Competition Law and Consciousness Data Ownership and Competition

1. Introduction

“Consciousness data” is an emerging concept covering highly intimate data generated from or about a person's cognitive, emotional, neurological, behavioural, or physiological state. It may include:

• brain-computer-interface (BCI) signals;
• neural activity and brain-signal datasets;
• eye movements and attention patterns;
• emotional and cognitive-state measurements;
• biometric and neurobiometric information;
• responses to immersive environments;
• data generated by neuroprosthetics and wearable devices;
• inferred mental-state or behavioural profiles produced by AI.

The competition-law problem arises when a firm obtains exclusive or unusually extensive control over such data and uses that control to create entry barriers, foreclose competitors, discriminate against users or business partners, or reinforce an existing digital ecosystem.

The important distinction is that data ownership is not automatically equivalent to market power. Competition law generally asks whether control over the data gives the undertaking a significant competitive advantage and whether its conduct harms the competitive process.

China is particularly relevant because its competition framework increasingly addresses the interaction between data, algorithms, platforms and unfair competition. China's 2024 Interim Provisions on Internet Unfair Competition, for example, prohibit undertakings from using technical means to unlawfully obtain or use data lawfully held by another undertaking where this disrupts normal operation or fair competition.

2. Meaning of Consciousness Data

Consciousness data can be divided into four broad categories.

A. Direct neural data

Information directly obtained from neurological activity, such as:

• EEG signals;
• neural impulses;
• brain-computer-interface outputs;
• cortical activity;
• neural responses to stimuli.

B. Physiological proxies

Data that may indirectly reveal cognitive or emotional states:

• heart-rate variability;
• pupil dilation;
• facial expressions;
• eye tracking;
• galvanic skin response;
• sleep patterns.

C. Behavioural data

Information about:

• attention;
• preferences;
• reaction times;
• purchasing behaviour;
• interaction with digital environments;
• responses to advertisements or virtual environments.

D. Inferred consciousness data

This is potentially the most commercially valuable category.

An AI system could take raw neural or behavioural signals and infer:

“This person is distracted,”
“This person is experiencing stress,”
“This person prefers product A,”
“This user is highly susceptible to particular advertising,”

or construct a probabilistic cognitive profile.

Thus, competition concerns may exist even where the underlying raw data is not itself commercially valuable.

3. Is Consciousness Data “Owned” by Someone?

There is no universal legal rule under which a company automatically owns all data generated by a consumer.

Several legal interests may overlap:

Consequently, “data ownership” and “data control” should not be treated as identical concepts.

From a competition-law perspective, control may be more important than formal ownership.

A company may have no absolute property right in every individual data point but may nevertheless possess:

• exclusive access;
• superior aggregation capability;
• proprietary processing technology;
• exclusive interfaces;
• switching barriers;
• contractual restrictions preventing competitors from accessing the dataset.

That combination can create substantial market power.

4. Why Consciousness Data Can Create Competition Problems

A. Data as an entry barrier

Suppose a dominant neurotechnology platform possesses ten years of neural-response data from millions of users.

A new entrant may technically be able to build a competing BCI system, but it cannot reproduce:

• the historical dataset;
• training data;
• user-specific calibration;
• behavioural correlations;
• AI models trained on the data.

The incumbent therefore possesses a data-based competitive advantage.

B. Data network effects

The relationship can be circular:

More users → more consciousness data → better AI model → better product → more users → more data

This creates a feedback loop.

A competitor with fewer users may therefore face difficulty reaching the scale necessary to compete.

5. Data Advantage Versus Dominance

Possession of a large dataset does not automatically establish dominance.

Competition authorities would normally examine factors such as:

1. relevant product market;
2. geographic market;
3. market shares;
4. substitutability;
5. uniqueness of the dataset;
6. ability to replicate the data;
7. frequency of data collection;
8. interoperability;
9. switching costs;
10. network effects;
11. access to alternative datasets;
12. duration of the data advantage.

A small company with an exclusive dataset may not have market power.

Conversely, a platform possessing several complementary datasets may acquire substantial ecosystem power.

6. Main Competition-Law Theories

A. Refusal to provide data access

A dominant undertaking could potentially violate competition law if it refuses access to an indispensable dataset under circumstances satisfying the applicable essential-facilities/refusal-to-deal doctrine.

The analysis would normally require consideration of:

• indispensability;
• absence of realistic alternatives;
• elimination or substantial weakening of competition;
• objective justification;
• proportionality of the requested access.

B. Discriminatory access

A dominant consciousness-data platform could give:

• its own downstream business full access;
• affiliated companies preferential access;
• independent competitors limited access.

This creates a classic vertical foreclosure problem.

