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The cover of The AI Con

The AI Con

Emily M. Bender, Alex Hanna, 2025

See how AI hype obscures human choices, present harms, exploited labor, and practical ways to demand accountable technology on democratic terms.

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7 parts, about 22 minutes to read.

Why read it

  • Argues that artificial intelligence is a marketing label that hides who builds, sells and profits from automated systems
  • Gives you a set of questions for any AI claim: what task, measured on whom, who bears the errors, and who can appeal
  • A linguist and a sociologist trace the hidden workers, benchmarks and resource costs behind both doom and boom stories

Who it is for

  • Workers told their jobs will be automated away
  • Officials and buyers deciding whether to adopt AI tools
  • Readers skeptical of both AI hype and AI doom

What the summary covers

  1. The Label That Makes Power Disappear3 min
  2. Why Fluent Machines Feel Like Minds3 min
  3. Automation Is Made of Work3 min
  4. When Austerity Wears a Technical Mask3 min
  5. Synthetic Abundance Can Impoverish Knowledge3 min
  6. Fantasy Risk Versus Material Risk3 min
  7. After Hype: Specificity, Rights, and Refusal4 min

Recommended by

  • Karen HaoAuthor of Empire of AI
    Bender and Hanna write with absolute authority and incredible wit and verve. Come for the piercing observations; leave with the tools to slice your way through the absurdist narratives that prop up the AI industry and to hold it accountable
  • Timnit GebruFounder and Executive Director of the Distributed AI Research Institute
    A must-read. Drs. Alex Hanna and Emily M. Bender cut through the dizzying hype to provide the clearest picture yet of what AI is, what it is not, and why none of us need to accept it being shoved down our throats
  • Ha Joon ChangAuthor of Economics: The User's Guide and Edible Economics
    This is a truly eye-opening book that will be an indispensable 'field manual' for those who want to fight for a more humane economy and a better society
  • Johann HariAuthor of Stolen Focus
    A fascinating and thought-provoking analysis of one of the most charged debates in the world

About the authors

  • Emily M. BenderLinguist and professor at the University of Washington specializing in computational linguistics
    • Faculty member at the University of Washington since 2003, where she is the Thomas L. and Margo G. Wyckoff Endowed Professor in the Department of Linguistics
    • Faculty director of the professional master's program in computational linguistics and director of the Computational Linguistics Laboratory
    • Holds a PhD in linguistics from Stanford University and an AB in linguistics from UC Berkeley
    • Worked in industry at YY Technologies and held temporary positions at Stanford and UC Berkeley before joining Washington
    • Born in 1973
    • Elected a fellow of the American Association for the Advancement of Science in 2022
    • President of the Association for Computational Linguistics in 2024
    • Has studied the societal impacts of language technology since 2016, including the dangers of large language models and of chatbots used for search
  • Alex HannaSociologist and director of research at the Distributed AI Research Institute
    • Director of Research at the Distributed AI Research Institute (DAIR)
    • Studies how data used in new computational technologies deepens racial, gender and class inequality, and works on social movements, especially anti racist campus protest in the US and Canada
    • Holds a BS in computer science and mathematics and a BA in sociology from Purdue University, and an MS and a PhD in sociology from the University of Wisconsin Madison
    • Received her PhD in sociology in 2016
    • Was an assistant professor at the University of Toronto Mississauga before joining Google
    • Worked at Google, eventually as a senior research scientist on the Ethical AI team, before joining DAIR
    • Her next book, under contract with MIT Press, is about ImageNet, a dataset of 14 million images that helped build modern AI practices
    • Recipient of the Wisconsin Alumni Association Forward Award

Read it alongside

  • Pushes backSuperagency

    Emily M. Bender and Alex Hanna argue that deployers should first justify an AI system and that some uses should be banned; Reid Hoffman and Greg Beato argue that precaution preempts benefits and that AI rules should be drafted as specific harms appear, as with cars.

  • Pushes backThe Precipice

    Bender and Hanna argue that fears of AI extinction share the boosters' premise and pull attention from present harms such as labor, discrimination and resource use; Ord argues that unaligned AI is a serious existential risk this century, by his subjective estimate about one in ten, and that existential risk work is underfunded.

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