouTube playlist) – note that my advice is likely most helpful for (a) lab-based disciplines, e.g. STEM and social science; and (b) PhD programs in the U.S., but some is broadly applicable!
TikTok-based Online Communities class (Spring 2021)
my favorite book rec video: with thanks to penelope scott
Algorithms of Oppression (Safiya Noble); The Age of Surveillance Capitalism (Shoshana Zuboff); Race After Technology (Ruha Benjamin); Weapons of Math Destruction (Cathy O’Neil); Automating Inequality (Virginia Eubanks); Technically Wrong (Sara Wachter-Boettcher; Ghost Work (Mary Gray & Siddharth Suri); Design Justice (Sasha Constanza-Chock); Data Feminism (Catherine D’Ignazio & Lauren Klein); Custodians of the Internet (Tarleton Gillespie); Antisocial Media (Siva Vaidhyanathan); Black Software (Charlton D. McIlwain); Behind the Screen (Sarah Roberts); Invisible Women (Caroline Criado Perez); Programmed Inequality (Mar Hicks); This Is Why We Can’t Have Nice Things (Whitney Phillips); Calling Bullshit (Carl Bergstrom & Jevin West); The Charisma Machine (Morgan Ames); The Black Box Society (Frank Pasquale); Intersectional Tech (Kishoanna Gray); Artificial Unintelligence (Meredith Broussard); Coding Freedom (Gabriella Colman); Hello World (Hannah Frye); Atlas of AI (Kate Crawford); Silicon Values (Jillian York); Your Computer is On Fire (eds. Thomas S. Mullaney, Benjamin Peters, Mar Hicks, Kavita Philip); System Error (Rob Reich, Mehran Saham, Jeremy M. Weinstein), Technology of the Oppressed (David Nemar)
book rec video with thanks to The Stupendium
Autonomous (Annalee Newitz), Axiom’s End (Lindsay Ellis), Rosewater (Tade Thompson), Little Brother (Cory Doctorow), Oryx and Crake (Margaret Atwood), After On (Rob Reid), Binti (Nnedi Okorafor), Ready Player One (Ernest Cline), Nexus (Ramez Naam), The Three-Body Problem (Cixin Liu), Warcross (Marie Lu), Ancillary Justice (Ann Leckie), All Systems Red (Martha Wells), War Girls (Tochi Onyebuchi), The Circle (David Eggers), Infomocracy (Malka Older), Snow Crash (Neal Stephenson), Jurassic Park (Michael Crichton), A Beautifully Foolish Endeavor (Hank Green)
VIDEOS: Algorithms are not neutral | AI, AOC & a bikini| Why AI didn’t hire women | Hiring has always been racist | Is AI naughty or nice? | How do machines learn? | Definitely white men. | Bias & black box algoithms
Gender Shades video | Buolamwini, Joy, and Timnit Gebru. “Gender shades: Intersectional accuracy disparities in commercial gender classification.” In Conference on fairness, accountability and transparency, pp. 77-91. PMLR, 2018. | How Computers See Gender (blog post) | Scheuerman, Morgan Klaus, Jacob M. Paul, and Jed R. Brubaker. “How computers see gender: An evaluation of gender classification in commercial facial analysis services.” Proceedings of the ACM on Human-Computer Interaction 3, no. CSCW (2019): 1-33.
