Attention Manipulation Claims — India

1. Meaning

Attention manipulation claims refer to legal claims arising when a person, platform, advertiser, employer, service provider, political actor, app developer, or other entity deliberately designs or uses a system to capture, retain, redirect, or exploit a person's attention through techniques that may be deceptive, coercive, addictive, discriminatory, privacy-invasive, or otherwise unlawful.

The concept is particularly relevant to:

social-media platforms;

recommendation algorithms;

short-video applications;

online advertising;

dark patterns;

personalised feeds;

notification systems;

autoplay;

infinite scrolling;

algorithmic ranking;

behavioural profiling;

targeted advertising;

manipulative interface design;

gamification;

persuasive AI systems.

Important legal qualification

India does not currently have a standalone statutory cause of action called an "attention manipulation claim."

Instead, such claims must generally be constructed using existing areas of law, including:

Consumer Protection Act, 2019;

Consumer Protection (E-Commerce) Rules, 2020;

Guidelines for Prevention and Regulation of Dark Patterns, 2023;

Information Technology Act, 2000;

Digital Personal Data Protection Act, 2023 and applicable rules/commencement framework;

Contract Act, 1872;

tort law;

constitutional rights;

privacy law;

advertising law;

competition law;

child-protection law;

intellectual-property law;

sector-specific regulation.

Therefore:

Attention manipulation is better understood as an emerging factual theory of liability rather than a fully independent Indian cause of action.

2. What Is "Attention Manipulation"?

Attention manipulation occurs when the architecture of a service is deliberately designed to influence what a person notices, how long they remain engaged, what they click, what they purchase, or what information they consume.

Not every attempt to attract attention is unlawful.

For example:

ordinary advertising;

attractive website design;

promotional emails;

lawful recommendations;

ordinary loyalty programmes

are not automatically attention manipulation in the legal sense.

The legal problem becomes stronger where the technique involves:

deception + exploitation of vulnerability + lack of meaningful choice + concealed commercial purpose + significant harm.

3. Common Examples

A. Infinite Scrolling

A platform continuously loads new content without requiring the user to make a deliberate stopping decision.

Potential issue:

Does the design intentionally impair meaningful user control over continued engagement?

B. Autoplay

One video automatically starts after another.

Potential legal issues include:

consumer autonomy;

dark patterns;

excessive engagement;

child protection;

privacy;

misleading design.

C. Manipulative Notifications

Examples:

repeated notifications;

false urgency;

emotionally charged alerts;

"You are missing out" messages;

notifications designed primarily to induce reopening of the application.

D. Personalised Recommendation Algorithms

An algorithm may learn that certain emotionally provocative content keeps a user engaged and repeatedly recommend similar material.

Potential claims can arise if the system causes:

deception;

discriminatory treatment;

privacy violations;

unlawful profiling;

consumer harm;

other legally recognised injury.

4. Dark Patterns and Attention Manipulation

The concept is particularly connected with dark patterns.

The 2023 Indian guidelines define dark patterns as practices or deceptive design patterns using UI/UX interactions to mislead or trick users into taking actions they did not originally intend or want to take.

Examples include:

false urgency;

basket sneaking;

confirm shaming;

forced action;

subscription traps;

interface interference;

bait and switch;

disguised advertisements;

nagging;

trick wording.

Thus:

Many dark patterns can be understood as specific techniques of attention and behavioural manipulation.

5. Attention Manipulation and Consumer Law

The Consumer Protection Act, 2019 is one of the most important legal frameworks.

A claim may arise where manipulative design produces:

unfair trade practice;

misleading representation;

deficiency in service;

unfair contractual conditions;

misleading advertising.

The Consumer Protection Act is particularly relevant where the user is acting as a consumer.

6. Unfair Trade Practice

An attention-manipulation strategy may become legally problematic when it is part of an unfair trade practice.

For example:

A shopping platform repeatedly displays a countdown timer saying "5 minutes remaining" even though the same offer automatically resets every five minutes.

The issue is no longer merely attractive design.

It potentially involves false urgency designed to induce a purchase.

