1. Introduction

Radical relational uncertainty in governance networks describes a situation in which uncertainty does not arise merely because individual institutions lack information. Rather, it arises because the relationships among institutions, regulators, private actors, infrastructure operators, communities, and technological systems are themselves unstable, changing, or difficult to predict.

Traditional administrative law often assumes identifiable institutions with relatively clear powers: a legislature makes law, a regulator regulates, an executive implements, and courts review. Modern governance networks are considerably more complicated. Energy systems, environmental regulation, digital infrastructure, financial markets, public-private partnerships, and smart grids involve multiple actors whose decisions continuously affect one another.

The concept can therefore be expressed as:

Radical relational uncertainty exists when the legal consequences of an action cannot be predicted solely from the characteristics of the individual actor because those consequences depend upon continuously changing relationships within a governance network.

In energy governance, for example, a distribution company may depend on a regulator, transmission operator, independent power producer, renewable generator, market operator, state government, central government, consumers, and increasingly automated systems. A decision by one participant can alter the behaviour and legal position of many others.

2. Meaning of “Radical Relational Uncertainty”

The concept contains three elements.

A. Radical

“Radical” means that the uncertainty is structural rather than temporary.

It is not simply:

• incomplete information;
• an unexpected event;
• an ambiguous statutory provision; or
• an administrative mistake.

Instead, uncertainty is embedded in the governance arrangement itself.

B. Relational

The uncertainty concerns relationships between actors.

For example:

• regulator ↔ utility;
• government ↔ regulator;
• utility ↔ consumer;
• transmission operator ↔ generator;
• public authority ↔ private contractor;
• central government ↔ state government.

The legal outcome may depend upon how these actors interact.

C. Governance Networks

A governance network contains multiple public and private actors participating in decision-making, implementation, monitoring and enforcement.

Consequently, governance is no longer purely hierarchical.

3. Traditional Governance Versus Network Governance

A traditional regulatory model can be represented as:

Legislature → Government → Regulator → Regulated Entity → Consumer

The authority flows principally downward.

A network model is different:

Government ↔ Regulator ↔ Utility ↔ Market Operator ↔ Generator ↔ Consumer ↔ Technology Provider

There may also be horizontal relationships between private and public entities.

This creates several forms of uncertainty.

3.1 Authority uncertainty

Which institution possesses the power to act?

3.2 Responsibility uncertainty

Who is legally responsible when several institutions jointly produce an outcome?

3.3 Causation uncertainty

Which actor caused the regulatory or infrastructural failure?

3.4 Accountability uncertainty

Who should answer to courts, legislatures, consumers or affected communities?

3.5 Temporal uncertainty

Can a regulatory decision made today remain appropriate when technology, markets and relationships change tomorrow?

4. Why Governance Networks Produce Radical Uncertainty

4.1 Multiple centres of authority

Modern governance frequently involves overlapping jurisdictions.

In the energy sector, for instance, authority can be divided among:

• Parliament;
• Central Government;
• State Governments;
• CERC;
• SERCs;
• electricity utilities;
• system operators;
• municipalities;
• environmental authorities.

An action may therefore have several possible legal sources.

4.2 Public-private interaction

Private entities increasingly perform functions traditionally associated with government.

Examples include:

• private distribution companies;
• independent power producers;
• private transmission operators;
• renewable-energy developers;
• technology providers;
• energy exchanges.

This raises a difficult question:

When a private actor performs a function with significant public consequences, how far should public-law obligations follow that function?

4.3 Technological interdependence

Smart grids, artificial intelligence, automated dispatch, energy-storage systems and digital metering create relationships that are difficult to regulate using traditional institutional categories.

An automated decision may involve:

1. software developer;
2. utility;
3. system operator;
4. regulator;
5. data provider; and
6. consumer.

If the system produces discriminatory or harmful results, responsibility may be distributed across the network.

5. Relationship Between Uncertainty and Legal Accountability

Radical relational uncertainty creates a fundamental problem for administrative law.

