Timnit Gebru
Founder · Distributed AI Research Institute
Named the labour, environmental, and stereotyping costs of large language models, and built an independent lab after leaving a major lab.
Voices
Who to read in each topic
Not a ranking. People and groups whose public work helps you go deeper. Save a piece to review later, or open it in a new tab.
Who is harmed, who is excluded, and whose dignity is diminished in outputs and decisions.What is known about people, who knows it, and what that knowledge is used for.Shared facts, persuasion, elections, and the conversations a public needs.Fraud, cybercrime, and the weaponization of capable systems.What happens between a person and a system: overreliance, loneliness, lost judgement.Care, clinics, and the people who depend on systems they did not choose.Work, wages, skill, and the meaning of contributing.What is learned, what is lost, and who gets to know.Who can use these systems, who is shut out, and who captures the gains.Language, culture, meaning, and the texture of a shared life.
Ruha Benjamin
Professor of African American studies · Princeton
Race After Technology is the book that lets a group see how ranking and scoring repeat older patterns of who is trusted.
Safiya Umoja Noble
Professor · UCLA
Algorithms of Oppression showed how search rankings can encode harm. A starting point for culture, identity, and what a system 'knows' about people.
Daron Acemoglu
Economist · MIT
Power and Progress asks whether a technical gain becomes a shared one. A good first book for labour, inequality, and who captures the surplus.
Virginia Eubanks
Writer and teacher
Automating Inequality follows ranking systems in welfare, homelessness, and child protection. Read this before a civic group talks about 'efficiency.'
Alondra Nelson
Former deputy director, White House OSTP · Institute for Advanced Study
Shepherded the Blueprint for an AI Bill of Rights. A civic starting point for rights language without requiring a legal training.