Energy Law and AI Constitutional Constraints in Energy Governance in Japan

1. Introduction

The use of artificial intelligence (AI) in energy governance raises important constitutional and administrative-law questions in Japan. AI can assist the government, electricity regulators, utilities, and nuclear-safety authorities in forecasting electricity demand, managing power grids, detecting equipment failures, allocating energy resources, monitoring emissions, and evaluating energy projects.

However, the use of AI does not exempt Japanese public authorities from constitutional guarantees, statutory requirements, administrative procedures, or judicial review. An AI system cannot independently acquire governmental authority merely because its predictions are technically sophisticated.

Japan's legal framework does not consist of one comprehensive statute governing all AI-assisted energy decisions. Instead, relevant constraints arise from the Constitution of Japan, energy legislation, administrative procedure, nuclear regulation, environmental law, information-protection rules, and the general principles governing the exercise of public power.

The central legal question is:

How can Japan use AI to improve energy security, efficiency, and decarbonization while preserving constitutional rights, democratic accountability, procedural fairness, and the rule of law?

This explanation examines the constitutional framework, relevant statutes, judicial decisions, practical applications, and unresolved legal issues.

2. Constitutional foundations

Article 13 — Individual dignity and personal rights

Article 13 protects respect for individuals and their rights to life, liberty, and the pursuit of happiness, subject to the public welfare. It is relevant where AI-based energy systems process household electricity data, infer residents' behavior, or make consequential decisions affecting individuals.

Article 14 — Equality before the law

AI-assisted energy subsidies, disconnection-risk assessments, demand-response programs, and renewable-energy incentives should not produce unjustified discriminatory outcomes. A model that systematically disadvantages rural households or particular categories of consumers may raise equality concerns, depending on the decision and its effects.

Article 31 — Due process

Article 31 states that no person shall be deprived of life or liberty, or subjected to other criminal punishment, except according to procedure established by law. Its direct application to ordinary energy-administration decisions requires careful analysis; it should not automatically be treated as a universal hearing right in every regulatory dispute. Related procedural protections may arise from specific statutes and broader constitutional principles.

Articles 41 and 65 — Legislative and executive authority

Article 41 identifies the Diet as the highest organ of state power and the sole law-making organ of the State. Article 65 vests executive power in the Cabinet. Together, they support the principle that AI cannot independently create binding energy rules or replace legally authorized decision-makers.

Articles 76 and 81 — Judicial independence and constitutional review

Article 76 protects judicial authority, while Article 81 gives the Supreme Court the power to determine the constitutionality of laws, orders, regulations, and official acts. AI-supported government decisions remain subject to judicial scrutiny where the relevant legal requirements for review are met.

Article 29 — Property rights

Energy infrastructure projects may affect landowners, businesses, and communities through compulsory acquisition, restrictions, or other legally authorized measures. AI-generated assessments cannot independently justify a property restriction or replace statutory procedures and applicable compensation requirements.

These provisions do not expressly regulate AI as a distinct technology. Their importance lies in applying established constitutional principles to new forms of automated decision-making.

3. Japan's AI Act and energy legislation

3.1 Act on Promotion of Research and Development and Utilization of AI-Related Technologies, 2025

Japan enacted the Act on Promotion of Research and Development and Utilization of AI-Related Technologies (Act No. 53 of 2025). It was promulgated on 4 June 2025 and fully brought into force on 1 September 2025. The Act promotes AI research, development, and utilization and establishes a framework for coordinated national AI policy.

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Its significance for energy governance includes:

Promoting AI applications for electricity-demand forecasting and grid optimization.

Supporting research into AI for renewable energy, storage, and energy efficiency.

Encouraging cooperation among government, research institutions, and AI-utilizing businesses.

Addressing concerns about the appropriate use of AI through policy, research, and coordination.

Important limitation: This is principally a framework and promotion law, not a comprehensive AI licensing statute for energy regulators. It does not, by itself, establish a universal requirement for human review of every AI decision, nor does it replace nuclear-safety legislation, electricity regulation, or constitutional review.

The Act's provisions concerning appropriate use of AI must therefore be read alongside the specific legislation governing the relevant energy activity.

3.2 Principal energy laws relevant to AI

The exact legal provisions applicable depend on the actor, the decision being made, and the consequences of the AI output.

