1. Benjamin, R. (2019). Race after technology: Abolitionist tools for the New Jim Code. Polity.
2. Broussard, M. (2023). More than a glitch: Confronting race, gender, and ability bias in tech. MIT Press.
3. Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency in Proceedings of Machine Learning Research, 81, 77–91. https://proceedings.mlr.press/v81/buolamwini18a.html
4. D’Ignazio, C., & Klein, L. F. (2020). Data feminism. MIT Press.
5. Joyce, K., Smith‐Doerr, L., Alegria, S., Bell, S., Cruz, T., Hoffman, S. G., Noble, S. U., & Shestakofsky, B. (2021). Toward a sociology of artificial intelligence: A call for research on inequalities and structural change. Socius, 7. https://doi.org/10.1177/2378023121999581