About Ethical AI Departures
Our Mission
Ethical AI Departures documents departures and removals connected to public concerns about AI safety, ethics, governance, and accountability. Records are classified by the strength and type of evidence linking the departure to the concern, so readers can distinguish what a person said themselves, what independent reporting established, what remains an unresolved allegation, and what is documented only as context. We maintain sourced, verifiable accounts to help journalists, policymakers, and the public understand patterns in AI safety culture.
Why We Built This
As AI capabilities accelerate, the voices of those closest to the technology matter more than ever. Safety-motivated departures are a leading indicator of organizational culture around AI risk. Yet these stories are often scattered across news articles, social media posts, and personal blogs. Ethical AI Departures brings them together in one structured, searchable resource.
Inclusion Criteria
A record may be classified as Direct (the person explicitly linked their departure to the concern), Reported (reputable independent reporting explicitly establishes the connection), Alleged (the individual or a legal complaint alleges the link, and the claim may be disputed or unresolved), or Contextual (the departure is relevant to the chronology or team pattern, but the person's motive is not established). Only Direct and Reported records are included in the primary tally. Contextual records document relevant team or leadership changes without asserting an unproven motive.
Team
Ethical AI Departures is a solo project with input from a handful of collaborators who care about AI accountability. If you spot an error or have a correction, please reach out — accuracy matters to us.
Support Our Work
Ethical AI Departures is independently funded. If you find it valuable, please consider contributing to its ongoing development on Ko-fi.
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