7. Consumer Protection and Dark Patterns

The Guidelines for Prevention and Regulation of Dark Patterns, 2023 are particularly relevant.

They identify and regulate specified deceptive interface practices.

Therefore, attention manipulation claims may be strengthened where the claimant can demonstrate:

a manipulative interface;

a commercial purpose;

misleading or coercive design;

impairment of informed choice;

resulting consumer harm.

8. Privacy Dimension

Attention manipulation frequently depends upon personal data.

A platform may collect information concerning:

browsing behaviour;

clicks;

watch time;

searches;

location;

device information;

purchase history;

interests;

interaction patterns.

It may then use those data to construct behavioural profiles.

This creates a second legal question:

Was the person's data lawfully collected and used to construct the behavioural system that manipulated attention?

The constitutional right to privacy is therefore highly relevant.

9. K.S. Puttaswamy v Union of India

K.S. Puttaswamy v Union of India, (2017) 10 SCC 1

This is the foundational Indian privacy judgment.

The Supreme Court recognised privacy as a constitutionally protected right under Article 21 and the broader guarantees of Part III.

Relevance to attention manipulation

A sophisticated attention-manipulation system may involve:

behavioural profiling;

monitoring;

inference;

targeted advertising;

personalised recommendations.

These practices can raise privacy questions where personal information is collected or processed.

Puttaswamy therefore supplies the constitutional privacy foundation even though it was not an attention-manipulation case.

10. Puttaswamy and Informational Privacy

The privacy judgment is especially important because modern attention systems may not simply observe what users voluntarily disclose.

They can infer:

preferences;

interests;

habits;

emotional responses;

behavioural patterns.

This makes informational privacy central to attention-manipulation analysis.

11. K.S. Puttaswamy (Aadhaar) Case

K.S. Puttaswamy (Aadhaar) v Union of India, (2019) 1 SCC 1

The Supreme Court examined issues concerning:

informational privacy;

proportionality;

collection and use of personal data;

institutional safeguards.

Relevance

An attention-manipulation claim involving extensive behavioural profiling can raise questions about:

purpose limitation, proportionality, data minimisation and safeguards.

The Aadhaar decision therefore provides useful constitutional principles even though it does not concern commercial social-media manipulation.

12. Shreya Singhal v Union of India

Shreya Singhal v Union of India, (2015) 5 SCC 1

The Supreme Court examined restrictions on online speech under the Information Technology Act.

Principle

Restrictions affecting online expression must satisfy constitutional requirements, particularly those associated with Article 19(1)(a) and Article 19(2).

Relevance

Algorithmic attention systems influence:

visibility;

ranking;

amplification;

suppression;

distribution.

However, an important distinction must be maintained:

Content moderation and attention manipulation are not identical legal issues.

An algorithm's amplification of particular content may implicate speech rights where governmental action is involved, but private platform conduct does not automatically become State action.

13. Anuradha Bhasin v Union of India

Anuradha Bhasin v Union of India, (2020) 3 SCC 637

The Supreme Court examined restrictions on internet access and their relationship with fundamental rights.

Relevance

The judgment reinforces the importance of:

proportionality;

constitutional scrutiny;

internet-mediated expression;

reasoned restrictions.

For attention manipulation claims, the case helps explain why the digital environment cannot be treated as constitutionally irrelevant.

14. Internet and Mobile Association of India v RBI

Internet and Mobile Association of India v Reserve Bank of India, (2020) 10 SCC 274

The Supreme Court invalidated the RBI's circular restricting regulated entities from dealing with cryptocurrency businesses, applying proportionality analysis.

Relevance

Although not an attention-manipulation case, it demonstrates the importance of:

rational connection + necessity/proportionality + evidence-based regulatory interference.

This can be relevant when assessing regulatory responses to algorithmic behavioural systems.

15. Consumer Education and Research Centre v Union of India

Consumer Education & Research Centre v Union of India, (1995) 3 SCC 42

The Supreme Court recognised important dimensions of consumer welfare and Article 21.

Relevance

The broader principle is that consumer protection can intersect with fundamental rights where commercial practices have serious implications for health, dignity or welfare.

This becomes relevant where attention manipulation is alleged to produce substantial harm rather than merely annoyance.

