Legal AI’s Legibility Problem

HAI Stanford – News(Global) 23 Jul 2026 52

AI legibility in high-stakes decision contexts mirrors challenges APS agencies face when deploying AI in regulatory or legal-adjacent functions.

  • Growing use of language models in legal tasks is prompting calls for transparency about error likelihood and severity.
  • Researchers argue meaningful AI transparency in legal contexts requires an institutional - not just technical - approach.
  • Limited extracted content makes full assessment difficult; the underlying PNAS special section is the primary resource.
  • Consider Agencies deploying AI in legal, regulatory, or quasi-judicial functions could consider how institutional transparency frameworks - rather than technical disclosures alone - apply to their governance arrangements.
  • Monitor Policy teams working on AI transparency or mandatory guardrails may want to monitor the PNAS special section for frameworks adaptable to Australian public sector contexts.

Implications are AI-generated. Starting points, not advice — see methodology for how they're framed.

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