1. Introduction

Governance of emerging technological risks refers to the legal, institutional, regulatory and ethical mechanisms used by governments and regulators to identify, assess, prevent and manage risks arising from new or rapidly developing technologies.

Emerging technologies include artificial intelligence (AI), machine learning, autonomous systems, smart grids, blockchain, quantum computing, biotechnology, Internet of Things (IoT), drones, autonomous vehicles, advanced energy-storage systems and algorithmic decision-making. These technologies can produce substantial economic and social benefits, but they may also create risks that existing legal frameworks were not designed to address.

The central difficulty is that regulation often develops after technology has already been deployed. Consequently, modern governance increasingly uses concepts such as risk assessment, precaution, transparency, accountability, human oversight, cybersecurity, data protection, regulatory sandboxes and adaptive regulation.

The European Union's AI Act illustrates this approach by expressly adopting a risk-based regulatory structure, including prohibited practices, obligations for high-risk AI systems and transparency requirements. (EUR-Lex)

2. Meaning of Emerging Technological Risks

Emerging technological risks are risks associated with technologies whose capabilities, applications or social consequences are still developing.

They may be:

Physical risks – injury, equipment failure or infrastructure damage.

Cybersecurity risks – hacking, malware and unauthorised access.

Privacy risks – unlawful collection or processing of personal information.

Algorithmic risks – bias, discrimination or erroneous automated decisions.

Environmental risks – pollution, resource consumption and ecological damage.

Economic risks – market disruption, monopoly and technological dependency.

Systemic risks – failure of interconnected technological infrastructure.

Governance risks – lack of accountability when decisions are made by automated systems.

In electricity systems, for example, AI-controlled grids, distributed batteries, smart meters and automated demand-response systems can improve efficiency while simultaneously creating cybersecurity, reliability, privacy and accountability challenges.

3. Why Emerging Technologies Require Special Governance

Traditional regulation generally assumes that the regulated activity and its risks are reasonably understood. Emerging technologies challenge that assumption.

A. Regulatory uncertainty

A regulator may not initially know the complete consequences of a new technology. Legislatures therefore face difficulty in defining appropriate standards without either under-regulating or unnecessarily restricting innovation.

B. Technological complexity

Modern technologies frequently involve algorithms, cloud infrastructure, sensors and interconnected networks. A harmful outcome may therefore result from several actors rather than one identifiable decision-maker.

C. Speed of technological change

Technology can develop much faster than legislation. A statute drafted for one technological architecture may become inadequate after only a few years.

D. Cross-border character

Digital technologies operate across national boundaries. Data, algorithms, software and infrastructure may be located in different jurisdictions.

E. Difficulty of attributing responsibility

Where an autonomous system causes harm, responsibility may potentially involve the developer, manufacturer, operator, data provider, infrastructure owner or user.

4. Principles of Governance of Emerging Technological Risks

4.1 Precautionary Principle

The precautionary principle allows regulatory intervention where there is a credible risk of serious harm even though scientific or technological certainty is incomplete.

It is particularly important where technological failure could cause irreversible consequences.

The principle does not necessarily require prohibition. It can justify:

pilot programmes;

testing requirements;

licensing;

monitoring;

safety standards;

reporting obligations; and

restrictions on particularly dangerous applications.

4.2 Risk-Based Regulation

A modern regulatory framework should distinguish between technologies according to the severity and probability of potential harm.

For example:

The EU AI Act formally adopts this risk-based philosophy, with different obligations corresponding to the risks posed by AI systems. (EUR-Lex)

4.3 Transparency

Technology governance requires sufficient transparency to determine:

what the technology does;

what data it uses;

who controls it;

what risks have been identified;

how decisions are produced; and

how affected persons can challenge decisions.

Transparency is particularly important when automated systems affect fundamental rights.

4.4 Accountability

Technological innovation should not create an accountability gap.

A regulatory system should identify:

responsible developers;

operators;

manufacturers;

infrastructure owners;

regulators;

data controllers; and

persons responsible for final decisions.

The principle can be expressed as:

Technological autonomy should not eliminate legal responsibility.

4.5 Human Oversight

Automated decision-making should not necessarily be treated as an independent substitute for human judgment.

This principle is particularly important in areas such as:

healthcare;

criminal justice;

employment;

financial services;

energy-system control;

public administration; and

judicial decision-making.

The Supreme Court of India has recently addressed the dangers of relying on AI-generated legal material. In Pooja Ramesh Singh v. Jammu and Kashmir Bank Ltd., 2026 INSC 668, the Court considered judgments containing AI-generated citations that were subsequently found to be nonexistent or incorrectly attributed, emphasizing the consequences for judicial decision-making. (Supreme Court of India)

This illustrates an important governance principle: AI may assist decision-makers, but mechanisms must exist to verify its outputs.

5. Privacy and Data Governance

Emerging technologies depend heavily on data. AI, IoT, biometric systems, smart meters and surveillance technologies may collect enormous quantities of personal or behavioural information.