The traditional accountability question is:

Who made the decision?

Network governance requires a broader question:

Which combination of actors, institutional relationships and technological processes produced the decision?

This changes the conception of administrative responsibility.

Accountability may have to operate at several levels:

• individual accountability;
• institutional accountability;
• contractual accountability;
• regulatory accountability;
• systemic accountability.

6. Indian Constitutional Framework

The Indian Constitution provides important principles for controlling uncertain governance relationships.

Article 14

Article 14 prohibits arbitrary state action.

Where a governance network creates arbitrary distinctions or unpredictable administrative treatment, Article 14 can become relevant.

Article 21

Where infrastructure or regulatory decisions affect life, livelihood, health or environmental interests, Article 21 may become relevant.

Article 32 and Article 226

Judicial review enables constitutional courts to examine decisions of public authorities and, in appropriate circumstances, entities performing public functions.

7. Case Law

7.1 Ramana Dayaram Shetty v. International Airport Authority of India (1979)

This is an important Indian authority concerning public power exercised through institutional and contractual relationships.

The Supreme Court emphasized that government instrumentalities cannot exercise public power arbitrarily in contractual matters.

Relevance

The case demonstrates that the legal character of governmental action cannot always be separated from the contractual network through which the government acts.

It therefore supports the proposition that:

Administrative legality can extend into relationships that superficially appear to be private or contractual.

8. Ajay Hasia v. Khalid Mujib Sehravardi (1981)

The Supreme Court developed principles for determining when an entity may qualify as an instrumentality or agency of the State under Article 12.

The Court looked beyond formal corporate structure and examined the substance of governmental control and functional relationships.

Importance for relational uncertainty

The case is particularly relevant because governance networks frequently contain entities whose formal legal identity does not completely reveal their public character.

A corporation may be legally separate from government while being deeply integrated into public governance.

Thus:

Formal identity ≠ complete legal responsibility.

9. Pradeep Kumar Biswas v. Union of India (2002)

The Supreme Court refined the test for determining whether a body is an instrumentality of the State.

The Court emphasized the financial, functional and administrative domination of the government.

Relational significance

The decision illustrates how courts examine the relationship between an institution and government, rather than merely its corporate label.

This is directly relevant to network governance because institutional status can depend upon the intensity of relationships.

10. Binny Ltd. v. V. Sadasivan (2005)

The Supreme Court examined the availability of judicial review against private bodies performing public functions.

The Court recognized that judicial review may extend beyond conventional government bodies where a body performs a public function.

Significance

This is important for network governance because public functions can be distributed across public and private institutions.

The question becomes:

Is the function sufficiently public to justify public-law scrutiny?

This is a relational inquiry.

11. Zee Telefilms Ltd. v. Union of India (2005)

The Supreme Court examined whether the Board of Control for Cricket in India could be regarded as “State” under Article 12.

Although the Court ultimately distinguished Article 12 status from the broader possibility of judicial review based on public duties, the case illustrates the difficulty of determining the legal position of institutions operating between the public and private spheres.

Governance-network relevance

Modern governance frequently produces such hybrid institutions.

Their uncertain status can create uncertainty about:

• constitutional obligations;
• judicial review;
• accountability;
• transparency.

12. Tata Cellular v. Union of India (1994)

The Supreme Court established important principles concerning judicial review of governmental contractual decisions.

The Court emphasized that judicial review primarily examines:

• legality;
• rationality;
• procedural propriety.

It does not ordinarily substitute judicial decision-making for administrative expertise.

Relational significance

Public procurement is a network relationship involving:

Government ↔ tendering authority ↔ private bidders ↔ contractors ↔ public beneficiaries.

Judicial review must therefore control arbitrariness without unnecessarily disrupting legitimate institutional relationships.

13. Reliance Natural Resources Ltd. v. Reliance Industries Ltd. (2010)

This case concerned the allocation and use of natural gas and the relationship between contractual arrangements and governmental control over natural resources.