C. Self-preferencing

A platform could use consciousness data to favour its own:

• neurotechnology applications;
• advertising service;
• healthcare platform;
• virtual-reality ecosystem;
• AI assistant.

For example:

Platform collects neural-attention data → analyses it → ranks its own applications using superior behavioural intelligence.

The issue is not merely data collection but using privileged information to disadvantage rivals.

D. Exclusive data arrangements

A dominant undertaking could require users, hospitals, universities or device manufacturers to provide data exclusively to its platform.

Exclusive arrangements can become problematic where they substantially foreclose competitors.

E. Data tying

A company could condition access to one product on compulsory surrender of consciousness data.

For example:

“You may use the neuro-interface only if all cognitive-response data is transferred to our advertising platform.”

If the undertaking possesses sufficient market power, this may raise tying, exploitative or exclusionary concerns.

7. Privacy Can Become a Competition Parameter

Traditional competition analysis frequently focuses on:

• price;
• output;
• quality;
• innovation.

Digital markets demonstrate that privacy can also constitute a dimension of competition.

A service offering stronger privacy protections may compete against a service requiring extensive data collection.

This is particularly significant for consciousness data because the information may be substantially more intimate than ordinary browsing data.

The European Commission's 2025 DMA decision concerning Meta illustrates this developing intersection: the Commission found Meta in breach of the DMA obligation concerning consumers' ability to choose a service using less personal data and imposed a €200 million fine.

Thus, competition regulation increasingly recognises that data practices can affect consumer choice and competitive conditions.

8. Six Important Case Laws

Because consciousness-data litigation is still developing, there are not yet six major reported judgments specifically concerning neural/consciousness data ownership. The better legal methodology is therefore to use leading data-driven competition and platform cases as precedents for analysing future consciousness-data disputes.

Case 1: FTC v. Facebook, Inc. / Meta Platforms

Principle

The FTC's case against Facebook concerns alleged maintenance of monopoly power through acquisitions and restrictions involving platform access and interoperability.

The FTC alleged that Facebook used acquisitions of Instagram and WhatsApp and restrictions involving API access to maintain its personal-social-networking monopoly.

Relevance to consciousness data

The case illustrates how control over a digital ecosystem can be connected with:

• data accumulation;
• network effects;
• interoperability;
• API access;
• acquisition of emerging competitors.

A consciousness-data platform acquiring promising BCI competitors could generate analogous competition concerns.

Legal lesson: data accumulation can become strategically important when combined with network effects and exclusionary conduct.

Case 2: Bundeskartellamt v. Facebook/Meta

Principle

The German competition authority's Facebook proceedings are particularly important because they demonstrate the connection between:

competition + personal data + platform power.

The central concern was whether Facebook's market power could be exercised through extensive combination and use of user data.

Relevance

The case provides an important conceptual foundation for analysing consciousness-data markets.

If a dominant neurotechnology platform makes access to its service conditional on extensive data collection, the relevant question becomes:

Is the data practice merely a privacy matter, or can it also constitute an exercise of market power affecting competition?

Legal lesson

Data-processing conditions may have competition significance where they are imposed by a powerful platform and materially affect competitive conditions.

Case 3: Google Search / Google Data Access

The European Union's developing digital-market regime provides an especially important contemporary example.

Under Article 6(11) of the Digital Markets Act, Google is required to provide eligible search engines with access to anonymised Google Search data on fair, reasonable and non-discriminatory terms.

In 2026, the Commission adopted measures specifying how Google must make such search data available, including to eligible beneficiaries such as AI chatbots offering search functionalities.

Relevance

The principle is highly relevant to consciousness data.

Suppose a dominant BCI platform has the world's largest database of:

• neural responses;
• cognitive patterns;
• attention signals.

If competitors cannot reasonably reproduce that dataset, regulators may consider whether appropriate data-access mechanisms are necessary to prevent data-based entrenchment.

Legal lesson

Control over strategically important data can become a regulatory competition issue even without conventional price discrimination.

Case 4: Google Shopping

Google Shopping is relevant because it illustrates the relationship between:

• vertically integrated platforms;
• proprietary information;
• self-preferencing;
• downstream competition.

The European Commission has continued to regulate Google's treatment of its own services relative to third-party services. In July 2026, the Commission found Google in breach of the DMA's self-preferencing obligation concerning Google Search.

Application to consciousness data

Imagine:

BCI platform → collects consciousness data → owns app store → operates its own cognitive-health applications.

If the platform uses privileged consciousness data to favour its own downstream applications, competition concerns could arise.

Legal lesson

The critical issue is not simply ownership of information but using informational advantages to disadvantage rivals.

Case 5: Epic Games v. Google

The Epic Games litigation concerning Google Play is another useful platform precedent.