For example, a private utility using AI to predict transformer failures is not in the same legal position as a ministry using an AI-generated report to decide whether a nuclear power plant may continue operating. The latter involves a much more direct exercise of public regulatory authority.

4. Constitutional constraints on AI-assisted energy decisions

4.1 Legality and the prohibition on unauthorized governmental power

Under Articles 41 and 65, and the broader principle of legality in Japanese administrative law, public authorities must act within powers conferred by law.

Suppose an AI system used by an energy ministry produces a recommendation to reject an application for a power-generation license. The recommendation cannot itself become the legal basis for rejection. The competent authority must identify the applicable statute, apply the statutory criteria, and issue a legally valid decision.

Three distinctions are essential:

Technical assistance: AI calculates or predicts an outcome for an authorized decision-maker.

Administrative reliance: An official relies heavily on an AI recommendation when exercising statutory discretion.

Automated determination: An AI system effectively decides the matter without meaningful review by the legally authorized authority.

The first is generally the least problematic. The second requires safeguards appropriate to the decision's significance. The third raises the strongest concerns if the governing statute does not authorize the process or if the arrangement prevents the authority from exercising its own legally assigned judgment.

An agency cannot use a software contract or internal policy to expand its statutory powers.

4.2 Article 13: Life, personal dignity, and energy security

AI can influence decisions affecting the availability, safety, and affordability of essential energy services.

Examples include:

Predicting which areas should receive electricity during shortages.

Identifying households at risk of disconnection.

Assessing risks around nuclear facilities.

Monitoring household electricity consumption through smart meters.

Allocating emergency power after an earthquake or tsunami.

Article 13 becomes particularly relevant when a decision affects personal safety, privacy, or the basic conditions of daily life.

Example: Suppose an emergency electricity-allocation model gives a low priority score to a remote hospital because historical demand data are sparse. If officials rely blindly on that score, the resulting allocation could threaten patients' lives.

The legal problem is not simply that the model is inaccurate. It is that a public authority may have failed to discharge its own responsibilities when protecting people against foreseeable risks.

Constitutional analysis would depend on the particular statutory duties, the seriousness and foreseeability of the harm, the authority's discretion, and the available evidence. Article 13 does not automatically guarantee uninterrupted electricity to every individual in all circumstances.

4.3 Article 14: Equality and algorithmic discrimination

AI models learn patterns from historical data. Those patterns may reflect unequal access to infrastructure, historic underinvestment, or differences between urban and rural communities.

Potentially problematic applications include:

Subsidy models that consistently undervalue low-income households.

Grid-investment models that prioritize profitable urban districts while systematically overlooking remote communities.

Renewable-energy support models that disadvantage certain applicants because of biased historical records.

Automated consumer-risk assessments that treat unusual electricity-consumption patterns as evidence of unreliability.

Article 14 prohibits discrimination on the grounds specified in its text. Whether a particular algorithmic distinction violates Article 14 requires legal analysis of the classification, the governmental action, its justification, and the relevant constitutional standards.

Not every unequal result is unconstitutional. Differences based on legitimate technical or safety considerations may be justified. However, an authority should be able to explain why a classification is relevant, proportionate to its purpose, and consistent with applicable law.

4.4 Article 31: Procedural fairness and automated decisions

Article 31 is especially important in discussions of nuclear licensing and other high-consequence administrative decisions, but its scope must not be overstated.

In Japanese constitutional jurisprudence, the requirements of administrative procedures are not identical to those of criminal proceedings. The nature of the administrative decision, the applicable statute, and the interests affected all matter.

Where a decision affects a person's legally protected interests, relevant questions include:

Was the decision made under a valid legal procedure?

Did the authority follow any required notice, hearing, or consultation rules?

Were the statutory criteria actually considered?

Can the affected person understand and challenge the decision?

Did the AI system conceal an error or introduce an irrelevant factor?

For example, if an AI-assisted process results in refusal of a legally regulated energy-business application, the applicant may have procedural rights under the governing legislation. Whether an oral hearing or additional disclosure is required depends on the applicable legal framework.

There is no general rule that Article 31 requires disclosure of every source-code file or every internal model parameter in every energy dispute.

4.5 Article 29: Property rights and infrastructure development

AI can be used to identify sites for solar farms, transmission lines, pumped-storage facilities, wind farms, and nuclear infrastructure.

