Clauses 6 + 6.1 establish ethical values elicitation and prioritisation. Per public IEEE 7000-2021 abstract + Wikipedia + academic literature (full IEEE text NOT reproduced): elicit values from stakeholders covering categories: human autonomy + beneficence + non-maleficence + justice + dignity + privacy + transparency + accountability + fairness + sustainability + wellbeing + cultural sensitivity + human rights. Value prioritisation: multi-criteria decision analysis + analytic hierarchy process (AHP) + value-focused thinking + trade-off analysis when values conflict; precedence rules; ethical frameworks (consequentialism + deontology + virtue ethics + care ethics + capability approach) selection per context. IEEE 7000 family integration: IEEE 7001 Transparency (transparency levels per stakeholder type + technical means + user interfaces); IEEE 7002 Data Privacy Process (privacy by design + GDPR + ISO/IEC 27701 + privacy impact assessment); IEEE 7003 Algorithmic Bias Considerations (bias identification + measurement + mitigation per Aequitas + Fairlearn + IBM AI Fairness 360 + demographic parity + equal opportunity + equalised odds + individual fairness); IEEE 7010 Wellbeing Metrics (psychological + social + physical wellbeing measures); IEEE 7007 Ontologies for Ethically Driven Robotics. Bias mitigation throughout system lifecycle: training data + algorithm + deployment + post-deployment monitoring + demographic parity + intersectional analysis. Privacy protection in AI training data: differential privacy + federated learning + synthetic data + minimisation + anonymisation + pseudonymisation + GDPR Article 25 by design + IEEE 7002. Coordinates with EU AI Act fundamental rights impact assessment (FRIA) + NIST AI RMF GOVERN + GDPR + ISO/IEC 23894. IEEE 7000 Values + Prioritisation + Family Integration applies.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.