Therefore, technology governance must incorporate:

purpose limitation;

data minimisation;

security safeguards;

lawful processing;

access controls;

retention limits;

accountability; and

remedies for misuse.

Case Law: K.S. Puttaswamy v. Union of India

In Justice K.S. Puttaswamy (Retd.) v. Union of India, (2017) 10 SCC 1, the Supreme Court recognised privacy as a constitutionally protected right associated with Article 21 and other fundamental freedoms.

The Court's privacy jurisprudence is highly relevant to emerging technologies because technological systems can affect personal autonomy, dignity and informational privacy.

The Supreme Court has subsequently referred to technology's capacity to intrude into an individual's private space and reiterated the constitutional importance of privacy. (Sci API)

Legal significance

The case establishes an important foundation for technology governance:

technological capability does not automatically justify technological use.

State action involving emerging technologies must remain consistent with constitutional protections.

6. Cybersecurity Governance

The increasing digitisation of infrastructure creates cybersecurity risks.

Critical systems such as electricity networks, telecommunications, banking and transport may be interconnected. A cyberattack against one system may therefore generate consequences elsewhere.

Effective governance requires:

cybersecurity standards;

mandatory incident reporting;

vulnerability assessments;

security-by-design;

access controls;

encryption;

emergency-response procedures;

independent audits; and

continuity planning.

For energy infrastructure, cybersecurity governance becomes particularly important because digital control systems can potentially affect physical infrastructure.

7. Governance of Emerging Technologies in Electricity Systems

The energy sector provides an important example.

Technological developments include:

AI-based grid management;

smart meters;

battery-storage systems;

distributed energy resources;

virtual power plants;

blockchain-based electricity trading;

autonomous demand response;

digital substations;

electric-vehicle charging networks.

These technologies can improve system efficiency but also create new legal risks.

Example

Suppose an AI system automatically controls electricity flows and incorrectly disconnects thousands of consumers.

Several questions arise:

Who is legally responsible?

Was the algorithm properly tested?

Was there adequate human supervision?

Did the operator comply with grid codes?

Was the system cybersecure?

Was there an emergency override?

Who compensates affected consumers?

This demonstrates why technology governance must combine technical regulation with legal accountability.

8. Indian Electricity-Regulatory Context

India's Electricity Act, 2003 provides the basic institutional framework for electricity generation, transmission, distribution, trading and regulation. Emerging technologies, however, increasingly require regulators to address matters that were less prominent when the legislation was enacted.

Regulatory governance therefore involves institutions such as:

Central Electricity Regulatory Commission (CERC);

State Electricity Regulatory Commissions;

Central Electricity Authority;

Ministry of Power;

power-system operators; and

distribution and transmission licensees.

Courts have repeatedly examined the statutory limits of electricity regulators.

Case: M.P. Power Transmission Co. Ltd. v. CERC

In a 2025 Supreme Court judgment, the Court examined whether CERC had acted within the powers conferred upon it under the Electricity Act, 2003 and its regulations. The case demonstrates the continuing importance of statutory authority and institutional competence in electricity regulation. (Sci API)

The broader lesson for emerging technology is that regulators cannot simply rely upon technological necessity; regulatory action must remain grounded in legally conferred powers.

9. Environmental Governance

Emerging technologies may generate environmental risks even when their immediate purpose is beneficial.

Examples include:

large-scale battery production;

electronic waste;

data-centre electricity consumption;

mining of critical minerals;

hydrogen infrastructure;

carbon-capture systems;

biotechnology;

advanced nuclear technologies.

Environmental governance therefore requires:

environmental impact assessment;

lifecycle analysis;

pollution controls;

waste management;

resource monitoring;

environmental disclosure; and

remediation mechanisms.

Technology regulation should consequently examine the entire lifecycle of a technology rather than only its operational stage.

10. Regulatory Sandboxes

A regulatory sandbox permits new technologies to be tested under controlled conditions.

A sandbox may provide:

limited geographic deployment;

limited consumer participation;

temporary regulatory flexibility;

enhanced monitoring;

reporting requirements; and

predefined safety conditions.

This allows regulators to obtain empirical information before establishing permanent rules.

For emerging technologies, the sandbox model can therefore reconcile two competing objectives:

innovation + regulatory protection.

11. Adaptive Regulation

Traditional legislation can become obsolete when technology changes rapidly.

Adaptive regulation instead creates mechanisms through which regulatory requirements can be periodically reviewed.

Important mechanisms include:

delegated rule-making;

technical standards;

periodic regulatory review;

sunset clauses;

regulatory experimentation;

stakeholder consultation; and

continuous risk assessment.

This approach is especially useful for AI, autonomous systems and digital energy infrastructure.

12. Liability for Technological Harm

A major legal question is whether existing liability principles are adequate for autonomous technologies.

Traditional tort law generally examines:

duty;

breach;

causation; and

damage.

But autonomous technologies create additional questions.