The Supreme Court emphasized the constitutional significance of natural resources and the role of the State in regulating them.

Relevance

Energy governance frequently involves a complex relationship between:

• State ownership;
• private contracts;
• regulatory institutions;
• commercial interests;
• public interest.

This demonstrates how contractual rights cannot always be understood independently from the wider governance network.

14. Energy Sector Example: Electricity Regulatory Governance

The Electricity Act, 2003 provides a particularly useful illustration.

The Act distributes authority among multiple institutions, including:

• Central Electricity Regulatory Commission;
• State Electricity Regulatory Commissions;
• Central Electricity Authority;
• transmission utilities;
• distribution licensees;
• generating companies;
• system operators.

This creates a network rather than a single regulatory hierarchy.

For example:

Generator → Transmission System → System Operator → Distribution Licensee → Consumer

A regulatory decision concerning one actor may therefore have consequences throughout the network.

15. Case: PTC India Ltd. v. Central Electricity Regulatory Commission (2010)

This Supreme Court decision is one of the most important authorities concerning electricity regulation.

The Court examined the relationship between regulations framed by CERC and statutory rights/obligations under the Electricity Act.

Importance

The case demonstrates that electricity regulation involves layered relationships between:

• Parliament;
• regulator;
• market participants;
• contractual arrangements;
• statutory powers.

The Court's approach illustrates how regulatory authority must remain anchored in statutory delegation even within a complex governance network.

Principle

A governance network cannot eliminate the requirement of legal authority.

Network complexity does not mean unlimited regulatory discretion.

16. Energy Network and Federalism

Electricity governance also illustrates relational uncertainty between:

Union Government ↔ State Government ↔ CERC ↔ SERC ↔ utilities.

Federal arrangements create overlapping institutional relationships.

A policy introduced at the central level may require:

• state implementation;
• regulatory approval;
• utility compliance;
• infrastructure investment.

The resulting legal outcome may therefore depend upon cooperation among multiple institutions.

17. Radical Relational Uncertainty and Energy Transitions

The transition toward:

• renewable energy;
• battery storage;
• green hydrogen;
• electric vehicles;
• distributed generation;
• rooftop solar;
• smart grids;

increases relational uncertainty.

For example, rooftop solar changes the consumer from merely a consumer into a potential:

consumer + producer + storage operator + market participant.

This transforms traditional regulatory relationships.

18. Distributed Energy and the Prosumer

A conventional electricity relationship is:

Utility → Consumer

A distributed-energy relationship can become:

Utility ↔ Prosumer ↔ Grid ↔ Market ↔ Storage Operator

The legal system must answer:

• Who owns electricity generated behind the meter?
• Who bears grid-balancing responsibility?
• Who pays network charges?
• Who is liable for cybersecurity failures?
• How should excess electricity be compensated?
• Who controls consumption data?

These are examples of relational uncertainty.

19. Climate Governance

Climate governance provides another illustration.

Climate regulation may involve:

• national governments;
• state governments;
• municipalities;
• corporations;
• financial institutions;
• international organizations;
• carbon-market administrators;
• local communities.

A corporation's climate obligation may depend upon relationships with several regulatory regimes.

Consequently, climate governance is increasingly polycentric rather than purely hierarchical.

20. Radical Relational Uncertainty and Artificial Intelligence

AI-driven governance intensifies the problem.

Suppose an AI system determines:

• electricity demand;
• grid congestion;
• renewable dispatch;
• maintenance priorities;
• consumer risk;
• electricity pricing.

Responsibility may be divided between:

1. AI developer;
2. utility;
3. system operator;
4. regulator;
5. data provider;
6. human decision-maker.

If the algorithm produces an unlawful outcome, simply asking “Who made the decision?” may not provide an adequate answer.

The legal system must instead reconstruct the decision network.

21. Causal Attribution Problem

Radical relational uncertainty creates a major problem of causal attribution.

