Japan - Human-Centric AI Principles

Social Principles of Human-Centric AI

人間中心のAIの社会的原則

Japan

RAI-JP-NA-SPHAXXX-2019
Effective: 29 Mar 2019
In Force(In Force)As published at www8.cao.go.jp

Japan - Human-Centric AI Principles is In Force in Japan, according to www8.cao.go.jp. We have not yet been able to confirm the status.

PolicyGovernance and OversightFundamental Rights
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The "Social Principles of Human-Centric AI" is a non-binding national policy (soft law) published by Japan's Cabinet Office and adopted by the Integrated Innovation Strategy Promotion Council to set high-level values and principles for developing and deploying AI in Japanese society. It emphasizes human dignity, diversity and inclusion, sustainability, and seven operational principles (human-centric, education/literacy, privacy protection, security, fair competition, fairness/accountability/transparency, and innovation).

Summary

The Social Principles of Human-Centric AI (hereafter "the Principles") were prepared by the Council for Social Principles of Human-centric AI under Japan's Cabinet Office and formally adopted by the Integrated Innovation Strategy Promotion Council on March 29, 2019. The document sets a national, non-binding framework intended to guide government, industry, research institutions, and civil society in realizing an "AI-Ready Society" consistent with Japan's Society 5.0 vision. Unlike prescriptive law, the Principles are declaratory: they articulate three foundational values—dignity, diversity & inclusion, and sustainability—and seven operational principles: (1) human-centricity, (2) education and literacy for AI, (3) privacy protection, (4) ensuring security, (5) ensuring fair competition, (6) fairness, accountability and transparency, and (7) innovation.

The Principles treat AI broadly as "highly complex information systems" and stress that social systems, industrial structures, innovation ecosystems, governance, and human capacity must be adapted to realize AI benefits while minimizing harms. They recommend actions such as strengthening AI literacy and skills across the population, building interoperable data and digital infrastructures, safeguarding personal data and privacy, improving cyber and physical safety of AI systems, preventing market concentration and ensuring fair competition, and promoting transparency, explainability and accountability in design and deployment. The document also contains R&D and utilization guidance, calling for cross-disciplinary research, shared data infrastructure, public–private cooperation, and iterative evaluation.

Although the Principles are not directly enforceable, they have served as the foundation for subsequent Japanese guidance and self-regulatory work (including sectoral guidance by METI and the Ministry of Internal Affairs and Communications) and for Japan’s international engagement on AI governance (e.g., at the OECD, G20 and UNESCO). The document emphasizes voluntary stewardship and multi-stakeholder approaches rather than statutory bans, and it explicitly situates AI governance as a shared social responsibility—encouraging businesses, research organizations, government agencies, and civil society to adopt practices consistent with the Principles. For high-impact applications that implicate fundamental rights (healthcare decisions, employment screening, credit, law enforcement, etc.), the Principles call for heightened caution, transparency, human oversight and, where necessary, sectoral regulatory measures or conformity assessments under existing laws. Overall, the Social Principles reflect Japan’s soft-law, human-centric approach to AI governance: promoting innovation and international alignment while urging protections for dignity, rights and social sustainability.

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Overview

The "Social Principles of Human-Centric AI" is a policy document finalized by Japan's Integrated Innovation Strategy Promotion Council and published by the Cabinet Office to guide the ethical development and social implementation of AI. It establishes three core values—respect for human dignity, diversity & inclusion, and sustainability—and seven operational principles intended to shape both R&D and societal deployment of AI. The full English tentative translation is published by the Cabinet Office (see Social Principles of Human-Centric AI (tentative translation)) and the Japanese original and related Council materials are available on the Cabinet Secretariat and Cabinet Office web pages (for example, AI Strategy / AI policy pages). The document frames AI as part of Japan’s Society 5.0 agenda and is designed as soft law to foster a multi-stakeholder, iterative governance approach rather than immediate prescriptive regulation.

Definitions

The Principles do not attempt a narrow technical definition of AI; instead they treat AI as "highly complex information systems in general" that perform intelligent operations, possibly with autonomy, as components of broader information systems. Key normative terms used in the text include: "AI-Ready Society" (a society whose human capacity, institutions, industrial structures and governance are adapted to maximize AI benefits), "human-centric" (AI serves to augment human capabilities and respects human dignity), and "AI literacy" (public and professional knowledge and skills required to understand AI's advantages, limitations, biases, and safe use). The document distinguishes social principles (high-level values) from R&D and utilization principles (operational guidance for developers, deployers and public actors).

