Policy

Japan Adopts AI Training-Data Disclosure Principles, Joining Global Push for Transparency

Japan's government adopted guiding principles on intellectual property protection for generative AI operators on August 26, calling on AI businesses to publicly disclose training data types, collection methods, and copyright-infringement risk indicators.

M
By Marcus Holloway Enterprise Software Editor
August 26, 2026 / 5 min read

Japan's government adopted guiding principles on intellectual property protection for generative AI operators on August 26, calling on AI businesses to disclose an outline of the data and methods used to train their AI tools. Intellectual Property Strategy Minister Kimi Onoda announced the Principles Code at a news conference in Tokyo, framing the voluntary framework as a tool to boost AI transparency while protecting intellectual property rights and promoting innovation. While not legally binding, the code covers domestic AI businesses and overseas operators that provide AI systems and services in Japan.

What the Code Requires

Businesses that accept all or part of the code will notify the government and disclose, on their websites, the learning processes, types of learning data, and methods of collecting such data for their generative AI models. They will also make public whether the learning data includes information that could lead to copyright infringement if so requested by AI users and rights holders, provided certain conditions are met. The disclosure obligations apply to text, image, and other material types used as training inputs, addressing long-standing concerns that creative works are being ingested into AI models without permission.

Why It Matters

The Japanese code lands amid a wave of comparable moves by other governments. The European Union's AI Act, which entered into force in 2024 and is being phased in through 2027, requires general-purpose AI providers to disclose training data summaries under the Copyright Directive. South Korea on August 24 announced national AI ethics principles with three core values and seven guidelines, although experts noted those principles lack binding force. The United States has no federal AI training-data disclosure mandate, although individual lawsuits and FTC consent decrees have produced partial disclosures from major model providers.

Enforcement and Limits

Because the Japanese code is voluntary, its effectiveness depends on adoption. The government's strategy is reputational — businesses that refuse to participate in disclosure may face public pressure and loss of procurement eligibility — rather than punitive. Onoda said the government would "respond appropriately," including considering further measures if voluntary adoption proves insufficient. The code's coverage of overseas operators that serve the Japanese market is significant: it effectively means that any global AI provider serving Japanese customers must consider whether to comply with Japanese disclosure expectations even if its home jurisdiction does not require it.

What to Watch Through Year-End

Three checkpoints follow. The first wave of Japanese disclosures from major AI providers — particularly OpenAI, Anthropic, Google, and domestic players like SoftBank-affiliated Sakana AI and NTT — will be the first test of whether voluntary compliance produces meaningful transparency. Japan's planned Copyright Act amendments, expected to be discussed in the Diet this fall, will determine whether voluntary disclosure gives way to binding copyright safe-harbor requirements. And the bilateral AI dialogue between Japan and the EU on training-data transparency standards, which the METI and EU Commission's DG CONNECT are expected to schedule before year-end, will set the template for whether Asian and European transparency regimes can interoperate.

Tagged

Comments (0)

No comments yet. Be the first to share your thoughts.