A model may rank land according to expected energy output, construction cost, grid proximity, environmental sensitivity, or estimated financial return.

However, an AI ranking cannot itself:

Authorize compulsory acquisition.

Override legally protected land-use rights.

Replace a required permit or environmental assessment.

Establish the legality of a restriction on land use.

Determine compensation without the governing legal framework being applied.

Article 29 protects property rights while allowing restrictions and other measures justified by public welfare within constitutional and statutory limits. The precise requirements depend on the measure involved.

4.6 Articles 76 and 81: Judicial independence and review

The final legal authority to determine a dispute belongs to the courts, not to an AI system.

If a ministry or regulator makes a legally reviewable decision using AI, a court may need to assess whether the authority acted within its powers, applied the correct legal criteria, considered relevant evidence, and complied with required procedures.

A court need not independently reproduce an AI model's calculations to assess the legality of the decision. It can examine the administrative record, technical evidence, applicable standards, and the reasoning actually adopted by the authority.

The Constitution does not make every AI-generated error automatically unconstitutional. The legal question is whether the challenged act or decision violates the applicable constitutional or statutory requirements.

5. Administrative-law safeguards for AI energy governance

The constitutional principles above operate through concrete rules of administrative law.

Reasons for administrative dispositions

Where the Administrative Procedure Act or another applicable law requires reasons, an agency must provide legally adequate reasons for its decision. A bare statement that “the AI rejected the application” may be insufficient because it does not identify the relevant statutory grounds or explain the authority's conclusion.

Control of administrative discretion

A regulator must exercise any statutory discretion lawfully. A model should not introduce irrelevant considerations, ignore mandatory factors, or effectively replace the judgment entrusted to the regulator.

Evidence and technical verification

Forecasts and risk scores should be tested against reliable data, engineering requirements, uncertainty estimates, and relevant safety standards. The more serious the possible harm, the stronger the case for independent validation and human oversight.

Public participation and transparency

Where consultation, public comment, environmental assessment, or disclosure is required by law, AI cannot be used to bypass it. Publishing meaningful information about assumptions and impacts can also improve accountability, subject to legitimate confidentiality and security restrictions.

A further distinction matters: the Administrative Procedure Act does not impose identical procedures on every form of governmental conduct. Some activities, including certain policy decisions or administrative guidance, may be governed differently from formal dispositions. The specific statutory category must be identified before deciding what procedural safeguards apply.

6. Important Japanese case laws

A key point for legal accuracy is that the following judgments were not disputes about modern AI systems. They are relevant because they establish principles concerning nuclear safety, administrative discretion, constitutional procedure, and governmental responsibility that could apply when AI is introduced into energy governance.

Case 1: Supreme Court nuclear-plant installation permission case

Supreme Court of Japan · Judgment of 29 April 1992 · Nuclear reactor installation permission dispute

Legal issue: Whether Japan's nuclear reactor licensing procedures and the administrative safety examination satisfied constitutional requirements, including arguments based on Article 31.

In the judgment, the Supreme Court addressed arguments that nuclear installation legislation should have expressly provided for local residents' participation, disclosure of all application and examination materials, and clear quantitative safety criteria.

The Court explained that administrative procedures differ according to their purposes and nature, and that they do not invariably require the same prior-notice and hearing procedures as criminal proceedings. The case also recognized the highly technical nature of nuclear installation assessments.

Supreme Court of Japan

Relevance to AI energy governance

Suppose a nuclear regulator uses a machine-learning model to assess whether a proposed reactor meets safety requirements.

The case supports three important distinctions:

The Constitution does not automatically require identical procedures for every administrative decision.

Technical complexity does not eliminate the need to follow applicable law.

The fact that an authority uses a technical assessment does not, by itself, settle whether its procedure or conclusion is lawful.

An AI-based safety assessment would still need to operate within the statutory licensing framework. The case does not establish that AI decisions are constitutionally valid merely because they involve technical expertise.

Case 2: Ohi Nuclear Power Plant litigation

Fukui District Court · 21 May 2014 · Ohi Nuclear Power Plant Units 3 and 4 operating-injunction case · Case No. Heisei 24 (Wa) 394

Legal issue: Whether operation of the Ohi nuclear reactors should be restrained in light of the risks to people's lives and personal rights.