For example, if an autonomous energy-management system makes an unexpected decision, the court may need to determine whether the problem arose from:

defective design;

inadequate training data;

negligent deployment;

poor maintenance;

cybersecurity failure;

operator negligence; or

an unforeseeable technological event.

Therefore, emerging technology governance may require a combination of product liability, negligence, statutory liability and regulatory enforcement.

13. Case Law Relevant to Technological Risk Governance

1. K.S. Puttaswamy (Retd.) v. Union of India (2017)

Principle: Privacy is a constitutionally protected right.

Relevance: Establishes constitutional limits on data-intensive technologies and surveillance. (SciGov)

2. Anuradha Bhasin v. Union of India (2020)

Principle: Constitutional freedoms must be considered in the context of modern digital communications.

Relevance: Demonstrates how constitutional rights must be interpreted in technological environments.

3. Justice K.S. Puttaswamy (Aadhaar) v. Union of India (2018)

Principle: Large-scale biometric and digital identification systems must satisfy constitutional requirements.

The judgment specifically examined safeguards concerning biometric information and referred to existing data-protection provisions and privacy jurisprudence. (SciGov)

Relevance: Shows the importance of proportionality, safeguards and data governance when emerging technology is deployed at population scale.

4. Pooja Ramesh Singh v. Jammu and Kashmir Bank Ltd. (2026)

Principle: AI-generated legal material cannot simply be treated as authoritative without verification.

The Supreme Court's official judgment summary records the problem of AI-generated citations that were nonexistent or incorrectly attributed. (Supreme Court of India)

Relevance: Demonstrates the need for human verification, professional responsibility and institutional controls over generative AI.

5. M.P. Power Transmission Co. Ltd. v. CERC (2025)

Principle: Electricity regulators must act within the authority granted by the Electricity Act and applicable regulations.

Relevance: Emerging technological regulation in electricity systems must remain legally grounded rather than relying solely on technological or administrative necessity. (Sci API)

14. International Comparative Perspective

The EU provides an important example of formalised technology-risk governance.

The EU Artificial Intelligence Act, Regulation (EU) 2024/1689, uses a risk-based framework and provides different obligations for prohibited practices, high-risk AI, transparency and general-purpose AI models. (EUR-Lex)

Its significance lies in moving away from a simple question of:

"Is this technology legal?"

towards:

"What level of risk does this particular use of the technology create, and what regulatory safeguards correspond to that risk?"

This model is increasingly influential in global technology governance.

15. Institutional Governance Model

An effective emerging-technology governance framework can be represented as:

Technology Development
↓
Risk Identification
↓
Risk Classification
↓
Testing and Certification
↓
Regulatory Approval / Controlled Deployment
↓
Monitoring and Auditing
↓
Incident Reporting
↓
Enforcement and Remediation
↓
Periodic Regulatory Review

This creates a continuous regulatory cycle rather than a one-time licensing process.

16. Major Challenges

A. Regulatory lag

Technology develops faster than legislation.

B. Knowledge asymmetry

Technology companies may possess significantly more technical knowledge than regulators.

C. Fragmented jurisdiction

Multiple regulators may have overlapping responsibilities.

D. International enforcement

Technology may be developed in one country and deployed in another.

E. Algorithmic opacity

Some systems are difficult for regulators and affected persons to understand.

F. Innovation versus safety

Excessive regulation may inhibit beneficial innovation, while inadequate regulation may expose society to unacceptable risks.

G. Accountability gaps

Autonomous systems can make responsibility difficult to allocate.

17. Recommended Governance Framework

A comprehensive legal framework for emerging technological risks should contain:

Technology-neutral legislation where possible.

Risk-based classification of technologies.

Mandatory safety assessments for high-risk applications.

Independent technical audits.

Human oversight for consequential decisions.

Cybersecurity-by-design.

Privacy-by-design.

Transparency and explainability requirements.

Incident reporting mechanisms.

Clear liability rules.

Regulatory sandboxes for experimentation.

Public participation in major regulatory decisions.

Periodic review of regulatory standards.

Cross-border regulatory cooperation.

Effective judicial and administrative remedies.

18. Conclusion

Governance of emerging technological risks represents a shift from reactive regulation to anticipatory governance. The objective is not simply to prevent technological development but to ensure that innovation occurs within an accountable legal framework.

Indian constitutional jurisprudence, particularly the privacy decisions beginning with Puttaswamy, provides an important rights-based foundation. Electricity cases demonstrate the importance of statutory authority and institutional competence, while the Supreme Court's recent treatment of AI-generated legal material illustrates the practical necessity of human verification and accountability. (Supreme Court of India)

The central legal principle can therefore be stated as follows:

Emerging technology should be governed according to the risks it creates, the rights it affects, and the responsibilities of the actors who design, deploy and control it.

A durable framework should combine precaution, proportionality, transparency, cybersecurity, privacy, human oversight, accountability and adaptive regulation. Such a framework allows technological innovation while ensuring that technological progress remains consistent with constitutional rights, public safety, environmental protection and the rule of law.