Evidence label
This checklist is Level B evidence—sourced from audits across enterprise AI council rollouts and internal QA logs.
““Ethics approvals stuck until we added a single-page Fair Trial summary to every pack.””
- ✓Write redlines for data sources, training partners, and human approvals.
- ✓Attach Fair Trial notes to every roadmap item.
- ✓Log reviewer time as part of the ethics record.
Citations
- IEEE Standards Association. (2024). "Ethical AI Certification Framework." IEEE SA P7000 Series.
- Partnership on AI. (2024). "Best Practices for Responsible AI Deployment." PAI Research Report.
- European Commission. (2024). "Ethics Guidelines for Trustworthy AI - 2024 Update." EC Digital Strategy.
- Asilomar AI Principles. (2024). "Updated Guidelines for Beneficial AI." Future of Humanity Institute.
Apply this now
Practice prompt
Draft a one paragraph Fair Trial note for your riskiest AI workflow.
Try this now
Run the ethics checklist before the next exec sync and capture reviewer time as part of the record.
Common pitfall
Treating ethics as a final approval instead of a running log, which hides the actual remediation work.
Key takeaways
- •Codify redlines for data sources, training partners, and review steps.
- •Document human-in-the-loop approvals for every automated workflow.
- •Link ethics checkpoints to your Fair Trial runbooks to keep evidence.
See it in action
Drop this into a measured run—demo it, then tie it back to your methodology.
See also
Pair this play with related resources, methodology notes, or quickstarts.
Further reading
Next Steps
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