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AI Governance & Data Ethics ESG Checklist

Este checklist está em inglês.

Assess responsible AI and data ethics governance as an emerging ESG topic, covering accountability, fairness, transparency, and risk management under ISO/IEC 42001 and the NIST AI RMF.

ISO/IEC 42001:2023NIST AI Risk Management FrameworkOECD AI Principles

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Governance & Accountability

  • Is there a board-endorsed responsible AI policy and assigned accountability for AI oversight? *
  • Is an inventory of AI systems maintained with risk classification? *
  • Are roles, responsibilities, and escalation paths for AI risks defined? *

Data Ethics & Privacy

  • Are training and operational data governed for lawful basis, consent, and minimization? *
  • Is data lineage, quality, and representativeness assessed to reduce bias? *
  • Are privacy-enhancing controls applied to personal data used by AI systems? *

Fairness & Transparency

  • Are AI systems tested for bias and disparate impact across affected groups? *
  • Is transparency provided to affected users, including disclosure that AI is in use? *
  • Is explainability appropriate to the risk level and context of the system? *

Risk Management & Human Oversight

  • Are AI-specific risks (safety, security, robustness) assessed before and during deployment? *
  • Is meaningful human oversight and the ability to intervene or disable systems ensured? *
  • Are high-risk uses evaluated against emerging regulation such as the EU AI Act? *

Monitoring & Disclosure

  • Are AI systems monitored post-deployment for drift, incidents, and performance degradation? *
  • Is an AI incident response and reporting process in place? *
  • Are responsible-AI practices disclosed in ESG or sustainability reporting? *

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