Suppose a major grid failure occurs.

Possible causes could include:

• inadequate generation;
• transmission congestion;
• poor maintenance;
• faulty forecasting;
• regulatory failure;
• extreme weather;
• cybersecurity;
• operator error.

The event may therefore have distributed causation.

Legal responsibility cannot always be assigned by identifying one immediate actor.

22. Implications for Administrative Law

Radical relational uncertainty requires administrative law to develop several principles.

22.1 Traceability

Authorities should maintain records showing:

• who participated;
• what information was considered;
• what decisions were made;
• which algorithms were used;
• which institution had final authority.

22.2 Reason-giving

Network participants exercising public power should provide sufficient reasons.

22.3 Procedural fairness

Affected parties should have meaningful opportunities to challenge decisions.

22.4 Institutional coordination

Where powers overlap, institutions should establish clear coordination mechanisms.

22.5 Responsibility allocation

Regulatory frameworks should expressly allocate responsibility among network participants.

23. Relationship Between Uncertainty and Judicial Review

Courts generally do not eliminate uncertainty completely.

Instead, judicial review seeks to ensure that uncertainty does not become:

• arbitrariness;
• discrimination;
• irrationality;
• procedural unfairness;
• unauthorized exercise of power.

Thus, courts establish legal boundaries around uncertainty.

24. The Principle of Institutional Legibility

One possible response is to require institutional legibility.

Every major governance network should make clear:

1. who possesses decision-making authority;
2. who provides technical information;
3. who supervises implementation;
4. who bears legal responsibility;
5. who can be challenged;
6. who provides remedies.

This is especially important for energy infrastructure because failures can have systemic consequences.

25. Regulatory Sandboxes and Managed Uncertainty

Regulatory sandboxes can provide a mechanism for dealing with emerging technologies.

Instead of imposing permanent rules immediately, regulators may:

• permit controlled experimentation;
• collect data;
• identify risks;
• consult stakeholders;
• revise regulations.

This converts radical uncertainty into managed regulatory learning.

However, sandboxes must not become a mechanism for avoiding accountability.

26. Public Participation as a Response

Participation can reduce relational uncertainty by allowing affected groups to enter governance networks.

This is particularly important for:

• renewable-energy projects;
• transmission infrastructure;
• dams;
• mining;
• nuclear facilities;
• energy corridors.

Public participation improves information flows and helps regulators identify consequences that technical agencies may overlook.

27. Theoretical Significance

The concept challenges the assumption that governance is simply a hierarchy.

It suggests that modern governance should be understood as a dynamic relational system.

Legal authority is therefore not merely a property possessed by an institution.

It is also expressed through relationships:

authority + interaction + dependence + information + accountability = network governance.

The more complex the network becomes, the more difficult it becomes to predict legal outcomes solely from formal institutional structures.

28. Key Case-Law Principles

29. Conclusion

Radical relational uncertainty in governance networks represents a major challenge for contemporary administrative and energy law.

The central problem is not merely that regulators lack information. The deeper problem is that legal responsibility, authority and causation become distributed across changing relationships among public institutions, private actors, infrastructure systems and technological platforms.

Indian constitutional and administrative law provides important tools for controlling this uncertainty. Articles 14, 21, 32 and 226, together with the principles developed in cases such as Ramana Dayaram Shetty, Ajay Hasia, Pradeep Kumar Biswas, Binny Ltd., Tata Cellular and PTC India, demonstrate that institutional complexity cannot be allowed to become a shield against accountability.

The future of governance therefore requires a shift from asking only “Which institution has power?” to asking:

“How is power distributed across the network, how do relationships generate consequences, and where does legal accountability attach?”

That shift is particularly important in energy governance, where interconnected grids, renewable generation, storage, AI, smart meters and private infrastructure operators are making regulatory relationships increasingly complex. The appropriate legal response is not to eliminate uncertainty—which may be impossible—but to make uncertainty traceable, procedurally fair, reviewable and institutionally accountable.