A-LIGN转发了
VP of Strategy and Innovation at A-LIGN | TEDx Speaker | Forbes Technology Council | AI Ethicist | ISO/IEC JTC1/SC42 Member
??Bridging Compliance and Strategy: How, Why, and What?? By integrating measurement methodologies inspired by Doug Hubbard's “How to Measure Anything” and John Doerr’s OKRs from “Measure What Matters”, organizations can quantify ethical progress and drive meaningful change leveraging #ISO standards. ? Using ISO Standards with Empirical Measures 1. Fairness as a Measurable Outcome ISO/IEC TS 12791 offers practical tools to identify and reduce bias in AI systems.? ?Example OKR:? ??????Objective: Ensure AI outputs are equitable.? ??????Key Results:? ???- Reduce demographic disparities in system recommendations by 20%.? ???- Conduct quarterly audits of datasets for bias detection. ??Hubbard's Insight: ?Even seemingly intangible metrics, like fairness, can be quantified. Use proxy variables like decision consistency across demographics to track progress. 2. Transparency Through Explainability ISO5339 emphasizes transparency by guiding organizations in creating explainable decision pathways.? ?Example OKR:? ??????Objective: Improve user trust in AI systems.? ??????Key Results:? ???- Achieve 90% satisfaction in user surveys related to system explainability.? ???- Implement traceability mechanisms in 100% of deployed systems. ??Hubbard's Insight: Measuring trust can use tools like Net Promoter Scores (#NPS) or user feedback metrics. Quantifying subjective experiences, such as transparency, makes iterative improvements possible. 3. Accountability in Governance ISO/IEC 38507 defines governance frameworks to ensure clear accountability for AI decisions.? ?Example OKR:? ??????Objective: Establish organizational accountability for AI outcomes.? ??????Key Results:? ???- Reduce the number of unresolved AI governance incidents to zero.? ???- Conduct biannual accountability reviews with stakeholder input. ??Hubbard's Insight: Accountability can be quantified by tracking the resolution time for identified governance issues or through compliance rates in internal audits. 4. Continuous Adaptation and Resilience ISO42001 and ISO/IEC 23894 support lifecycle monitoring to adapt to societal changes and emerging risks.? ?Example OKR:? ??????Objective: Maintain alignment with evolving ethical standards.? ??????Key Results:? ???- Update AI risk assessments every 3 months.? ???- Maintain 95% compliance with new regulatory requirements. ??Hubbard's Insight: Measuring adaptability involves monitoring the time taken to incorporate new standards and the percentage of systems updated within defined timelines. ?Combining Hubbard’s Metrics with Doerr’s OKRs Doerr’s OKRs provide a clear structure for setting ambitious yet achievable objectives, while Hubbard’s methodology ensures that even qualitative goals, like ethical AI, are measured empirically: ?Use OKRs to define the “What” (e.g., "Improve fairness in AI systems"). ?Apply Hubbard’s approach to measure the “How” (e.g., using decision parity or user sentiment as proxy metrics for fairness).