Tristan Harris
Co-founder · Center for Humane Technology
Named how attention systems shape minds at scale, then turned the same lens on generative models in The AI Dilemma.
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.
Renée DiResta
Writer and researcher · Formerly Stanford Internet Observatory
Traces how influence operations, rumor, and now generative media move through networks. Useful when a group wants facts about manipulation, not vibes.
Emily M. Bender
Professor of linguistics · University of Washington
Insists that language models are not minds. A clarifying voice when a group is mixing 'the model said' with 'a person claims.'