Feminist Perspectives for ML & CV: A Reading List
This page serves as a continuation of our discussion at the 2020 WiML UnWorkshop. To learn more about this reading list and how to contribute to it, see the FAQ.
Referenced in Our Presentation
- Data Feminism by Catherine D'Ignazio & Lauren Klein
- Feminism is for Everybody: Passionate Politics by bell hooks
- Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics by Kimberlé Crenshaw
- The Combahee River Collective statement
- Gender Shades by Joy Buolamwini & Timnit Gebru
- Large image datasets: A pyrrhic win for computer vision? by Vinay Uday Prabhu & Abeba Birhane
- Algorithms of Oppression by Safiya Umoja Noble
- 2020 Vision: Reimagining the Default Settings of Technology & Society by Ruha Benjamin
Intersectionality
- Age, Race, Class, and Sex: Women Redefining Difference by Audre Lorde
- Mapping the margins: Intersectionality, Identity Politics, and Violence Against Women of Color by Kimberlé Crenshaw
Diversity, Equity, & Inclusion
- HCI Guidelines for Gender Equity and Inclusivity by Morgan Klaus Scheuerman, Katta Spiel, Oliver L. Haimson, Foad Hamidi, & Stacy M. Branham
- Discriminating Systems: Gender, Race, and Power in AI by Sarah Myers West, Meredith Whittaker, & Kate Crawford
Critiquing Classification
- Excavating AI: The Politics of Images in Machine Learning Training Sets by Kate Crawford & Trevor Paglen
- The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition by Os Keyes
Talks & Videos
- How Machine Learning Research Shifts Power by Pratyusha Ria Kalluri
- FATE/CV Tutorial by Timnit Gebru & Emily Denton
- AI, Ain't I A Woman? by Joy Buolamwini
- Talking Data Feminism with Catherine D'Ignazio and Lauren F. Klein by Catherine D'Ignazio and Lauren F. Klein
Groups & Organizations
- Women in Machine Learning
- Black in AI
- Queer in AI
- LatinX in AI
- {Dis}Ability in AI
- Indigenous AI
- Data for Black Lives
- Feminist.AI