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Karen Hao Launches Crowdsourced Global AI Resistance Archive

TL;DR

  • Karen Hao launched the AI Resist List on the one-year anniversary of her book Empire of AI as a publicly accessible, community-contributed database.
  • The database organizes entries by 'Pillars of Support' sustaining AI empires, a framework adapted from Choose Democracy's authoritarianism resistance model.
  • Entries span labor actions, legal challenges, and grassroots campaigns across gig work, healthcare, education, and law enforcement sectors.

Journalist and author Karen Hao timed the launch of The AI Resist List to mark the one-year anniversary of her book *Empire of AI*, releasing a publicly accessible, community-contributed database that catalogs organized resistance to AI deployment across the globe. The project was built with collaborators from the DAIR Institute, WeandAI, and RefugeeLawLab, alongside independent researchers and journalists.

What makes the structure interesting is how it organizes what it collects. Rather than a flat list of protests or petitions, the database maps resistance movements according to how they pressure different 'Pillars of Support' that uphold dominant AI companies, a framework Hao adapted from Choose Democracy's Resist List, originally designed for tracking opposition to authoritarianism. The analogy is deliberate: it treats AI expansion as a power system with identifiable pressure points, not as a neutral technological wave.

Entries span labor actions, legal challenges, community organizing, and grassroots campaigns, with documented cases cutting across gig work, healthcare, education, and law enforcement sectors. That breadth matters. Most coverage of AI pushback focuses on one slice at a time, a union drive here, a lawsuit there. Aggregating them into a single searchable archive makes patterns visible in a way that isolated news coverage cannot.

For practitioners, the honest caveat is that community-contributed databases are only as good as their submissions and whatever editorial review sits behind them; the source material does not detail what verification standards govern entry. What the reporting also does not give you is a sense of scale: how many entries exist, which sectors or countries are best represented, or how current the data is.

Still, if the database gains traction among policymakers, civil society organizations, and communities already pushing back against specific deployments, it could become a genuine coordination tool. Organizers in one country dealing with AI in law enforcement could find precedents from another. Researchers tracking the political economy of AI get a structured archive to work from. Karen Hao announced the project on X, framing it as documentation of 'resistance to the AI empires around the world'; the scope language suggests this is meant to be comprehensive, not selective.

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