Technology CritiquePapers

This paper investigates the interplay between gender bias in AI systems and the potential of digital literacy to empower women in technology. Synthesizing research from 2010-2024, it examines how gender bias manifests in AI and the effectiveness of digital literacy initiatives.

A groundbreaking 2018 FAccT study revealing severe bias in commercial facial recognition systems against darker-skinned women, with error rates up to 34.7% compared to just 0.8% for lighter-skinned males.

D’Ignazio and Klein turn feminist epistemology into questions for visualization design: how categories, visual form, participation, context, and labor shape whose knowledge becomes legible.

Safiya Umoja Noble connects Black women's representation in search to the extraction, labor, and waste behind digital infrastructure.

Carol Cohn's fieldwork traces how U.S. nuclear strategists' euphemisms, sexualized metaphors, and domestic imagery make mass violence appear technical, controlled, and rational.