The plaintiffs sought an injunction against the operation of Units 3 and 4, invoking personal rights and safety concerns after the Fukushima Daiichi disaster.

The District Court's judgment is notable for its strong emphasis on the importance of personal rights and the potentially catastrophic consequences of nuclear accidents. The decision treated the protection of life and bodily integrity as central to the assessment of nuclear-power risks.

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Relevance to AI energy governance

Imagine an AI system estimates that a nuclear plant's probability of equipment failure is acceptably low. An operator then uses the result to support continued operation.

The Ohi judgment illustrates why a favorable numerical risk estimate cannot automatically displace the legal protection of life and personal safety. A court may need to examine the assumptions, evidence, and applicable legal standards rather than treating a model's output as conclusive.

The judgment is a District Court decision, not a general Supreme Court rule declaring all nuclear operation unlawful. Its persuasive significance must be distinguished from binding legislation and higher-court precedent.

Case 3: Fukushima nuclear disaster — Supreme Court State Redress judgment

Supreme Court, Second Petty Bench · 17 June 2022 · Case No. 2021 (Ju) 342

Legal issue: Whether the State was liable under Article 1(1) of the State Redress Act for failing to exercise regulatory authority under the Electricity Business Act to prevent the Fukushima Daiichi accident caused by a tsunami.

The Supreme Court held, on the specific facts before it, that the necessary causal relationship between the alleged regulatory failure and the accident had not been established. It therefore rejected the relevant State-compensation claims on that basis.

Supreme Court of Japan

This decision should not be read as a general declaration that nuclear regulators can never be liable for failures to act. Japanese State Redress law examines the circumstances, the purpose and nature of the regulatory authority, the alleged illegality, and causation.

Relevance to AI energy governance

This is one of the most important cases for understanding the legal consequences of AI-assisted safety regulation.

Consider a regulator that uses AI to forecast tsunami risk at a nuclear power station. The system produces a warning, but the regulator does not investigate it or require appropriate safety measures.

A subsequent legal claim could raise questions about:

Whether the regulator had statutory authority and a duty to act.

Whether its failure to act was unlawful under the applicable legal standard.

Whether the warning was sufficiently reliable and foreseeable.

Whether a different regulatory response would have prevented the damage.

Whether the requirements for State Redress Act liability were satisfied.

The 2022 judgment makes causation particularly important. An inaccurate or ignored AI warning does not automatically establish State liability; the relevant legal elements must still be proven.

Equally, a government agency cannot assume that using AI removes its responsibility to evaluate foreseeable risks.

Case 4: Supreme Court judgment on the scope of administrative procedural protections

Supreme Court of Japan · 29 April 1992 · Nuclear reactor installation permission dispute

This is the same nuclear installation judgment discussed in Case 1, but it warrants separate attention because of its procedural implications.

The Court rejected the argument that Article 31 necessarily requires every administrative procedure to include the same safeguards proposed by the plaintiffs. It emphasized that administrative procedures differ according to their purpose and nature.

Supreme Court of Japan

Application to algorithmic decision-making

This judgment cautions against two opposite errors:

Claiming that every AI-assisted administrative decision must include a full oral hearing.

Claiming that AI-based technical assessments never require procedural safeguards.

The appropriate approach is to identify the governing statute, the nature of the administrative act, the interests affected, and any applicable notice, hearing, explanation, or disclosure requirements.

Case-law comparison

These cases provide the legal foundation for analysis. They should not be cited as judgments that directly decided the constitutionality of AI in Japanese energy regulation.

7. AI governance in Japan's electricity and nuclear sectors

7.1 AI-based electricity-grid management

AI can forecast electricity demand, identify transmission bottlenecks, predict renewable-energy output, and help balance supply and demand.

The Electricity Business Act provides the relevant statutory framework for electricity business and technical standards. In particular, the Supreme Court's 2022 Fukushima judgment discusses the regulatory authority that existed under Articles 39 and 40 of the Act before the 2012 amendments.

Supreme Court of Japan

The constitutional implications depend on how AI is used.

Example: An AI grid-management system predicts a shortage and recommends reducing electricity supply to a particular region.