“AI phrenology”: Stinson, Catherine. “The Dark Past of Algorithms That Associate Appearance and Criminality: Machine learning that links personality and physical traits warrants critical review.” American Scientist 109, no. 1 (2021): 26-30. | Bowyer, Kevin W., Michael C. King, Walter J. Scheirer, and Kushal Vangara. “The “Criminality From Face” Illusion.” IEEE Transactions on Technology and Society 1, no. 4 (2020): 175-183. | An AI Paper Published in a Major Journal Dabbles in Phrenology (Vice)
bias in healthcare algorithms: A hospital algorithm designed to predict a deadly condition misses most cases (The Verge) | Obermeyer, Ziad, Brian Powers, Christine Vogeli, and Sendhil Mullainathan. “Dissecting racial bias in an algorithm used to manage the health of populations.” Science 366, no. 6464 (2019): 447-453. | Millions of black people affected by racial bias in health-care algorithms (Nature)
Sharing learnings about our image cropping algorithm (Twitter) | Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency by Yee et al. | Twitter says its image-cropping algorithm was biased, so it’s ditching it (CNN)
Black homeowner had a white friend stand in for third appraisal. Her home value doubled (South Bend Tribune) | Black Homeowners Face Discrimination in Appraisals (NY Times) | Why a proposed HUD rule could worsen algorithm-driven housing discrimination (Brookings) | EFF to HUD: Algorithms Are No Excuse for Discrimination
Dressel, Julia, and Hany Farid. “The accuracy, fairness, and limits of predicting recidivism.” Science advances 4, no. 1 (2018): eaao5580.
Washington, Anne L. “How to argue with an algorithm: Lessons from the COMPAS-ProPublica debate.” Colo. Tech. LJ 17 (2018): 131.
Kahn, Kimberly Barsamian, and Karin D. Martin. “The Social Psychology of Racially Biased Policing: Evidence-Based Policy Responses.” Policy Insights from the Behavioral and Brain Sciences 7, no. 2 (2020): 107-114.
Williams, Betsy Anne, Catherine F. Brooks, and Yotam Shmargad. “How algorithms discriminate based on data they lack: Challenges, solutions, and policy implications.” Journal of Information Policy 8 (2018): 78-115.
All the Ways Hiring Algorithms Can Introduce Bias (Harvard Business Review) – based on Help Wanted: An Examination of Hiring Algorithms, Equity, and Bias
Raghavan, Manish, Solon Barocas, Jon Kleinberg, and Karen Levy. “Mitigating bias in algorithmic hiring: Evaluating claims and practices.” In Proceedings of the 2020 conference on fairness, accountability, and transparency, pp. 469-481. 2020.
Bertrand, Marianne, and Sendhil Mullainathan. “Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination.” American economic review 94, no. 4 (2004): 991-1013. [And here’s a simplified explainer.]
Quillian, Lincoln, Devah Pager, Ole Hexel, and Arnfinn H. Midtbøen. “Meta-analysis of field experiments shows no change in racial discrimination in hiring over time.” Proceedings of the National Academy of Sciences 114, no. 41 (2017): 10870-10875.
Buolamwini, Joy, and Timnit Gebru. “Gender shades: Intersectional accuracy disparities in commercial gender classification.” In Conference on fairness, accountability and transparency, pp. 77-91. PMLR, 2018.
Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases (FaaCT 2021) [Press: What a picture of Alexandria Ocasio-Cortez in a bikini tells us about the disturbing future of AI (The Guardian)]
Haimson, Oliver L., Daniel Delmonaco, Peipei Nie, and Andrea Wegner. “Disproportionate Removals and Differing Content Moderation Experiences for Conservative, Transgender, and Black Social Media Users: Marginalization and Moderation Gray Areas.” Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW2 (2021): 1-35. | Summary: Social Media Sites are Censoring Transgender, Black, and Conservative Users – But for Very Different Reasons | False Accusation: The Unfounded Claim that Social Media Companies Censor Conservatives (NYU Stern Center for Business and Human Rights)
WSJ Facebook reports: Facebook Tried to Make Its Platform a Healthier Place. It Got Angrier Instead. | How Facebook Hobbled Mark Zuckerberg’s Bid to Get America Vaccinated [related: A 61-million-person experiment in social influence and political mobilization (Bond et al., Nature)
Tiktok & extreme content: WSJ investigation video | Chancellor et al. #thyghgapp: Instagram content moderation and lexical variation in pro-eating disorder communities. CSCW 2016. | Ribeiro et al. Auditing radicalization pathways on YouTube. FaaCT 2020. | The Making of a YouTube Radical (NYT) | YouTube’s Plot to Silence Conspiracy Theories (WIRED)
interview w/ me in MIT Technology Review about TikTok!: Welcome to TikTok’s endless cycle of censorship and mistakes
bias in content moderation: Beyond a technical bug: Biased algorithms and moderation are censoring activists on social media (The Conversation) | Sap, Maarten, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A. Smith. “The risk of racial bias in hate speech detection.” In Proceedings of the 57th annual meeting of the association for computational linguistics, pp. 1668-1678. 2019.
