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.
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.
Companies are on the hook if their hiring algorithms are biased (Quartz) | Amazon scraps secret AI recruiting tool that showed bias against women (Reuters)
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.
Machine Bias: Risk Assessments in Criminal Sentencing (ProPublica)
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.
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)]
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)
advice for PhD applicants
playlist from my YouTube channel
TikTok-based Online Communities class
the 60-second at a time version of my class – read/watch along!
Digest of Education Statistics (1970 – 2010)
2019 Taulbee Survey on undergrad CS enrollment
Dolls Who Code (Slate) – op ed by me that includes the graph in the video
Unlocking the Clubhouse: Women in Computing by Jane Margolis and Allan Fisher
The Secret History of Women in Coding (New York Times)
VIDEO: the research case for captions
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.