Governance and Institutional Framework

The Principles recommend a governance architecture based on collaboration across ministries, local governments, industry, research institutions, and civil society. The Cabinet Office (Council for Science, Technology and Innovation and the Integrated Innovation Strategy Promotion Council) serves as the coordinating hub referenced in the document. The policy foregrounds soft-law instruments—guidelines, sectoral codes of conduct, voluntary standards, and public–private fora—while acknowledging the need for legal frameworks where rights or safety are at stake. The Principles call for transparent stakeholder processes, periodic review of guidance, common data infrastructures to support interoperable systems, and institutional mechanisms to support AI literacy and workforce development. See the original document and Council materials at Cabinet Office tentative translation and the Council's AI pages at Cabinet Office AI Strategy.

Key Focus Areas

The Principles articulate seven operational domains that form the substance of Japan’s human-centric approach: (1) Human-Centric: AI must serve people’s well‑being and respect basic human rights and dignity; (2) Education & Literacy: broad-based AI literacy and specialized skills training are essential to empower citizens and professionals; (3) Privacy Protection: personal data use must be lawful, transparent and proportional; (4) Ensuring Security: cyber and physical safety of AI systems must be prioritized to prevent misuse and harm; (5) Fair Competition: policies should discourage anti-competitive concentration and promote open, interoperable markets and data portability; (6) Fairness, Accountability & Transparency: designers and operators should consider bias mitigation, explainability, documentation and mechanisms for redress; (7) Innovation: regulation should be balanced to avoid stifling innovation while protecting rights and public interests. Across these domains the Principles stress cross-cutting needs—data infrastructure, standardization, and public engagement—to operationalize values in concrete systems and services. For example, in healthcare and finance the document highlights the need for special caution given potential impacts on life, health, and economic status, and recommends layered safeguards including human oversight and sector-specific compliance measures.

Implementation Framework

Implementation in the Principles is purposely non-prescriptive and relies on multiple levers: government-led strategies (AI Strategy and follow-on plans), sectoral guidelines (from METI, MIC and other ministries), public–private partnerships, standard-setting bodies, research funding priorities, and capacity building. The document recommends establishing interoperable data frameworks to enable responsible data sharing, investing in education and lifelong learning to expand AI literacy, and encouraging industry to adopt documentation, testing and accountability practices. It also calls for promotion of R&D that combines technical excellence with social science, ethics and human–machine interface research. The Principles expect ministries to use existing laws where appropriate (e.g., personal data protection law, consumer protection, safety standards) and to rely on voluntary governance where innovation requires flexibility; they further envisage staged review and updating as technologies and societal impacts evolve.

Monitoring and Evaluation

The Principles recommend iterative monitoring through multi-stakeholder mechanisms rather than a single national regulator. They encourage the use of sectoral metrics, impact assessments for high‑risk applications, public reporting and voluntary audits to evaluate whether AI systems align with the Principles. The document suggests that government bodies coordinate regular reviews, collect examples of best practice and failure, and update guidance. For high-impact uses affecting fundamental rights, the Principles highlight the need for transparent evaluation, human oversight, and where necessary, legally backed oversight mechanisms. Japan’s subsequent guidance and working groups (e.g., AI Strategy meetings and ministerial guidelines) have implemented monitoring tools and stakeholder consultations informed by this document.

Penalties, Liability, and Appeals

As a soft-law instrument, the Principles do not prescribe specific penalties or administrative sanctions. Instead, they situate liability and redress within existing Japanese legal frameworks (civil liability, consumer protection, sectoral regulation, and criminal law where relevant) and recommend that sectoral legal instruments fill enforcement gaps for high-risk applications. The document urges developers and deployers to design accountability mechanisms (incident reporting, remediation procedures, consumer complaint channels) and supports the use of conformity assessments, certifications, and third‑party audit regimes for sensitive systems. The Principles thus act as a normative baseline that can inform future binding rules when necessary, while encouraging voluntary accountability practices and internal compliance by organizations.

Relationship to Other Instruments

The Principles are explicitly tied to Japan’s broader AI policy architecture, including the AI Strategy (2019 and subsequent updates), sectoral guidelines by the Ministry of Economy, Trade and Industry (METI), and utilization guidelines by the Ministry of Internal Affairs and Communications (MIC). They are also referenced in Japan’s engagement with international instruments (OECD AI Principles, G20 discussions, UNESCO processes). The document is marketed as a national consensus document that complements technical standards, sectoral laws (privacy, consumer protection, medical device regulation), and voluntary codes—serving as a touchstone for harmonizing those instruments and guiding future legislative or administrative measures.

International Alignment

Japan’s Principles align with major international AI governance trends: human-centric values (similar to EU and OECD principles), emphasis on innovation and industry cooperation (reflecting Japan's preference for soft law and industry-led measures), and active participation in multilateral fora (OECD, G20, UNESCO). The text also references international guidelines (for example, the EC High-Level Expert Group) and stresses interoperability and cooperation—including the Data Free Flow with Trust (DFFT) concept that Japan has promoted in international forums. The Principles intentionally aim to make Japan interoperable with international standards while allowing room for sectoral adaptation and incremental regulatory responses.

