Accountability (Sekinin 責任) is the seventh of 10 Principles per Japan AI Guidelines for Business + addresses organisational governance + clear responsibility allocation + stakeholder engagement + regulatory compliance across AI lifecycle. (1) Accountability Principle Definition: (a) clear responsibility allocation across developer + provider + user roles; (b) governance structures + decision rights; (c) chain of accountability traceable to senior management; (d) regulatory + civil + ethical accountability. (2) AI Governance Structure: (a) Board oversight + AI Strategy approval; (b) AI Strategy Officer / Chief AI Officer (CAIO) emerging role; (c) AI Ethics Committee - diverse membership + advisory; (d) AI Risk Committee - operational risk + compliance; (e) DPO Data Protection Officer (APPI) + AI Officer coordination; (f) CISO + Cybersecurity intersection; (g) Privacy + Legal + Compliance integration; (h) Business Unit AI Champions / Stewards. (3) AI Inventory + Catalogue: (a) Comprehensive AI System Registry - all AI in use including foundation model APIs; (b) Per-System metadata - purpose + risk tier + lifecycle stage + stakeholders + data sources + monitoring; (c) Foundation Model Dependencies + supply chain; (d) Update + retraining log; (e) Inventory governance - quarterly review + sign-off; (f) Public-facing AI disclosure (emerging best practice). (4) Board Reporting: (a) Quarterly AI Risk + Compliance reporting to Board / Audit Committee; (b) Annual AI Strategy + Performance review; (c) High-risk AI incident immediate escalation; (d) Investor + ESG reporting on AI; (e) ESG metric integration - AI ethics + diversity + sustainability; (f) Annual AI Report public disclosure (emerging best practice). (5) Tone at the Top: (a) CEO + Board signed AI Ethics Statement; (b) Annual CEO message on AI responsibility; (c) Senior management visible commitment; (d) Performance metric integration; (e) Compensation alignment with AI ethics outcomes; (f) Anti-retaliation for whistleblowers. (6) Stakeholder Engagement: (a) Customer + User feedback mechanisms; (b) Affected non-user stakeholder consultation; (c) Civil society + NGO engagement; (d) Academic partnership; (e) Industry self-regulation participation; (f) Regulator engagement - METI + MIC + PIPC + AISI + sector regulators; (g) Public commentary on regulatory proposals; (h) Multi-stakeholder forums - Hiroshima AI Process + OECD + UN. (7) Roles + Responsibilities (RACI for AI): (a) Senior Management - strategy + accountability; (b) AI Ethics Committee - advisory + escalation; (c) DPO/AI Officer - day-to-day oversight + reporting; (d) Risk Owner per AI system - operational accountability; (e) Developer - implementation; (f) Auditor - independent assurance; (g) Business User - appropriate use. (8) Regulatory Compliance Tracking: (a) Multi-regulator landscape - APPI (PIPC) + ISMS + Cybersecurity + Sector-Specific (FSA + MHLW + MLIT + MEXT) + International (EU AI Act + UK + US); (b) Sector mapping - financial + healthcare + automotive + education + employment; (c) Cross-jurisdictional compliance (Japan operations + international users); (d) Regulatory horizon scanning - AI Bill + sector guidance + international developments; (e) Compliance calendar + obligation tracking; (f) Legal + regulatory affairs team. (9) AI Incident Reporting + Learning: (a) Internal incident reporting mechanism; (b) AISI + METI voluntary notification; (c) Sector regulator notification where required; (d) PIPC notification for personal data implications; (e) Customer + affected stakeholder notification; (f) Root cause analysis + post-mortem; (g) Lessons learned + improvement; (h) Industry sharing (where appropriate). (10) Third-Party AI Supplier Assurance: (a) Vendor + Sub-processor due diligence including AI ethics; (b) Foundation model provider evaluation - AISI + independent audit; (c) Contractual obligations - AI Guidelines compliance + audit rights + incident notification; (d) Supply chain transparency - upstream dependencies; (e) Concentration risk - foundation model dependency; (f) Open source AI considerations; (g) Cloud AI service provider obligations. (11) Audit + Assurance: (a) Internal audit annual AI program review; (b) External audit emerging (no formal certification yet); (c) ISO/IEC 42001 AI Management System certification (gaining traction Japan); (d) AISI evaluation for frontier models; (e) Sector-specific audit (financial + healthcare); (f) Customer audit rights; (g) Bug Bounty + responsible disclosure programs. (12) Education + Literacy (8th Principle): (a) AI literacy across organisation; (b) Role-specific AI training; (c) Senior management AI education; (d) Customer + user AI literacy support; (e) Industry-wide AI literacy investment. Coordinates with ISO/IEC 42001 AI Management System (October 2023) + ISO/IEC 23894 AI Risk + ISO/IEC 38507 AI Governance + NIST AI RMF + AI Verify (Singapore) + AISI evaluations + AISI Network + APPI Personal Information Protection Commission + Japan ISMS + Financial Services Agency AI Guidelines + Pharmaceutical and Medical Devices Agency + Ministry of Land Infrastructure Transport and Tourism + Japan Deep Learning Association + Robot Revolution Industrial Cooperation + ICTPF + JFTC + Japan AI Bill 2024-2026 + Hiroshima AI Process + OECD AI Principles + EU AI Act + UK AI Bill + US AI EO 14110 (revoked Jan 2025). Japan AI Guidelines Accountability + Governance applies.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.