Pangram Analysis Flags AI-Like Patterns in Dozens of Federal Appellate Opinions

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Pangram Analysis Flags AI-Like Patterns in Dozens of Federal Appellate Opinions

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National Review⚠

Reason

A study using the Pangram AI-detection tool examined approximately 2,250 published regional courts of appeals opinions and identified dozens showing linguistic markers consistent with AI-generated text. The analysis references Josh Morrow, a partner at Lehotsky Cohn LLP, but states the examined opinion has no connection to his practice. Perspectives differ on the implications for judicial accountability, institutional trust, and individual liberty.

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[National Review 🏛️] How I Use AI as a Professional Writer [Reason 🏛️] "Signs of AI Authorship in Federal Appellate Opinions"

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“How I Use AI as a Professional Writer”

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How different viewpoints frame this

Progressive

The findings indicate risks of unaccountable AI tools embedding biases in the justice system, particularly for disadvantaged groups, amid pressures like court underfunding.

“Equity, transparency, and structural drivers of AI adoption”

Conservative

Detections of AI patterns in opinions signal erosion of human accountability and potential ideological skews from opaque models in elite institutions.

“Institutional trust, precedent, and craftsmanship over productivity shortcuts”

Libertarian

Outsourcing judicial reasoning to proprietary algorithms weakens the personal responsibility required to justify coercive state power over individuals.

“Transparency, consent, and diffusion of blame in unaccountable systems”

Devil's Advocate

All views accept detector outputs without scrutinizing error rates on legal text or baseline clerk uniformity, and overlook the explicit lack of connection to judicial authorship.

“Unverified causal claims and substitution of narrower facts with broader institutional narratives”

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ReasonRight-Center✓ High

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