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Chapter 7 — Red Teaming with AI & Humans in the Loop

How to red team when AI assists analysis and humans retain decision authority — grounding, dissent, quality control, and hybrid session design.

  • AI-Assisted Red Teaming — Use AI as loyal opposition — challenge plans and surface risks — while the human owns stakes, judgment, and commitment.
  • Human-in-the-Loop Decision Authority — The decider remains accountable. AI informs and challenges; it does not approve, commit, or replace stakeholder judgment.
  • Grounding & Evidence Discipline — Read actual source material before analyzing. Separate grounded claims from model invention, guesswork, and phantom citations.
  • AI Check — Meta-review: mirror, grounding, dissent, sycophancy on AI-assisted analysis.
  • AI Anti-Patterns — Sycophancy, false balance, phantom citations, shallow steel-man, checklist theater in AI output.
  • Hybrid Session Design — Allocate roles across AI and humans across diverge → analyze → debate → converge with explicit handoffs.
  • Simulated Stakeholder Limits — When invented stakeholder voices help vs mislead — label simulations; prefer real dissent and culture with actual actors.
  • /redteam ai-check
  • /redteam challenge
  • /redteam review
  • /redteam steelman
  • /redteam calibrate
  • /redteam record
  • /redteam sequence

Handbook v10-native. UFMCS v9 predates modern AI-assisted workflows; this chapter defines how the RedTeam skill should behave with humans in the loop.