Analysis
When AI risks compound: reading Anthropic's S-1
The filing describes risks in infrastructure, financing and oversight. Assessing them means examining whether safeguards can operate under pressure.
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Legal analysis of AI disputes, regulation and governance, grounded in primary sources.
Analysis
Whose words does the court hear?
The Pelkey video joined a family's interpretation to a deceased person's face and voice. The legal problem survived its disclosure.
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Design as risk
How social-media litigation is reshaping the argument over AI liability.
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AI defamation: from the model's account to the record
Starbuck v. Google tests the evidence behind generated statements, fabricated sources, and notice to the people responsible for AI outputs.
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Part one: When the rule is not written down
Four records suggest that as a hiring mechanism becomes less legible, a plaintiff may reach filing without the rule, the model, or the group-level evidence needed to test it. None establishes that opacity caused the gap, or that discovery will close it.
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Part two: When the rule is written down and nobody looks
One city requires an automated hiring tool to be audited by an independent auditor and a summary of the result published. The official record through June 2025, which its auditors did not vouch for as complete, shows two complaints, no civil penalty, no notice of violation, and no proceeding at the city tribunal.
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What happens when AI governance enters the record?
Private assurances and California's frontier-model law expose the difference between governance evidence reconstructed in litigation and records created before a dispute.
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When the AI becomes a witness against you
Three federal rulings show why AI-related protection disputes turn on governing doctrine, procedural posture, counsel direction, and the material actually claimed.
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