Implementation Timeline

EventDate
Establishment of Review Council and stakeholder consultations2018 (meetings across 2018-2019)
Integrated Innovation Strategy Promotion Council decision (document adoption)2019-03-29
Publication of English tentative translation (Cabinet Office)2019 (published online)
Subsequent AI Strategy and sectoral guidance development (METI, MIC)2019–2022 (iterative)

Sources and References

SourceType
Social Principles of Human-Centric AI (tentative translation) - Cabinet OfficePrimary Source
Cabinet Office: AI Strategy / AI pagesPrimary Source
Cabinet Secretariat: Human-centric AI CouncilPrimary Source

Requirements for a company

What an organisation has to do under Japan - Human-Centric AI Principles, at a glance. Not legal advice — the table below gives the provision and deadline for each item.

Must do

9
  • Ensure AI systems serve human well-being and respect basic human rights and dignity.Developers and deployers of AI systems
  • Ensure personal data use in AI systems is lawful, transparent, and proportional.Developers and operators of AI systems handling personal data
  • Prioritize the cyber and physical security of AI systems to prevent misuse and harm.Developers and operators of AI systems
  • Consider bias mitigation, explainability, documentation, and redress mechanisms for AI systems.Designers and operators of AI systems
  • Design and implement accountability mechanisms, including incident reporting and consumer complaint channels.Developers and deployers of AI systems
  • Apply special caution and layered safeguards, including human oversight, for AI in healthcare and finance.Developers and deployers of AI in healthcare and finance
  • +3 more in the table below

Must not do

0

Nothing in this category.

Should do

3
  • Use sectoral metrics, impact assessments, public reporting, and voluntary audits for high-risk AI applications.Developers and deployers of high-risk AI applications
  • Promote R&D that combines technical excellence with social science, ethics, and human-machine interface research.Research institutions and funding bodies
  • Coordinate regular reviews, collect best practices, and update guidance for AI governance.Government bodies

Should not do

0

Nothing in this category.

Who must do what

The obligations under Japan - Human-Centric AI Principles, most serious first. Not legal advice — verify against the official text before relying on it.

#WhoRequirementBy whenWhereSeverity
1Developers and deployers of AI systemsEnsure AI systems serve human well-being and respect basic human rights and dignity.
“AI must serve people’s well‑being and respect basic human rights and dignity”
Ongoing—Important
2Developers and operators of AI systems handling personal dataEnsure personal data use in AI systems is lawful, transparent, and proportional.
“personal data use must be lawful, transparent and proportional”
Ongoing—Important
3Developers and operators of AI systemsPrioritize the cyber and physical security of AI systems to prevent misuse and harm.
“cyber and physical safety of AI systems must be prioritized to prevent misuse and harm”
Before placing on market, Ongoing—Important
4Designers and operators of AI systemsConsider bias mitigation, explainability, documentation, and redress mechanisms for AI systems.
“designers and operators should consider bias mitigation, explainability, documentation and mechanisms for redress”
During design and operation—Important
5Developers and deployers of AI systemsDesign and implement accountability mechanisms, including incident reporting and consumer complaint channels.
“urge developers and deployers to design accountability mechanisms (incident reporting, remediation procedures, consumer complaint channels)”
Before placing on market—Important
6Developers and deployers of AI in healthcare and financeApply special caution and layered safeguards, including human oversight, for AI in healthcare and finance.
“in healthcare and finance the document highlights the need for special caution... recommends layered safeguards including human oversight”
Before placing on market, Ongoing—Important
7Industry developing and deploying AIAdopt documentation, testing, and accountability practices for AI systems.
“encouraging industry to adopt documentation, testing and accountability practices”
Ongoing—Important
8Government, industry, and educational institutionsInvest in education and lifelong learning to expand broad-based AI literacy.
“investing in education and lifelong learning to expand AI literacy”
Ongoing—Important
9Government bodies and industryEstablish interoperable data frameworks to enable responsible data sharing.
“recommends establishing interoperable data frameworks to enable responsible data sharing”
Ongoing—Important
10Developers and deployers of high-risk AI applicationsUse sectoral metrics, impact assessments, public reporting, and voluntary audits for high-risk AI applications.
“encourage the use of sectoral metrics, impact assessments for high‑risk applications, public reporting and voluntary audits”
Ongoing—Recommended
11Research institutions and funding bodiesPromote R&D that combines technical excellence with social science, ethics, and human-machine interface research.
“calls for promotion of R&D that combines technical excellence with social science, ethics and human–machine interface research.”
Ongoing—Recommended
12Government bodiesCoordinate regular reviews, collect best practices, and update guidance for AI governance.
“The document suggests that government bodies coordinate regular reviews, collect examples of best practice and failure, and update guidance.”
Ongoing—Recommended

© Regulations.AI · updated on 20 Sep 2026