16. Lucknow Development Authority v M.K. Gupta

Lucknow Development Authority v M.K. Gupta, (1994) 1 SCC 243

This landmark consumer-law case expanded the understanding of consumer remedies and recognised compensation for harassment and consequential injury arising from deficient services.

Relevance

Attention-manipulation claims may potentially fall within consumer jurisdiction where:

a consumer relationship exists;

the service is deficient or misleading;

the claimant establishes legally cognisable injury.

The case supports a broad, remedial approach to consumer protection.

17. IMA v V.P. Shantha

Indian Medical Association v V.P. Shantha, (1995) 6 SCC 651

The Supreme Court examined whether medical services fall within consumer protection law.

Relevance

The case illustrates the broader proposition that commercial/service relationships may attract consumer remedies where the statutory requirements are satisfied.

It is not an attention-manipulation case but can be used by analogy in service-based digital disputes.

18. Central Inland Water Transport Corp. v Brojo Nath Ganguly

Central Inland Water Transport Corporation v Brojo Nath Ganguly, (1986) 3 SCC 156

The Supreme Court invalidated an unconscionable contractual term in the circumstances of that case.

Relevance

Attention manipulation may be incorporated into standard-form digital contracts.

If the overall contractual architecture becomes:

oppressive;

unconscionable;

substantially one-sided;

contract-law principles may become relevant.

19. LIC of India v Consumer Education & Research Centre

LIC of India v Consumer Education & Research Centre, (1995) 5 SCC 482

The Supreme Court examined unequal bargaining power and unfair contractual conditions.

Relevance

Digital platforms often use:

standard-form terms;

non-negotiable conditions;

complex consent interfaces.

Where manipulative design is combined with an oppressive contractual arrangement, this jurisprudence may become relevant.

20. E.P. Royappa v State of Tamil Nadu

E.P. Royappa v State of Tamil Nadu, (1974) 4 SCC 3

The Supreme Court developed the modern understanding of arbitrariness under Article 14.

Relevance

If attention-ranking or algorithmic systems are used by governmental authorities, arbitrary allocation of visibility, access or services could potentially raise Article 14 issues.

But a private platform's algorithm does not automatically attract Article 14.

21. Maneka Gandhi v Union of India

Maneka Gandhi v Union of India, (1978) 1 SCC 248

The Supreme Court established the interconnectedness of Articles 14, 19 and 21 and emphasised fairness and non-arbitrariness in State action.

Relevance

Where the State uses algorithmic systems to influence citizens' information environment or behaviour, attention manipulation could potentially be examined through:

fairness;

reasonableness;

proportionality;

due process.

22. A.K. Kraipak v Union of India

A.K. Kraipak v Union of India, (1969) 2 SCC 262

This landmark administrative-law decision emphasised the importance of natural justice and avoidance of arbitrariness.

Relevance

If a governmental algorithm determines:

benefits;

eligibility;

ranking;

access;

regulatory treatment;

and attention manipulation forms part of the governmental decision architecture, administrative-law safeguards may become relevant.

23. Tata Cellular v Union of India

Tata Cellular v Union of India, (1994) 6 SCC 651

The Supreme Court articulated important principles of judicial review of administrative action.

Relevance

Where public authorities procure or deploy attention-shaping technologies, judicial review may examine:

legality;

rationality;

procedural propriety;

public interest.

24. Competition-Law Dimension

Attention manipulation can also have a competition-law dimension.

A dominant digital platform might use control over:

ranking;

recommendations;

advertising;

user attention;

access to consumers

to disadvantage competitors.

Potential issues may involve:

abuse of dominant position;

discriminatory conditions;

denial of market access;

self-preferencing;

leveraging.

The Competition Act, 2002 may therefore become relevant depending on the facts.

25. Google Android Case — Competition Commission of India

The CCI's proceedings involving Google's Android ecosystem are important in understanding the competitive significance of control over digital ecosystems.

Although such proceedings are not classical "attention manipulation" cases, they illustrate how:

control over digital architecture can affect consumer choice, competition and market access.

