Abebe, Rediet
1991- · Contribution: 2010s-2020s
Computer scientist
Algorithmic fairness research
Portraits are AI-generated interpretations, not photographs.
Quick facts
- Born
- 1991, Addis Ababa, Ethiopia
- Active since
- 2013
- Category
- Technology & Engineering
- Best known for
- Research on algorithms and social inequality
Impact on the world
Abebe helped establish the study of algorithms as a tool for understanding poverty and inequality, insisting that computer science engage directly with questions of justice.
An alternative history
What Would the World Look Like Without It?
One contribution. Many possible consequences. No single-person origin story.
Imagine this selected contribution absent, not the person or the entire field. The areas below are reflection prompts related to this discipline, not verified chains of direct dependency.
Sources
- Source lookupFind
University of California, Berkeley (EECS)
Exact source links open the cited record. Source lookups help locate legacy references whose original records did not include a direct URL.
2 more sources and references are available to members.
Related visionaries
Gebru, Timnit
1982/1983-
Co-authored 'Gender Shades,' a landmark 2018 study proving major facial recognition systems were significantly less accurate on darker-skinned faces; co-founded Black in AI; her controversial 2020 departure from Google sparked one of the most prominent public debates over corporate AI ethics research
Buolamwini, Joy Adowaa
1989-
Founded the Algorithmic Justice League after discovering commercial facial recognition software could not detect her own face unless she wore a white mask; co-authored 'Gender Shades,' which forced IBM, Microsoft, and Amazon to overhaul their facial recognition products
Sweeney, Latanya
1972-
Data privacy and re-identification research; algorithmic fairness in computing
Raji, Inioluwa Deborah
1995/1996-
Co-authored the 2019 'Actionable Auditing' study with Joy Buolamwini, already profiled in this collection, directly leading Amazon to face sustained public pressure over racial and gender bias in its facial recognition technology; later co-authored major frameworks for internal AI accountability auditing alongside Timnit Gebru, also already profiled here