135. AI Transparency and Electricity Markets

Introduction

Artificial Intelligence (AI) is increasingly relevant to electricity markets. AI systems can forecast electricity demand, predict renewable-energy generation, detect fraud, optimise grid operations, determine prices and assist in trading decisions. However, when important electricity-market decisions depend upon automated or AI-based systems, transparency, accountability and explainability become essential. Consumers and market participants should be able to understand the basis of significant regulatory or commercial decisions.

Meaning of AI Transparency

AI transparency means that relevant stakeholders should have sufficient information about:

the purpose of an AI system;

the data used;

the factors influencing its output;

limitations and risks;

responsibility for decisions; and

mechanisms for review or challenge.

Complete disclosure of source code is not necessarily required in every situation. Transparency must be balanced with legitimate interests such as cybersecurity, privacy and protection of confidential commercial information.

AI in Electricity Markets

AI may be used for load forecasting, dynamic pricing, demand response, renewable-energy forecasting, electricity trading and grid balancing. These applications can improve efficiency but may also create risks.

For example, an opaque algorithm could produce discriminatory outcomes between consumer categories, make unexplained pricing recommendations, or contribute to market manipulation. If market participants cannot understand or challenge an automated decision, conventional principles of administrative fairness may be weakened.

Indian Legal Framework

India does not currently have a single comprehensive statute exclusively governing AI transparency in electricity markets. The issue must therefore be considered through existing constitutional, electricity, data-protection and regulatory principles.

Article 14 requires State action to be non-arbitrary and fair. Article 21 protects life and personal liberty and has been interpreted to include procedural fairness in appropriate circumstances.

The Electricity Act, 2003 provides the statutory framework for electricity regulation, while regulatory authorities such as CERC and State Electricity Regulatory Commissions supervise electricity markets. AI-based regulatory decisions must operate within their statutory powers.

The Digital Personal Data Protection Act, 2023 is also relevant where AI systems process personal data, subject to its applicability and statutory requirements.

Case Laws

1. State of U.P. v. Raj Narain (1975)

The Supreme Court recognised the importance of transparency in government functioning, observing that citizens have an interest in knowing about public acts. This principle supports the broader idea that public authorities should not operate important decision-making processes without appropriate accountability.

2. Maneka Gandhi v. Union of India (1978)

The Supreme Court significantly expanded the interpretation of Article 21 and emphasised that procedures affecting fundamental rights must satisfy standards of fairness and reasonableness. In an AI-driven regulatory environment, this principle can support procedural safeguards where automated decisions affect legally protected interests.

3. Shreya Singhal v. Union of India (2015)

The Supreme Court examined restrictions on online speech and struck down Section 66A of the Information Technology Act. The case demonstrates the constitutional importance of clear legal standards and safeguards when technology is used to regulate rights.

Although it did not concern AI or electricity markets, its principles are relevant to technology-based governance.

Need for AI Accountability

Electricity regulators using AI should consider:

Explainability of significant decisions;

Human oversight over high-impact decisions;

Auditability of algorithms;

protection of confidential and personal data;

mechanisms for correcting errors;

cybersecurity safeguards; and

opportunities for affected parties to challenge decisions.

Conclusion

AI can improve the efficiency and reliability of electricity markets, but opaque automated decision-making may create significant legal and regulatory risks. AI transparency therefore requires an appropriate balance between innovation, efficiency, confidentiality, privacy, fairness and accountability. Constitutional principles of non-arbitrariness and procedural fairness, together with electricity and data-protection laws, provide an emerging framework for responsible use of AI in electricity markets.