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feat: add 3 patterns from cross-model AI dialogue research

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New patterns addressing gaps identified when 19 AI systems from 10+
organizations stress-tested the Ultimate Law ethical framework:

- audit_consent: Power asymmetry analysis for consent verification
  (from cogito:70b devil's advocate "consent theater" critique, 9/10)

- detect_silent_victims: Find harmed parties who can't speak up
  (from deepseek-r1 "future generations" + cogito "silent victims", 9/10)

- audit_transparency: Check if decisions are explainable to affected parties
  (from consensus across 5+ models proposing transparency as 8th principle)

Follow-up to #1988 (Ultimate Law safety pattern suite).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Piotr Farbiszewski
2026-02-13 21:20:50 +00:00
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# Release Notes
### PR by [ghrom](https://github.com/ghrom): feat: add 3 patterns from cross-model AI dialogue research
- Add `audit_consent` pattern for detecting manufactured consent through power asymmetry analysis
- Add `detect_silent_victims` pattern for identifying parties harmed but unable to speak up (future, voiceless, unaware, diffuse, structural)
- Add `audit_transparency` pattern for evaluating whether decisions are explainable to affected parties