A lawful response requires more than a model-generated ranking. The operator and any relevant public authority must consider applicable supply obligations, technical requirements, emergency rules, and the consequences for essential services.

If a public authority makes the allocation decision, it must also act within its legal powers. If a private utility makes it, its obligations depend on the applicable legislation, regulatory conditions, contracts, and other relevant law.

7.2 AI in nuclear-safety regulation

AI may assist in:

Predicting component degradation and equipment failure.

Detecting abnormal reactor conditions.

Assessing earthquake and tsunami hazards.

Monitoring radiation and environmental measurements.

Reviewing inspection records and maintenance histories.

Nuclear governance is particularly sensitive because errors can result in widespread and irreversible harm.

Japan's nuclear regulatory framework includes the Act on the Regulation of Nuclear Source Material, Nuclear Fuel Material and Reactors, while the Electricity Business Act also governs relevant aspects of electricity infrastructure.

The legal position is straightforward: AI can assist nuclear-safety assessment, but an AI-generated prediction is not a substitute for compliance with statutory safety requirements.

For example, if an AI system predicts that a safety-critical component will probably remain functional, that prediction does not authorize an operator to disregard mandatory inspection, maintenance, or technical standards.

A defensible system should preserve the underlying evidence, record the model's limitations, test its predictions against relevant engineering standards, and provide for independent technical verification.

7.3 AI and renewable-energy licensing

AI can identify suitable locations for solar farms, offshore wind installations, geothermal facilities, and battery-storage projects.

However, its recommendations may affect landowners, local communities, agricultural land, biodiversity, and public infrastructure.

An AI system might rank a site highly because of its expected electricity output while failing to account adequately for a legally protected environmental interest.

The resulting decision must be assessed under the applicable planning, environmental, land-use, and energy laws. Article 29 property rights and other constitutional interests may also be relevant.

An algorithmic ranking is evidence for consideration, not an independent permit or a legal authorization.

8. Privacy and personal data in AI energy systems

Smart meters and connected energy systems can generate detailed information about electricity consumption. When linked with other data, such information may reveal occupancy patterns, daily routines, or the use of particular household devices.

Japan's Act on the Protection of Personal Information (APPI) is relevant when the information constitutes personal data within the Act's scope.

AI energy systems should be designed to address:

The legal basis and purpose of data processing.

Appropriate security controls.

Restrictions on unauthorized use or disclosure.

Applicable requirements for third-party provision and overseas transfers.

Data accuracy, retention, and governance.

The risks of inferring sensitive personal characteristics from consumption patterns.

Article 13 of the Constitution provides an additional constitutional context for privacy and personal dignity, although the precise legal analysis depends on the circumstances.

Illustration: A utility develops a model that predicts which households are likely to be occupied at night. If the model uses identifiable customer data for a purpose that is not permitted by the applicable rules, the utility may face data-protection issues even if its electricity forecasts are technically accurate.

The constitutional issue is not that all energy analytics are prohibited. Rather, useful energy data must be processed within the relevant legal framework and with appropriate safeguards.

9. Judicial review of AI-assisted energy decisions

The Administrative Case Litigation Act provides the principal framework for litigation concerning administrative dispositions and other forms of legally reviewable administrative conduct.

A person challenging an AI-assisted energy decision would need to establish the relevant requirements for the particular type of action. Not every policy recommendation, technical report, or internal AI output is independently challengeable in court.

Where review is available, potential grounds of challenge include:

Lack of legal authority: The agency relied on AI in a way that exceeded its statutory powers.

Error of law: The authority applied the wrong legal criteria.

Improper exercise of discretion: The authority relied on irrelevant considerations or failed to consider legally required factors.

Procedural illegality: A mandatory notice, hearing, consultation, or reasoning requirement was not followed.

Insufficient factual basis: The decision relied on materially unreliable information or an inadequately examined model output.

Constitutional infringement: The decision violated an applicable constitutional guarantee.

Whether an error in an AI system invalidates an administrative decision depends on its significance to the decision, the applicable law, and the nature of the defect.

Evidence that may matter in an AI-related dispute

Data and model records

Data provenance, validation reports, training-data limitations, error rates, and known failure modes.

Administrative record

The official's reasons, the statutory criteria applied, the evidence considered, and any departures from the AI recommendation.

