Executive summary

A method for testing how much evidence each AI release needs, before making the standard mandatory.

What is inside

What the research pack covers

The asset walks a research lead through harvesting assumptions, grading them, ranking materiality, tier design, scoring tests, seeded regressions, cost and time, and freezing the standard. It ends with an assumption register, a source log, and research questions.

  • Turning a baseline into a governed release standard
  • Designing evidence tiers by severity
  • Testing automatic scoring against human grading

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