OpenAI API and the Personal Information Protection Act: The “Opt-out Trap” LLM Developers Fall Into and the Reality of Practical Risks

“Since it’s via the API, it won’t be used for training. Therefore, there are no legal issues with inputting personal information.” — If your team is proceeding with a project based on this assumption, you may be stepping on an extremely dangerous “governance landmine.” This is because the “existence of data training” in OpenAI’s terms and the “discipline” required by Japan’s Act on the Protection of Personal Information (hereinafter referred to as APPI) are matters on entirely different dimensions.

Currently, in the Japanese LLM development scene, discussions regarding the handling of personal information when using APIs are rapidly surfacing. In particular, the boundary between “third-party provision” and “entrustment” is an area that many engineers overlook. In this article, I will unpack the core of how to balance technical implementation with legal compliance from the perspective of a tech evangelist.

The biggest misunderstanding in LLM development is the perception that "opt-out settings (prohibiting training) = legal safety." Under Japan's APPI, the act of "providing" data to an overseas operator requires notification or consent from the user, or a strict definition of an entrustment relationship, even if the data is not used for training. Especially when sending data to a US company like OpenAI, the point that the Japanese concept of "entrustment" may not apply as-is constitutes a governance loophole that engineers should be most wary of.

In OpenAI’s API (Enterprise plan and standard API tiers), the terms clearly state that input data will not be used for model retraining. However, this is merely a promise within a “contract (Terms of Service)” with a single company, OpenAI.

From the perspective of Japan’s APPI, even before considering the use of the data, the process of “moving data to an external party (especially a foreign one)” itself is subject to regulation. There are two major hurdles here.

The Debate: “Entrustment” or “Third-Party Provision”?

Under domestic law, when leaving the handling of personal data to an external party, if it is deemed “entrustment” (outsourcing), individual consent from the person is not required (Article 27, Paragraph 1, Item 4). However, if it is judged that “appropriate supervision” as defined by Japanese law is effectively impossible for a platformer like OpenAI, there is a risk it will be deemed “third-party provision.” In that case, individual user consent would, in principle, be required.

Provision to a Third Party in a Foreign Country (Article 31)

OpenAI is a US corporation, and its servers are located outside of Japan. Due to amendments in the law, when providing personal data to an operator in a foreign country, an obligation arises to provide users with information regarding the legal systems of the destination country and the measures taken for personal information protection. Even with settings that “do not use data for training,” the act of transmitting the data itself triggers this obligation—a point engineers must keep firmly in mind.

2. Three “Governance Gaps” Facing Developers

What specific risks lurk at the technical implementation stage? The main concerns can be summarized into the following three points:

① Unintentional Inclusion of Personal Information (PII Leakage)

It is impossible to completely prevent cases where users voluntarily input names, addresses, or highly sensitive personal information through prompts. Sending these to an API without filtering is nothing less than building a system that continuously performs the “foreign provision of personal data” unintentionally.

② Eligibility of OpenAI as an “Entrustee”

To establish “entrustment” under Japanese law, the entrusting party (the developer) has an obligation to supervise the entrustee (OpenAI). However, OpenAI’s terms are in a “Take it or leave it” format. Given the current situation where individual audit rights or instructions for safety management measures are difficult to enforce, the concern that the legal framework for “entrustment” remains fragile cannot be dismissed.

③ The Exception of Abuse Monitoring

Even if training is not conducted, OpenAI reserves the right to retain data for up to 30 days to prevent service abuse. It is necessary to reconfirm whether this “temporary storage” falls within the scope of the privacy policy agreed upon with the user and whether its purpose is clearly stated.

To minimize these risks and ensure product sustainability, here are three actions professionals should consider:

Mitigation PlanProsCons
Use Azure OpenAI ServiceProcessing can be done in Japan-based regions based on commercial contracts with Microsoft. Establishing a legal “entrustment” relationship becomes significantly easier.Increased configuration complexity and changes in cost structure compared to direct API use.
Implement PII Masking (Anonymization)Use libraries like Microsoft Presidio to mask personal information before transmission. Data can be sent as “non-personal information,” which falls outside legal regulation.Risk of reduced LLM contextual understanding or accuracy due to replacement of proper nouns.
Adopt Local LLMs (e.g., Llama 3)Enables “full on-premises” operation where data never leaves the internal network. Can fundamentally eliminate APPI risks.Challenges include securing high-performance GPU resources and optimizing operation/inference speed.

FAQ: Concerns in Practice

Q: Is it enough to just write “We use AI services” in the privacy policy? A: No, it is insufficient. Based on the amended law, you must specifically disclose “to which country” and “to what kind of operator” the data is provided, as well as the legal systems of that country.

Q: If I anonymize the data, is it exempt from legal regulations? A: If it is elevated to “Anonymously Processed Information” (where specific individuals cannot be identified), it is exempt. However, note that “Pseudonymously Processed Information” (where names are merely redacted) is still subject to certain regulations.

Q: Is the OpenAI Enterprise plan “safe” legally? A: While contractual protection is stronger, the scheme of “provision to a third party in a foreign country” remains the same. The process of confirming accountability to users and alignment with domestic law is still mandatory.

Conclusion: Engineers Must Embrace “Privacy by Design”

The fact that something is “technically possible” is not synonymous with it being “legally permissible.” An outstanding engineer in the era of Generative AI is not merely someone who can masterfully use APIs, but someone who can incorporate compliance as an essential element of design (Privacy by Design).

If you want to truly scale the product you are developing, you should immediately review your company’s privacy policy and consider migrating to Azure OpenAI or implementing masking processes. Neglecting this is equivalent to binding the wings of innovation with the heavy chains of legal risk.

The evolution of AI technology is moving at a speed that outpaces legal updates. This is precisely why we, as tech evangelists, must constantly update our understanding of the latest legal interpretations and technical trends.

This article is also available in Japanese.