Feminist Approaches to AI Reading Group

This reading group engages in an interdisciplinary exploration of feminist approaches to Artificial Intelligence, examining how systems of power and privilege shape and are shaped by the design, development, and deployment of AI technologies. In drawing from feminist technoscience, intersectional theory, and design justice, this set of readings critically examines dominant AI imaginaries and considers how to construct just, inclusive, and relational alternatives

We will investigate the ways AI reproduces social hierarchies and exclusions while imagining how feminist principles—such as care, justice, and collective flourishing, might transform AI spaces. Central themes include the co-construction of knowledge, the role of emotional labour and relationality in AI systems, and the ethical implications of designing AI technologies that reflect and reinforce gender, race, and class biases.

To approach feminist AI we must first work to define AI, considering both what AI is and what AI does. Importantly, increasing AI literacy allows for a multidisciplinary approach – essential for a solid analysis, just as fuller awareness and integration of social scientific theories and methodologies would lead to more equitable systems. Here are some resources to get you started:

  • A People’s Guide to AI
  • History of Artificial Intelligence
  • How Does AI Learn?
  • How Computers See Gender
  • Anatomy of an AI System
  • Knowing Machines
  • Critical Algorithm Studies: A Reading List

SCHEDULE

Session 1: A View from Nowhere

January 21: What does it mean to approach AI through a feminist lens?

Readings: 

Session 2: Lab Cultures and Histories

February 4: These readings investigate the AI lab as a site of knowledge production, considering how lab cultures, funding priorities, institutional norms, and histories of labour influence AI research trajectories and outcomes. 

Readings: 

  • Cetina, K. (1995). Laboratory studies: the cultural approach to the study of science. In Handbook of Science and Technology Studies (pp. 140-166). SAGE Publications, Inc., https://doi.org/10.4135/9781412990127
  • Govia, L. (2020). Coproduction, Ethics and Artificial Intelligence: A Perspective from Cultural Anthropology. Journal of Digital Social Research, 2(3), Article 3. https://doi.org/10.33621/jdsr.v2i3.53
  • Mulvin, Dylan. (2021). “The Visual Culture of Image Engineers (or the Lena Image, Part 1)” in Proxies: The Cultural Work of Standing In. 10.7551/mitpress/11765.001.0001.
  • Andreev, A., Komatsu, V., Almiron, P., Rose, K., Hughes, A., & Lee, M. Y. (2022). Welcome to the lab. ELife, 11, e79627. https://doi.org/10.7554/eLife.79627

Session 3: AI Intimacies

February 18: What are the promises of AI? Who desires the promised outcomes and who benefits from them? AI often (dis)embodies and reproduces gendered affects, biases, and normative notions of care and relationality. These readings consider how AI systems—like digital assistants or companion bots— reflect and reshape emotional labour, intimacy, sexuality, and gender norms and how it feels to engage with them.

Readings: 

  • Bassett, Caroline, ‘The Cruel Optimism of Technological Dreams’, in Jude Browne, and others (eds), Feminist AI: Critical Perspectives on Algorithms, Data, and Intelligent Machines (Oxford, 2023; online edn, Oxford Academic, 23 Nov. 2023), https://doi.org/10.1093/oso/9780192889898.003.0015
  • Depounti, I., Saukko, P., & Natale, S. (2023). Ideal technologies, ideal women: AI and gender imaginaries in Redditors’ discussions on the Replika bot girlfriend. Media, Culture & Society, 45(4), 720–736. https://doi.org/10.1177/01634437221119021
  • Phan, T. (2017). The Materiality of the Digital and the Gendered Voice of Siri. Transformations, 29, 24–33.
  • Rhee, Jennifer, ‘From ELIZA to Alexa: Automated Care Labour and the Otherwise of Radical Care’, in Jude Browne, and others (eds), Feminist AI: Critical Perspectives on Algorithms, Data, and Intelligent Machines (Oxford, 2023; online edn, Oxford Academic, 23 Nov. 2023), https://doi.org/10.1093/oso/9780192889898.003.0010,
  • Care Bot
  • Feminist Chatbots

Session 4: Constructing Gender and Rejecting Binaries

March 4: Feminist and queer theories have long rejected binaries as hierarchical and limiting classification structures. Gender is fraught, conceptually, within AI systems. In order to recommend products or music, or generate text or images, algorithms make a variety of assumptions about gender that often are not aligned with current understandings of what gender is, how it should be encoded, and how a gender variable should be ethically used.  

Readings: 

  • Adam, “Constructions of gender in the history of artificial intelligence,” in IEEE Annals of the History of Computing, vol. 18, no. 3, pp. 47-53, Fall 1996, doi: 10.1109/MAHC.1996.511944
  • Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition. Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 88 (November 2018), 22 pages. https://doi.org/10.1145/3274357
  • Draude, C., Klumbyte, G., Lücking, P., & Treusch, P. (2019). Situated algorithms: A sociotechnical systemic approach to bias. Online Information Review, 44(2), 325–342 
  • Burt-D’Agnillo, Madelin. 2022. “FemTech: A Feminist Technoscience Analysis”. The IJournal: Student Journal of the Faculty of Information 8 (1). Toronto, Canada. https://doi.org/10.33137/ijournal.v8i1.39909.
  • Leavy, S. (2018). Gender bias in artificial intelligence: The need for diversity and gender theory in machine learning. Proceedings of the 1st International Workshop on Gender Equality in Software Engineering, 14–16. https://doi.org/10.1145/3195570.3195580

Session 5: Feminist Methodologies

March 18: These readings offer strategies and frameworks for transforming AI through feminist principles of care, data ethics, and design justice. 

Readings: 

  • Towards a feminist framework for AI development: from principles to practice
  • A Feminist Data Ethics of Care for Machine Learning: The What, Why, Who and How
  • Design Justice: Community-Led Practices to Build the Worlds We Need Mhlambi, S. (2020). From Rationality to Relationality: Ubuntu as an Ethical & Human Rights Framework for Artificial Intelligence Governance. Carr Center Discussion Paper. https://carrcenter.hks.harvard.edu/publications/rationality-relationality-ubuntu-ethical-and-human-rights-framework- artificia
  • Tandon, A. (2021). Practicing Feminist Principles in AI Design. Feminist AI. https://feministai.pubpub.org/pub/practicing- feminist-principles/release/2 
  • Costanza-Chock, Sasha, ‘Design Practices: ‘Nothing About Us Without Us’’, in Jude Browne, and others (eds), Feminist AI: Critical Perspectives on Algorithms, Data, and Intelligent Machines (Oxford, 2023; online edn, Oxford Academic, 23 Nov. 2023), https://doi.org/10.1093/oso/9780192889898.003.0021,
  • “How to Build Anything Ethically” in Lewis, Jason Edward, ed. 2020. Indigenous Protocol and Artificial Intelligence Position Paper. Honolulu, Hawaiʻi: The Initiative for Indigenous Futures and the Canadian Institute for Advanced Research (CIFAR)

Session 6: Speculative Fictions

April 1

Readings: 

  • Imarisha, Walidah and adrienne maree brown, eds. Octavia’s Brood: Science Fiction Stories From Social Justice Movements. AK Press/IAS, 2015.
  • VanderMeer, A., & VanderMeer, J. (Eds.). (2015). Sisters of the revolution: A feminist speculative fiction anthology. PM Press.
  • Ursula K. Le Guin, “The Matter of Seggri” edited-book Author(s): Victoria Hegner Publication date: 2023 Publisher: Göttingen University Press
  • The Oracle for Transfeminist Technologies
  • Feminist Tech Exchange