Such authorities should be treated as competition-law analogies, rather than direct attention-manipulation precedents.

26. Attention Manipulation and Children

This is one of the most important emerging areas.

Children may be especially vulnerable to:

gamification;

autoplay;

addictive design;

personalised recommendations;

influencer marketing;

targeted advertising;

social validation mechanisms.

Where children are involved, legal scrutiny can become stronger because of:

child-protection principles;

privacy;

consumer protection;

education and welfare;

contractual capacity;

constitutional protection.

27. Article 21 and Psychological Autonomy

A sophisticated claim might argue that manipulative digital architecture interferes with:

autonomy;

decisional freedom;

dignity;

mental well-being.

The constitutional foundation for such arguments can be traced to Article 21 jurisprudence, particularly:

Puttaswamy;

Maneka Gandhi;

Suchita Srivastava.

However, it is important not to overstate the law:

Indian courts have not yet recognised a freestanding constitutional right called a "right against attention manipulation."

28. Suchita Srivastava v Chandigarh Administration

Suchita Srivastava v Chandigarh Administration, (2009) 9 SCC 1

The Supreme Court recognised important aspects of decisional autonomy and personal liberty.

Relevance

Attention manipulation claims may use autonomy-based reasoning where a system is alleged to substantially interfere with meaningful decision-making.

Again, this is an analogical constitutional authority, not a digital-platform case.

29. Navtej Singh Johar v Union of India

Navtej Singh Johar v Union of India, (2018) 10 SCC 1

The Supreme Court emphasised dignity, autonomy, equality and constitutional morality.

Relevance

These constitutional values may inform future claims involving technologies that substantially interfere with individual autonomy.

It should not, however, be presented as a precedent directly regulating recommendation algorithms.

30. Defamation Dimension

Attention manipulation can also cause defamation problems.

Example:

An algorithm repeatedly recommends false allegations about a person, substantially amplifying them to users.

Potential legal questions include:

defamatory imputation;

publication;

identification;

knowledge;

negligence;

platform responsibility;

intermediary protection;

applicable defences.

Relevant cases include:

Subramanian Swamy v Union of India, (2016) 7 SCC 221

The Supreme Court upheld the constitutional validity of criminal defamation.

R. Rajagopal v State of Tamil Nadu, (1994) 6 SCC 632

Important for privacy, publication and reputational interests.

These cases do not create an independent "algorithmic amplification" tort, but they provide the underlying legal principles.

31. Attention Manipulation and Misrepresentation

Suppose a platform uses:

"Only 2 seats remaining!"

when there are actually 500 seats available.

The problem may involve:

false representation;

consumer deception;

unfair trade practice;

contract;

misleading advertising.

Potentially relevant authorities include:

Avadh Kishore Das v Ram Gopal, AIR 1979 SC 861;

Derry v Peek, (1889) 14 App Cas 337;

Hedley Byrne & Co Ltd v Heller & Partners Ltd, [1964] AC 465.

The English authorities are analogical only; the Indian statutory framework must be applied.

32. Attention Manipulation and Negligence

A negligence-based claim could theoretically require:

duty of care;

foreseeable risk;

breach;

causation;

legally recognised damage.

For example:

A service provider knows that its algorithm repeatedly promotes demonstrably dangerous content to a particularly vulnerable user group but fails to implement reasonable safeguards.

Whether this amounts to actionable negligence depends heavily on:

the relationship;

foreseeability;

statutory duties;

causation;

recognised injury.

There is currently no general Indian Supreme Court rule declaring all harmful algorithmic engagement to constitute negligence.

33. AI and Attention Manipulation

Artificial intelligence makes attention manipulation significantly more sophisticated.

An AI system can dynamically optimise:

headlines;

images;

timing;

recommendations;

notifications;

advertising;

emotional framing;

content order.

Instead of one fixed interface, the system may effectively run millions of personalised experiments.

This creates the possibility of:

individualised behavioural manipulation.

34. AI Recommendation and Legal Responsibility

The fact that an AI system generated a recommendation does not automatically eliminate legal responsibility.

The relevant questions remain:

Who deployed it?

Who controlled its objective?

What data did it use?

