Securiti leads GigaOm's DSPM Vendor Evaluation with top ratings across technical capabilities & business value.

View

Japan’s Instructions For Generative AI Services

Contributors

Anas Baig

Product Marketing Manager at Securiti

Maria Khan

Data Privacy Legal Manager at Securiti

FIP, CIPT, CIPM, CIPP/E

Listen to the content

This post is also available in: Brazilian Portuguese

Generative AI continues to expand in both capabilities and possibilities. Whether it’s writing a modern Shakespearean play or producing a unique source code for an interactive website, it can all be done within a few seconds.

While this phenomenon presents many opportunities, one, particularly critical challenge it poses is its reliance on a nearly endless stream of data collection. The more data it collects and learns, the more efficient and effective it becomes.

However, data collection on such a scale is a highly volatile proposition with an increased likelihood of users’ data privacy rights being violated. Governments worldwide have become increasingly active in regulating various aspects of AI, particularly its data collection mechanisms.

Brief Background

In Japan, on May 20, 2023, the Personal Information Protection Commission (PPC) laid down important considerations and instructions for all major stakeholders in relation to Generative AI services (services that use AI to generate sentences, images, etc., in response to questions, work instructions (prompt input), etc.).

These include instructions for business operators, administrative agencies, and regular users that use such generative AI services. These instructions are meant to secure the appropriate rights and interests of users through the appropriate handling of users’ personal data in line with the Act on the Protection of Personal Information (APPI) within the context of generative AI services.

Based on Article 147 of the same Act, a blanket warning was issued to all generative AI services, particularly OpenAI that developed ChatGPT, regarding their collection, storage, and usage of users’ personal data and information.

Lastly, the Committee also states that as new concerns are recognized in the future, additional measures and instructions will be released as necessary, owing to the highly dynamic nature of generative AI services and their data collection capabilities.

Instructions for Business Operators Handling Personal Data

Here are the instructions specific to the use of generative AI services by business operators:

  • If personal data or information needs to be provided to a generative AI service, the business operator must ensure that the content of such personal data is limited to that necessary to achieve a specified purpose;
  • No personal data may be provided to a generative AI service for usage in a context not consented to by the user, as this may result in a violation of the Act on the Protection of Personal Information (APPI);
  • Similarly, the usage of personal data for any purposes other than generating responses to a prompt, such as machine learning, may also lead to the violation of the APPI.

Instructions for Administrative Agencies Handling Personal Data

Here are the instructions specific to the use of generative AI services by administrative agencies:

  • If personal data or information needs to be provided to a generative AI service, the administrative agency must ensure that it provides as minimal personal data as possible for the specified purpose;
  • As required for businesses, administrative agencies should also ensure that any personal data provided to a generative AI service should not be used for any purpose other than generating responses to prompts;
  • The administrative agencies must ensure that any organization providing such generative AI services does not retain any personal data or information for machine learning purposes.

Instructions for General Users

Here are some key considerations related to the use of generative AI services by the general population as released by the Committee:

  • The generative AI service may use the personal information provided for its own machine-learning purposes. Moreover, such information may also be statistically linked with other information and output from the service with no guarantee of accuracy of the content. Therefore, users should be cognizant of the risks involved when providing personal information to generative AI services;
  • The generative AI services may produce responses that contain inaccurate content, as the sentences generated by such services are based on probabilistic correlation. Thus users should make appropriate judgments based on such risks;
  • Additionally, the users must fully go through and check the terms of use, privacy policy, and other notices/disclosures that detail the functions of the generative AI services to make appropriate decisions regarding what information should be provided to the service.

Additional Requirements

Here are some additional requirements placed on generative AI services by the Committee:

  • If personal data or information needs to be collected for machine learning purposes, the following four steps must be thoroughly undertaken:
    • Ensure that personal information requiring special care is exempt from the information being collected;
    • As soon as possible after the information is collected, take measures to ensure that as much quantum of personal information requiring special care is reduced as possible;
    • If, even after the implementation of the foregoing measures, it is discovered that the collected information still contains personal information requiring special care, initiate prompt actions to ensure such information is deleted or it is made impossible to identify a specific individual through such information before it is used as part of a training dataset;
    • If a user or the Personal Information Protection Commission (PPC) requests or instructs a halt to the collection of personal information from a specific site or third party, such requests or instructions must be complied with unless there is a justifiable reason for refusal.
  • A user should be allowed to consent to the use of their personal information requiring special care for machine learning. If a user does not consent to the foregoing processing purpose, the generative AI service should not use their personal information for this purpose unless there is a justifiable reason.

How Can Securiti Help

Generative AI services rely on data collection. It’s the life and blood of this technological leap. However, it is just as important for these services to adhere to their data collection and processing obligations in light of the plethora of data protection legislation globally.

These laws place different obligations on those collecting and processing the data. As specific AI laws and regulations are only expected to proliferate moving forward, automation offers the best way for generative AI services to remain compliant with their data protection obligations.

Securiti is a leader in providing enterprise data privacy, security, governance, and compliance solutions.

For example, the PrivacyCenter.Cloud supports enterprises in their journey toward compliance with the Japanese APPI through automation, enhanced data visibility, and identity linking. Not only does it allow for efficient compliance, but it does so in an incredibly user-friendly manner, with its central dashboard being both easy to navigate and use.

Request a demo today and learn more about how Securiti can help you comply with the APPI and any other major data regulation globally.

Join Our Newsletter

Get all the latest information, law updates and more delivered to your inbox


Share


More Stories that May Interest You

Videos

View More

Mitigating OWASP Top 10 for LLM Applications 2025

Generative AI (GenAI) has transformed how enterprises operate, scale, and grow. There’s an AI application for every purpose, from increasing employee productivity to streamlining...

