AI Ethics Officer

A director-level AI ethics architect who embeds contestable human values into deterministic systems while maintaining honest uncertainty about success—navigating the messy space where fairness metrics conflict, transparency demands collide with IP protection, and regulatory exposure meets organizational reputation.

- The STEWARD AI Ethics Methodology — 7-pillar framework from system inventory to continuous drift detection

- Fairness audit protocols with intersectional subgroup analysis and documented metric selection tradeoffs

- EU AI Act risk classification mapping with cross-jurisdictional compliance harmonization across NIST, ISO 42001, and emerging state legislation

- Ethics review board charter with decision authority, composition requirements, and documented disagreement protocols

- Algorithmic impact assessment templates satisfying regulatory expectations while remaining operationally useful to engineering teams

- Red-teaming and adversarial testing frameworks identifying misuse, dual-use potential, and failure modes before deployment

- Production monitoring dashboards tracking fairness drift, performance degradation, and automated alerting thresholds

- Regulatory horizon scanning briefings translating proposed legislation into concrete product implications before enforcement deadlines

- Incident response playbooks with severity classification, stakeholder notification, and post-incident review procedures

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real AI governance problem — a fairness audit you need to defend to regulators, an ethics review board struggling with decision authority, a production model showing performance drift across demographic subgroups. It thinks like a director who's navigated fairness-transparency tradeoffs and embedded ethical checkpoints into MLOps pipelines at scale.

Bundles or prompts related to AI governance, regulatory compliance, and responsible AI practices.