What safeguards existed?

Was the system monitored?

Was harmful behaviour foreseeable?

Were complaints received?

Was the system modified?

Did the provider make representations about safety?

35. Attention Manipulation and Data Protection

The Digital Personal Data Protection Act, 2023 is potentially important where personal data are processed to construct attention profiles.

Relevant questions include:

lawful processing;

notice;

consent where applicable;

legitimate statutory basis where applicable;

purpose;

data fiduciary responsibilities;

security safeguards;

rights of data principals;

children's data;

significant data fiduciary obligations where applicable.

Because commencement of the DPDP framework is phased, the applicable provision and effective date must be checked for the relevant transaction.

36. Children's Data

The DPDP framework contains special provisions relating to children.

Attention-manipulation systems directed toward children therefore require particular caution.

Potential issues include:

behavioural tracking;

profiling;

targeted advertising;

consent mechanisms;

age verification;

manipulative engagement;

excessive notifications.

A child-focused attention system can therefore generate overlapping:

consumer + privacy + child-protection + contractual claims.

37. Attention Manipulation and Consent

A key question is:

Was the user's consent genuinely informed and voluntary?

Consent may be questionable where the interface:

hides the decline option;

makes acceptance extremely prominent;

repeatedly nags the user;

uses confusing language;

bundles unrelated permissions;

makes refusal practically difficult.

A click does not necessarily answer every legal question concerning meaningful consent.

38. "Consent" vs "Manipulated Choice"

This distinction is critical.

Ordinary choice

"Would you like to subscribe?"

with equally accessible:

Accept

Decline

Manipulative choice

"Yes! Give me amazing benefits"

while the refusal option says:

"No, I prefer to miss out."

The latter may raise dark-pattern and consumer-protection concerns.

39. Attention Manipulation and Contract Formation

A digital contract may be challenged where the interface materially interferes with meaningful assent.

Relevant Contract Act concepts include:

Section 10 — valid contracts;

Sections 13–14 — consent/free consent;

Sections 15–18 — coercion, undue influence, fraud, misrepresentation;

Section 19 — voidability in cases of absence of free consent;

Section 23 — unlawful consideration/object;

Section 74 — compensation/penalty issues.

Not every manipulative interface automatically makes a contract void.

The claimant must establish the relevant contractual doctrine.

40. Fraud and Misrepresentation

Where attention manipulation deliberately uses false information to induce a transaction, fraud or misrepresentation may become relevant.

For example:

A platform falsely represents that a product will disappear from sale within five minutes solely to induce immediate purchase.

The legal issue is not simply that the platform captured attention.

It is that:

attention was captured through a potentially false representation that materially affected the consumer's decision.

41. Attention Manipulation and Advertising

Advertising is inherently designed to attract attention.

Therefore:

Attention attraction ≠ unlawful attention manipulation.

The legal distinction becomes stronger where advertising is:

misleading;

disguised;

hidden;

falsely urgent;

targeted through unlawfully processed data;

directed at vulnerable users;

integrated so seamlessly that users cannot reasonably identify it as advertising.

42. Influencer Marketing

Attention manipulation can arise through influencers where commercial relationships are concealed.

Potential issues include:

misleading endorsement;

undisclosed paid promotion;

deceptive advertising;

consumer protection.

The legal framework may include consumer-protection rules and advertising guidelines.

43. Political Attention Manipulation

Political attention manipulation raises particularly complex questions.

Examples include:

algorithmic microtargeting;

emotionally manipulative political advertising;

artificial amplification;

bot-driven engagement;

personalised political messaging.

Potential legal areas include:

election law;

privacy;

constitutional speech rights;

IT law;

advertising regulation;

criminal law where specific offences are established.

However:

There is no general Indian tort called "political attention manipulation."

44. Private Platform vs State Action

This distinction is fundamental.

Government algorithm

Potentially engages:

Article 14;

Article 19;

Article 21;

administrative law;

judicial review.

Private platform

Generally relies more heavily on:

contract;

consumer law;

privacy/data law;

tort;

competition law;

statutory platform obligations.

A private company's algorithm does not automatically become subject to Article 14 merely because it affects many people.