The FTC's intervention highlighted the importance of:

• network effects;
• data feedback loops;
• platform incumbency;
• restoring competition through effective remedies.

The FTC expressly identified data feedback loops and network effects as relevant considerations in determining whether a remedy can restore competition in digital markets.

Relevance

Consciousness-data ecosystems may exhibit even stronger feedback effects:

Users → neural data → AI training → better predictions → more users → more neural data.

Consequently, a remedy limited merely to stopping one exclusionary contract may be insufficient if the underlying data advantage continues to entrench the incumbent.

Case 6: Google Android

The Google Android competition proceedings demonstrate how control over an ecosystem can interact with:

• default arrangements;
• application distribution;
• interoperability;
• platform dependence;
• foreclosure of competing services.

The relevance to consciousness-data markets lies in the ecosystem model.

A BCI manufacturer may simultaneously control:

1. hardware;
2. operating system;
3. app marketplace;
4. cloud infrastructure;
5. AI model;
6. consciousness-data repository.

The combination can produce a vertically integrated ecosystem where competitors depend upon the dominant undertaking.

Legal lesson

Competition analysis should examine the whole ecosystem, rather than considering the data market in isolation.

9. China: Particularly Important Legal Framework

For China, the analysis can be built around three principal bodies of law.

A. Anti-Monopoly Law

The amended Chinese Anti-Monopoly Law provides the principal framework for:

• monopoly agreements;
• abuse of dominant market position;
• concentrations;
• abuse involving digital platforms.

Digital platforms are particularly important because market power can arise from:

• network effects;
• economies of scale;
• data;
• algorithms;
• technological advantages;
• user dependence.

B. Anti-Unfair Competition Law

China's competition framework also addresses conduct involving online platforms and data.

The 2024 Interim Provisions on Internet Unfair Competition specifically prohibit technical methods used to unlawfully obtain or use data lawfully held by another undertaking where this interferes with normal operation or fair competition.

This is particularly relevant where consciousness data is:

• collected by one platform;
• processed by another;
• scraped by a competitor;
• transferred through APIs;
• used to train competing AI systems.

C. Personal Information Protection Law

Consciousness data may also involve highly sensitive personal information.

Consequently, a competition analysis cannot be separated entirely from:

• lawful collection;
• purpose limitation;
• consent;
• processing restrictions;
• security;
• cross-border transfer.

This creates a distinctive legal problem:

Competition law may favour greater access to data, while privacy law may restrict such access.

The solution is not unrestricted data sharing.

The legally appropriate objective is generally pro-competitive access compatible with privacy and data-security requirements.

10. Consciousness Data and Essential Facilities

This is one of the most significant theoretical issues.

Suppose Company A possesses:

• 95% of commercially usable BCI data;
• the dominant BCI operating system;
• millions of calibrated devices;
• the only interoperable neural-data API.

Competitors request access.

The essential-facility analysis could ask:

1. Is the dataset indispensable?

Can competitors realistically create an equivalent dataset?

2. Is duplication feasible?

Can the competitor collect comparable data without enormous cost or time?

3. Does refusal eliminate competition?

Would denial prevent meaningful competition?

4. Is there objective justification?

For example:

• cybersecurity;
• privacy;
• patient safety;
• trade secrets;
• data integrity.

5. Can access be provided safely?

Possible mechanisms include:

• anonymisation;
• secure APIs;
• federated learning;
• clean rooms;
• restricted research access;
• licensing.

11. Data Portability

Data portability can reduce switching costs.

Imagine a consumer has accumulated ten years of:

• neural profiles;
• cognitive-response history;
• BCI calibration;
• personalised AI settings.

Switching to another provider may require abandoning all of that information.

The result is:

Data accumulation → switching costs → customer lock-in → reduced competitive pressure.

Therefore, portability may become a competition-enhancing remedy.

However, portability must protect:

• third-party information;
• trade secrets;
• security;
• privacy;
• intellectual property.

12. Consciousness Data and Mergers

Data can also affect merger control.

Consider:

Dominant BCI platform + leading neuro-AI startup.

Even if the startup has:

• low revenue;
• few users;
• no substantial profits,

its consciousness dataset may have significant strategic value.

Traditional turnover thresholds may therefore fail to capture the competitive importance of the transaction.

Authorities may examine:

• nascent competition;
• potential competition;
• data assets;
• innovation pipelines;
• interoperability;
• future market entry.

The FTC's examination of technology-company acquisitions illustrates why acquisitions involving emerging digital competitors can attract scrutiny even where individual transactions did not initially trigger ordinary reporting requirements.

13. Consciousness Data and Algorithmic Competition

A particularly difficult problem occurs when consciousness data is fed into AI systems.