Inadvertent Algorithmic Cruelty by Eric Meyer | Pinter, Anthony T., Jialun Aaron Jiang, Katie Z. Gach, Melanie M. Sidwell, James E. Dykes, and Jed R. Brubaker. “Am I Never Going to Be Free of All This Crap?” Upsetting Encounters with Algorithmically Curated Content About Ex-Partners. Proceedings of the ACM on Human-Computer Interaction 3, no. CSCW (2019): 1-23.
Does Facebook listen to you? Is your phone really listening to your conversations? Well, turns out it doesn’t have to by Dana Rezazadegan (The Conversation, 2021) | These Academics Spent the Last Year Testing Whether Your Phone Is Secretly Listening (Gizmodo) | No, Facebook Is Not Secretly Listening to You (Except when it is.) (New York Times) | Frick, N.R., Wilms, K.L., Brachten, F., Hetjens, T., Stieglitz, S. and Ross, B., 2021. The perceived surveillance of conversations through smart devices. Electronic Commerce Research and Applications, 47, p.101046. | Pan, E., Ren, J., Lindorfer, M., Wilson, C. and Choffnes, D., 2018. Panoptispy: Characterizing audio and video exfiltration from android applications. Proceedings on Privacy Enhancing Technologies, 2018(4), pp.33-50.
Kokolakis, Spyros. “Privacy attitudes and privacy behaviour: A review of current research on the privacy paradox phenomenon.” Computers & security 64 (2017): 122-134. | Carrascal, Juan Pablo, Christopher Riederer, Vijay Erramilli, Mauro Cherubini, and Rodrigo de Oliveira. “Your browsing behavior for a big mac: Economics of personal information online.” In Proceedings of the 22nd international conference on World Wide Web, pp. 189-200. 2013. | Shklovski, Irina, Scott D. Mainwaring, Halla Hrund Skúladóttir, and Höskuldur Borgthorsson. “Leakiness and creepiness in app space: Perceptions of privacy and mobile app use.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2347-2356. 2014. | Fiesler, Casey, and Blake Hallinan. “” We Are the Product” Public Reactions to Online Data Sharing and Privacy Controversies in the Media.” In Proceedings of the 2018 CHI conference on human factors in computing systems, pp. 1-13. 2018.
McDonald, Aleecia M., and Lorrie Faith Cranor. “The cost of reading privacy policies.” Isjlp 4 (2008): 543. (NPR article) | Fiesler, Casey, Cliff Lampe, and Amy S. Bruckman. “Reality and perception of copyright terms of service for online content creation.” Proceedings of the ACM conference on computer-supported cooperative work & social computing. 2016. | Obar, Jonathan A., and Anne Oeldorf-Hirsch. “The biggest lie on the internet: Ignoring the privacy policies and terms of service policies of social networking services.” Information, Communication & Society 23.1 (2020): 128-147.
New paper! Shilton et al. Excavating awareness and power in data science: A manifesto for trustworthy pervasive data research. Big Data & Society, 2021.
