Joy Buolamwini

Joy Buolamwini is a computer scientist and activist who turned a personal encounter with a flawed facial recognition demo into one of the most influential bodies of research on bias in AI training data. While a graduate student at the MIT Media Lab, she discovered that a facial-analysis system could not detect her own dark-skinned face unless she wore a white mask, an experience that led directly to her landmark 'Gender Shades' research.

Published in 2018 with Timnit Gebru, 'Gender Shades' audited commercial facial recognition systems from IBM, Microsoft and Face++ and found error rates of up to 34.7 percent for darker-skinned women compared with under 1 percent for lighter-skinned men. The study demonstrated concretely how skewed training datasets, overwhelmingly composed of lighter-skinned male faces, produced systems that performed unevenly and unfairly across racial and gender lines. The research prompted the audited companies to revise their systems and became a reference point in subsequent regulatory debate over facial recognition and biometric data.

Buolamwini founded the Algorithmic Justice League in 2016 to combine research, art and advocacy in exposing algorithmic bias, and has since testified before the US Congress and briefed policymakers internationally on the risks of unregulated biometric and facial recognition data collection. Her 2020 mini-documentary 'The Coded Gaze' and her role in the Emmy-nominated Netflix documentary 'Coded Bias' brought her research to a mainstream audience well beyond academic and policy circles.

A Rhodes Scholar with degrees from the Georgia Institute of Technology, the University of Oxford and MIT, where she completed her PhD in 2022, Buolamwini published the bestselling book 'Unmasking AI: My Mission to Protect What Is Human in a World of Machines' in 2023, chronicling her research and advocacy and calling for stronger data governance around biometric technologies.

Her work has directly influenced corporate and municipal policy, including facial recognition bans and moratoria in multiple US cities and revised auditing practices at major technology companies, making her one of the most consequential voices connecting technical data science to civil rights and public accountability.