Safety and risk evidence

Engineering assessments, uncertainty analysis, incident records, alternative scenarios, and independent expert opinions.

Procedural evidence

Required notices, public comments, hearing records, explanations, and documents showing how the final decision was reached.

The absence of a single universally mandated AI audit format does not mean that the authority can ignore its existing duties to maintain a lawful and adequately supported administrative process.

10. A hypothetical case study

Consider the following hypothetical dispute involving an AI-assisted nuclear-safety assessment.

Hypothetical: AI-based tsunami-risk assessment

The following facts are illustrative and do not describe an actual court judgment.

Facts

A nuclear operator uses AI to predict tsunami risk. The model estimates a low probability of flooding. However, the model has limited data on extreme events, and a separate engineering report identifies a potentially serious failure scenario.

The operator relies on the AI result when preparing its safety documentation. A regulator approves the relevant application without adequately addressing the conflicting engineering evidence.

Legal questions

Did the regulator apply the correct statutory safety criteria?

Did it properly consider the conflicting technical evidence?

Was its decision supported by adequate factual and technical analysis?

Were all required regulatory procedures followed?

If an accident occurred, would the legal requirements for operator liability or State Redress Act liability be satisfied?

Possible legal analysis

The 1992 nuclear installation judgment is relevant to the procedural treatment of technical assessments. The Ohi judgment provides context for the importance of personal rights and nuclear safety. The 2022 Fukushima judgment is relevant to the analysis of governmental regulatory failure and causation.

If the regulator failed to consider legally relevant safety evidence, its decision could be vulnerable to challenge, depending on the applicable statutory standards and review requirements. If harm subsequently occurred, liability would require a separate assessment of the relevant legal duties, unlawful conduct, causation, and damage.

Key lesson

A low AI-generated risk estimate cannot automatically override mandatory safety requirements or relieve a regulator of its legal responsibilities.

11. Recommended safeguards for constitutionally compliant AI governance

Japan can reduce constitutional and administrative-law risks by adopting the following governance measures. These are recommendations for sound implementation; they should not all be mistaken for universally binding requirements under current Japanese law.

The degree of oversight should be proportionate to the risk. An AI model used to optimize routine energy-consumption forecasts does not require the same controls as a model whose output influences nuclear-safety authorization or emergency electricity allocation.

12. Overall legal assessment

Japan's approach to AI in energy governance is best understood as the application of existing constitutional and statutory obligations to new technical systems, alongside the newer national framework promoting AI development and utilization.

Three conclusions follow.

First, constitutional legality remains paramount. AI cannot create new governmental powers, displace the Diet's legislative role, or immunize an administrative decision from judicial review.

Second, technical sophistication does not eliminate legal responsibility. The nuclear-safety cases demonstrate the importance of procedure, personal rights, evidence, regulatory duties, and causation. Their principles can inform AI-related disputes even though the cases themselves did not decide the legality of modern AI systems.

Third, constitutional compliance is not achieved through human oversight alone. Effective governance also requires a lawful basis, reliable evidence, appropriate procedures, data protection, technical validation, accountability, and access to the remedies provided by law.

In short, AI should operate as a tool within Japan's legal energy-governance system, not as an autonomous source of legal authority.

13. Primary legal sources and further reading

The following official and judicial sources are useful for verifying the legal framework and developing a research paper.

Constitution of Japan

Official English text published by the House of Representatives.

Read the Constitution

AI Act — Cabinet Office of Japan

Overview of the 2025 AI promotion legislation and related materials.

Read the official AI Act overview

Supreme Court of Japan — Fukushima State Redress judgment

17 June 2022; Case No. 2021 (Ju) 342.

Read the judgment and case summary

Supreme Court of Japan — Nuclear installation permission judgment

29 April 1992; relevant to Article 31 and nuclear licensing procedures.

Read the judgment

AI-related technologies promotion legislation

Official Japanese statutory text on e-Gov.

Read the legislation

For academic or legal submissions, verify the full Japanese judgments, the applicable statutory versions at the date of the disputed conduct, and the exact scope of each holding. The Ohi decision should be cited as a District Court judgment, and the Fukushima decision should be cited for its actual ruling on the State's liability rather than as a blanket endorsement or rejection of nuclear regulation.

This is a general legal analysis for research and educational purposes, not an opinion on a particular dispute under Japanese law.