Research integrity: Evidence of Fraud in an Influential Field Experiment About Dishonesty | A Big Study About Honesty Turns Out To Be Based On Fake Data | The Case of the Amazing Gay-Marriage Data: How a Graduate Student Reluctantly Uncovered a Huge Scientific Fraud | my tweet thread | I Fooled Millions Into Thinking Chocolate Helps Weight Loss
Facebook & data scraping: Facebook Disables Accounts Tied to NYU Research Project (Bloomberg) | Research Cannot Be the Justification for Compromising People’s Privacy (Facebook’s statement) | Facebook’s Reason for Banning Researchers Doesn’t Hold Up (WIRED) | Letter from Acting Director of the Bureau of Consumer Protection Samuel Levine to Facebook (FTC statement) | The law and ethics of data scraping (by me!) | Open letter on tech industry accountability research
#medbikini study: “Prevalence of unprofessional social media content among young vascular surgeons” by Hardouin et a. (Journal of Vascular Surgery, now retracted) | Why Doctors Are Posing in Swimwear on Social Media (Scientific American) | my twitter thread about it
Studying Reddit: A Systematic Overview of Disciplines, Approaches, Methods, and Ethics by Proferes, Jones, Gilbert, Fiesler & Zimmer (Social Media + Society)
Fiesler, Casey, Shannon Morrison, and Amy S. Bruckman. “An archive of their own: A case study of feminist HCI and values in design.” In Proceedings of the 2016 CHI conference on human factors in computing systems, pp. 2574-2585. 2016. | Tumblr post research summary | Fans are better than tech at organizing information online (WIRED, 2019) | Why Archive of Our Own’s Hugo nomination is such a big deal (Slate, 2019) | YouTube video essay: The Life and Death of Fandom Platforms
Fiesler, Casey, and Brianna Dym. “Moving across lands: Online platform migration in fandom communities.” Proceedings of the ACM on Human-Computer Interaction 4, no. CSCW1 (2020): 1-25. | Tumblr post research summary | YouTube video essay: The Life and Death of Fandom Platforms
Warcross (Marie Lu), Don’t Read the Comments (Eric Smith), Slay (Brittney Morris), For the Win (Cory Doctorow), Reamde (Neal Stephenson), Dragon Ops (Mari Mancusi), Ready Player One (Ernest Cline)
Unlocking the Clubhouse: Women in Computing by Jane Margolis and Allan Fisher
The Secret History of Women in Coding (New York Times)
Shiver, Brent N., and Rosalee J. Wolfe. “Evaluating alternatives for better deaf accessibility to selected web-based multimedia.” In Proceedings of the 17th international ACM SIGACCESS conference on computers & accessibility, pp. 231-238. 2015.
Gernsbacher, Morton Ann. “Video captions benefit everyone.” Policy insights from the behavioral and brain sciences 2, no. 1 (2015): 195-202.
Henry, Shawn Lawton, Shadi Abou-Zahra, and Judy Brewer. “The role of accessibility in a universal web.” In Proceedings of the 11th Web for all Conference, pp. 1-4. 2014.
Some sources from advocacy groups etc. on the EARN IT Act: Center for Democracy and Technology | ACLU | Electronic Frontier Foundation | Stanford Center for Internet & Society | 2020 letter from a coalition of advocacy organizations |TechDirt article on myths vs facts | the text of the bill
Tripping through IBM’s astonishingly insane 1937 corporate songbook (Ars Technica, 2014))
How Black Twitter has become the new Green Book (CU Boulder Today) | Klassen, Shamika, Sara Kingsley, Kalyn McCall, Joy Weinberg, and Casey Fiesler. “More than a Modern Day Green Book: Exploring the Online Community of Black Twitter.” Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW2 (2021): 1-29.
Is the uncanny valley an uncanny cliff? by Barneck et al (2007) | Speech Synthesis and Uncanny Valley by Romportl (2014) | The Perception and Analysis of the Likeability and Human Likeness of Synthesized Speech by Baird et al. (2018) | also a good Wikipedia page on “uncanny valley”
Connolly, J., Mocz, V., Salomons, N., Valdez, J., Tsoi, N., Scassellati, B. and Vázquez, M., 2020, March. Prompting prosocial human interventions in response to robot mistreatment. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 211-220). | Abusing a robot won’t hurt it but it could make you a crueller person (The Conversation) | Sex robots increase the potential for gender-based violence (The Conversation)
Socioeconomic Roots of Academic Faculty by Morgan et al
Ask Delphi | Jiang et al. Delphi: Towards Machine Ethics and Norms. (pre-print) | The AI oracle of Delphi uses the problems of Reddit to offer dubious moral advice (The Verge)