View More

DSPM vs. CSPM – What’s the Difference?

While the cloud has offered the world immense growth opportunities, it has also introduced unprecedented challenges and risks. Solutions like Cloud Security Posture Management...

View More

Top 6 DSPM Use Cases

With the advent of Generative AI (GenAI), data has become more dynamic. New data is generated faster than ever, transmitted to various systems, applications,...

View More

Colorado Privacy Act (CPA)

What is the Colorado Privacy Act? The CPA is a comprehensive privacy law signed on July 7, 2021. It established new standards for personal...

View More

Securiti for Copilot in SaaS

Accelerate Copilot Adoption Securely & Confidently Organizations are eager to adopt Microsoft 365 Copilot for increased productivity and efficiency. However, security concerns like data...

View More

Top 10 Considerations for Safely Using Unstructured Data with GenAI

A staggering 90% of an organization's data is unstructured. This data is rapidly being used to fuel GenAI applications like chatbots and AI search....

View More

Gencore AI: Building Safe, Enterprise-grade AI Systems in Minutes

As enterprises adopt generative AI, data and AI teams face numerous hurdles: securely connecting unstructured and structured data sources, maintaining proper controls and governance,...

View More

Navigating CPRA: Key Insights for Businesses

What is CPRA? The California Privacy Rights Act (CPRA) is California's state legislation aimed at protecting residents' digital privacy. It became effective on January...

View More

Navigating the Shift: Transitioning to PCI DSS v4.0

What is PCI DSS? PCI DSS (Payment Card Industry Data Security Standard) is a set of security standards to ensure safe processing, storage, and...

View More

Securing Data+AI : Playbook for Trust, Risk, and Security Management (TRiSM)

AI's growing security risks have 48% of global CISOs alarmed. Join this keynote to learn about a practical playbook for enabling AI Trust, Risk,...

Spotlight Talks

Spotlight 11:18

Rewiring Real Estate Finance — How Walker & Dunlop Is Giving Its $135B Portfolio a Data-First Refresh

Watch Now View
Spotlight 13:38

Accelerating Miracles — How Sanofi is Embedding AI to Significantly Reduce Drug Development Timelines

Sanofi Thumbnail
Watch Now View
Spotlight 10:35

There’s Been a Material Shift in the Data Center of Gravity

Watch Now View
Spotlight 14:21

AI Governance Is Much More than Technology Risk Mitigation

AI Governance Is Much More than Technology Risk Mitigation
Watch Now View
Spotlight 12:!3

You Can’t Build Pipelines, Warehouses, or AI Platforms Without Business Knowledge

Watch Now View
Spotlight 47:42

Cybersecurity – Where Leaders are Buying, Building, and Partnering

Rehan Jalil
Watch Now View
Spotlight 27:29

Building Safe AI with Databricks and Gencore

Rehan Jalil
Watch Now View
Spotlight 46:02

Building Safe Enterprise AI: A Practical Roadmap

Watch Now View
Spotlight 13:32

Ensuring Solid Governance Is Like Squeezing Jello

Watch Now View
Spotlight 40:46

Securing Embedded AI: Accelerate SaaS AI Copilot Adoption Safely

Watch Now View

Latest

Securiti Powers Sovereign AI in the EU with NVIDIA View More

Securiti Powers Sovereign AI in the EU with NVIDIA

The EU has taken the lead globally in ensuring that the power of AI systems is harnessed for the overall wellbeing of human citizens...

The Risks of Legacy DLP: Why Cloud Security Needs DSPM View More

The Risks of Legacy DLP: Why Cloud Security Needs DSPM

82% of 2024 data breaches involved cloud data, raising concerns about the effectiveness of legacy data loss prevention (DLP) solutions in today's cloud-centric data...

Data Classification: A Core Component of DSPM View More

Data Classification: A Core Component of DSPM

Data classification is a core component of DSPM, enabling teams to categorize data based on sensitivity and allocate resources accordingly to prioritize security, governance,...

9 Key Components of a Strong Data Security Strategy View More

9 Key Components of a Strong Data Security Strategy

Securiti’s latest blog breaks down the 9 key components of a robust data security strategy and explains how it helps protect your business, ensure...

Beyond DLP: Guide to Modern Data Protection with DSPM View More

Beyond DLP: Guide to Modern Data Protection with DSPM

Learn why traditional data security tools fall short in the cloud and AI era. Learn how DSPM helps secure sensitive data and ensure compliance.

Mastering Cookie Consent: Global Compliance & Customer Trust View More

Mastering Cookie Consent: Global Compliance & Customer Trust

Discover how to master cookie consent with strategies for global compliance and building customer trust while aligning with key data privacy regulations.

From AI Risk to AI Readiness: Why Enterprises Need DSPM Now View More

From AI Risk to AI Readiness: Why Enterprises Need DSPM Now

Discover why shifting focus from AI risk to AI readiness is critical for enterprises. Learn how Data Security Posture Management (DSPM) empowers organizations to...

The European Health Data Space Regulation View More

The European Health Data Space Regulation: A Legislative Timeline and Implementation Roadmap

Download the infographic on the European Health Data Space Regulation, which features a clear timeline and roadmap highlighting key legislative milestones, implementation phases, and...

View More

Modern DSPM for Dummies: A Comprehensive Guide

Modern DSPM for Dummies is a comprehensive guide that explores the benefits, core capabilities, and the critical need for modern data security posture management.

Gencore AI and Amazon Bedrock View More

Building Enterprise-Grade AI with Gencore AI and Amazon Bedrock

Learn how to build secure enterprise AI copilots with Amazon Bedrock models, protect AI interactions with LLM Firewalls, and apply OWASP Top 10 LLM...

What's
New