Connor Leahy proposes deepfake liability as a first step toward AGI governance
In a dated TIME interview, Connor Leahy argued that liability across the deepfake development and distribution chain could build enforcement capacity for wider AI harms, alongside an internationally verifiable compute cap on frontier training runs.
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Why it moved the index
The full interview provides primary attribution for a distinct two-stage governance mechanism: price harm into the AI supply chain through liability, then use measurable compute caps to pause frontier scaling. The proposal is concrete but unimplemented, and the source does not establish its effectiveness, so magnitude and confidence remain modest.
Assessment history
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R1
Away 18 · confidence 68
Historical people-backfill adds a dated, attributable governance mechanism distinct from Leahy's later nuclear-command and superintelligence-ban evidence.
27 Aug 2026
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DoomBench assesses “Connor Leahy proposes deepfake liability as a first step toward AGI governance” as evidence moving away from doom, with magnitude 18 and confidence 68 out of 100 in the governance and control category.
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The DoomBench assessment of “Connor Leahy proposes deepfake liability as a first step toward AGI governance” is based on reporting from TIME and records the editorial rationale, source quality, attribution, and revision history.
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DoomBench summarizes “Connor Leahy proposes deepfake liability as a first step toward AGI governance” as follows: In a dated TIME interview, Connor Leahy argued that liability across the deepfake development and distribution chain could...
https://www.doombench.com/news/connor-leahy-proposes-deepfake-liability-as-a-first-step-toward-agi-governance-2024-01-19