For example:

Neural data → AI model → prediction of emotional state → personalised advertising → behavioural response → additional data

This creates a self-reinforcing algorithmic loop.

A dominant undertaking may therefore possess not merely a dataset but:

Data + model + infrastructure + users + feedback loop.

That combination can be considerably more difficult for competitors to replicate.

14. Potential Abuses

15. Possible Remedies

Competition authorities could potentially employ several remedies.

Structural remedies

• divestiture;
• separation of business units;
• restrictions on data combination.

Behavioural remedies

• non-discriminatory access;
• API access;
• data portability;
• interoperability;
• prohibition of self-preferencing;
• prohibition of exclusive data arrangements.

Technical remedies

• secure data rooms;
• privacy-preserving computation;
• federated learning;
• anonymisation;
• differential privacy;
• interoperable data formats.

Merger remedies

• data-access commitments;
• firewalls;
• restrictions on combining datasets;
• licensing obligations;
• interoperability commitments.

16. Six Core Competition-Law Principles

The emerging doctrine can therefore be reduced to six principles:

Principle 1 — Data ownership is not automatically market power

The size, uniqueness and strategic importance of the dataset matter.

Principle 2 — Control can matter more than ownership

A firm can possess decisive competitive power through contractual or technical control without holding conventional property rights.

Principle 3 — Data becomes especially significant when combined with network effects

Large datasets can create feedback loops that strengthen incumbency.

Principle 4 — Privacy and competition can overlap

Privacy degradation may constitute a dimension of product quality and consumer choice.

Principle 5 — Data access remedies must respect privacy

Competition law should not require indiscriminate disclosure of sensitive consciousness information.

Principle 6 — AI makes data advantages cumulative

The combination of data, algorithms, computing infrastructure and user networks can create substantially stronger barriers than the dataset alone.

17. Hypothetical Example

Assume NeuroX operates the largest BCI platform.

It has:

• 70% of active BCI users;
• the largest neural-response dataset;
• the leading BCI operating system;
• its own AI model;
• its own cognitive-health applications.

A competing company, MindAI, requests anonymised neural-response data.

NeuroX refuses.

At the same time, NeuroX provides its own subsidiary with extensive access to the same data.

The potential competition issues are:

1. Relevant market — BCI services, neural-data services or a broader technology market?
2. Dominance — Does NeuroX possess substantial market power?
3. Data indispensability — Can MindAI reproduce the dataset?
4. Refusal to deal — Is access necessary for effective competition?
5. Discrimination — Why does NeuroX's affiliate receive better access?
6. Self-preferencing — Does NeuroX favour its own applications?
7. Privacy — Can data be shared lawfully?
8. Interoperability — Can MindAI access the system through APIs?
9. Innovation — Does exclusion reduce technological innovation?
10. Remedy — Could privacy-preserving data access restore competitive conditions?

This illustrates why consciousness-data competition law is likely to be an interdisciplinary field rather than a simple question of data ownership.

18. Conclusion

Consciousness data is likely to become an important competition-law asset as BCI, neurotechnology, immersive computing and AI develop.

The central legal question will not simply be:

“Who owns the consciousness data?”

It will increasingly be:

“Who controls access to the data, what competitive advantages does that control create, and is that control being used to exclude or disadvantage competitors?”

The existing digital-competition cases involving Meta/Facebook, Google, Google Play and other platform ecosystems provide the foundational principles, even though they do not yet constitute a mature body of jurisprudence specifically on neural or consciousness data. The European Union's current DMA framework is particularly significant because it expressly addresses data access, interoperability and consumer choice in data-intensive platform markets.

For China, the combination of the Anti-Monopoly Law, Anti-Unfair Competition Law, data-governance rules and personal-information regulation provides a framework for analysing future disputes involving exclusive consciousness datasets, discriminatory access, data scraping, interoperability and platform dominance. China's 2024 Internet Unfair Competition provisions are especially relevant because they expressly address unlawful technical acquisition or use of another undertaking's lawfully held data.

Key Case-Law List

1. FTC v. Facebook, Inc. (Meta) — platform monopoly, acquisitions, API restrictions and network effects.
2. Bundeskartellamt v. Facebook/Meta — relationship between data practices, privacy and market power.
3. Google Search/Data Access under the EU DMA — access to strategically important search data.
4. Google Shopping — platform power and preferential treatment of own services.
5. Epic Games v. Google — platform foreclosure, network effects and data feedback loops.
6. Google Android — ecosystem power, interoperability and exclusionary platform practices.

These authorities should be understood as analogical precedents for consciousness-data competition, rather than as cases already deciding ownership of neural or consciousness data specifically.