Bias in AI Reading Group

TDAI hosts monthly informal gatherings to discuss publications addressing racial and gender bias in algorithms and automated decision-making technologies. For 2024-25, the group is led by Dr. Harmony Bench (Dance), and held on Tuesdays (see below for dates). Our free-ranging conversations explore societal ramifications and implications for researchers, educators and students.

All OSU faculty, staff and students are welcome.

Join us!

Spring 2025 Dates:

  • Jan. 14
  • Feb. 11
  • Mar. 4
  • Apr. 15

Time: 2:30-3:30 p.m. (ET) 

Location: 279 Pomerene Hall or by Zoom

Email Dr. Harmony Bench at bench.9@osu.edu for the Zoom link or for a copy of this month's text.

Click here to join the Bias in AI reading group listserv

Next selection:

Readings for March 4: 

Perpetual Motion: Dance, Digital Cultures and the Common

Dunham’s Data: Katherine Dunham and Digital Methods for Dance Historical Inquiry
Movement on the Move

For those who cannot attend in person but would like to join online, find the Zoom link here

Suggest future titles to read and discuss (opens a shared Excel list)

Previous Selections

Mirca Madianou. (2021) "Nonhuman humanitarianism: when 'AI for good' can be harmful." Information, Communication & Society, 24(6), 850-868. https://doi.org/10.1080/1369118X.2021.1909100

Ahmad, Nafees. (2020). "Refugees and Algorithmic Humanitarianism: Applying Artificial Intelligence to RSD Procedures and Immigration Decisions and Making Global Human Rights Obligations Relevant to AI Governance." International Journal on Minority and Group Rights, 28(3), 367-435.

Beyond Fairness in Computer Vision: A Holistic Approach to Mitigating
Harms and Fostering Community-Rooted Computer Vision Research
by Timnit Gebru and Remi Denton

The Lifecycle of Software Objects (2010) by Ted Chiang

Algorithms of Resistance by Tiziano Bonini and Emiliano Treré. 
Focus on: Intro, ch1, ch2, ch6
https://direct.mit.edu/books/oa-monograph/5721/Algorithms-of-ResistanceThe-Everyday-Fight-against

Artificial Intelligence and the Practice of History: A Forum
American Historical Review Volume 128, Issue 3, September 2023
https://academic-oup-com.proxy.lib.ohio-state.edu/ahr/issue/128/3

AI in the Wild: Sustainability in the Age of Artificial Intelligence by Peter Dauvergne
https://direct.mit.edu/books/book/4942/AI-in-the-WildSustainability-in-the-Age-of
With participants reading chapters according to their interest.

Davide Gunkel, Perspective on Ethics of AI: Philosophy
https://academic-oup-com.proxy.lib.ohio-state.edu/edited-volume/34287/chapter/290670538

Carolyn Ashurst, et al, AI Ethics Statements: Analysis and Lessons Learnt from NeurIPS Broader Impact Statements
https://www.researchgate.net/publication/355872637_AI_Ethics_Statements_--_Analysis_and_lessons_learnt_from_NeurIPS_Broader_Impact_Statements

Marika Cifor and Patricia Garcia, et al, Feminist Data Manifest-NO
https://www.manifestno.com/

The Black Technical Object: On Machine Learning and the Aspiration of Black Being by Ramon Amaro (Sternberg Press, 2022)

Uncomputable: Play and Politics in the Long Digital Age by Alexander Galloway (Verso, 2021).

"Meme Wars: The Untold Story of the Online Battles Upending Democracy in America," by Joan Donovan (New York: Bloomsbury, 2022).

Louise Amoore, Cloud Ethics: Algorithms and the Attributes of Ourselves and Others (Duke University Press, 2020). https://library.ohio-state.edu/search/t?SEARCH=cloud+ethics&searchscope=7

Dan McQuillan, Resisting AI: An Anti-facist Approach to Artificial Intelligence (Bristol University Press, 2022). 

Wendy Chun, Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition (MIT Press, 2021).

Sarah Brayne, "The Criminal Law and law enforcement implications of big data." Annual Review of Law and Social Science, Vol. 14:293-308, October 2018. https://doi.org/10.1146/annurev-lawsocsci-101317-030839

Brian Jefferson, "Digitize and punish: computerized crime mapping and racialized carceral power in Chicago." Environment and Planning D: Society and Space, Vol. 35, Issue 5: 775–796, March 2017. https://doi.org/10.1177/0263775817697703

Brian Christian, The Alignment Problem: Machine Learning and Human Values (W.W. Norton & Co., 2020).

Caroline Criado Perez, Invisible Women: Data Bias in a World Designed for Men (Abrams Press, 2019).

Catherine D'Ignazio and Laura F. Klein< Data Feminism (MIT Press, 2020).

Michael Kearns and Aaron Roth, The Ethical Algorithm: The Science of Socially Aware Algorithm Design (Oxford University Press, 2020).

Safiya Umoja Noble, Algorithms of Oppression: How Search Engines Reinforce Racism (NYU Press, 2018).