45. Public Law Attention Manipulation

Where a public authority deliberately uses algorithmic systems to shape citizens' information consumption, a claimant may potentially raise:

arbitrariness;

proportionality;

lack of statutory authority;

violation of fundamental rights;

procedural unfairness;

inadequate reasons;

privacy violations.

Relevant authorities include:

A.K. Kraipak;

E.P. Royappa;

Maneka Gandhi;

Mohinder Singh Gill v Chief Election Commissioner, (1978) 1 SCC 405;

S.N. Mukherjee v Union of India, (1990) 4 SCC 594.

46. Remedies

Depending on the legal basis, possible remedies include:

Consumer remedies

refund;

compensation;

discontinuation of unfair practice;

corrective directions;

other statutory relief.

Contract remedies

rescission;

damages;

restitution;

injunction;

declaration.

Privacy/data remedies

Depending on the applicable statutory regime:

correction;

deletion/erasure-related remedies where applicable;

grievance mechanisms;

regulatory action;

compensation/penalties where legally provided.

Constitutional remedies

Under Articles 32/226 where State action and fundamental rights are implicated:

writ of mandamus;

certiorari;

prohibition;

declaration;

appropriate directions.

Competition remedies

Where the statutory requirements are satisfied:

investigation;

behavioural remedies;

penalties;

structural or other appropriate orders.

47. Evidentiary Requirements

Attention-manipulation claims can be technologically complex.

Useful evidence may include:

screenshots;

screen recordings;

notification histories;

interface versions;

terms of service;

privacy policies;

advertising records;

algorithmic outputs;

recommendation history;

data-access records;

transaction records;

expert reports;

internal communications obtained lawfully;

A/B testing evidence;

evidence of repeated complaints.

The claimant should establish a chain such as:

Design → Manipulative mechanism → User interaction → Reliance/behaviour → Harm

48. Causation

Causation may be the most difficult element.

It is not enough to say:

"The platform showed me content and I purchased something."

The claimant may need to establish:

what manipulation occurred;

how it altered the claimant's decision;

why the resulting loss was foreseeable;

what legally recognised injury resulted.

Causation becomes especially difficult where multiple independent factors influenced the user's decision.

49. Types of Harm

Potentially relevant harm includes:

Economic harm

unwanted purchases;

subscriptions;

financial loss;

fraudulent transactions.

Privacy harm

unauthorised profiling;

intrusive tracking;

unlawful data processing.

Reputational harm

algorithmically amplified false content.

Psychological/health-related harm

Potentially relevant where a legally recognised duty and injury can be established.

Autonomy harm

A developing constitutional and jurisprudential argument, rather than a universally established independent cause of action.

50. Defences

Platforms and service providers may argue:

1. User voluntarily chose the service

2. The interface was clearly disclosed

3. The conduct was ordinary advertising

4. No false statement was made

5. No personal data was unlawfully processed

6. No legally recognised injury occurred

7. Causation is speculative

8. The defendant was not responsible for third-party content

9. Statutory intermediary protections apply

10. The claimant agreed to contractual terms

The strength of these defences depends on the facts and applicable legislation.

51. Important Case-Law Table

52. Which Cases Are Direct and Which Are Analogical?

This distinction is especially important.

Direct attention-manipulation/dark-pattern Supreme Court precedent in India is presently very limited.

The cases above primarily provide the legal foundations from:

privacy;

consumer protection;

constitutional rights;

contract;

online speech;

proportionality;

administrative law.

Therefore, it would be inaccurate to say that the Supreme Court has already recognised a comprehensive "attention manipulation tort."

The law is evolving through existing doctrines.

53. Possible Claim Structure

A claimant can structure an attention-manipulation case as follows:

Issue 1 — What was the design?

Identify the specific mechanism:

autoplay / infinite scrolling / false urgency / disguised advertisement / personalised recommendation / notification bombardment.

Issue 2 — What was the legal duty?

Identify:

consumer duty;

contractual duty;

privacy/data obligation;

statutory duty;

constitutional obligation;

negligence duty.

Issue 3 — Was the mechanism deceptive or coercive?

Identify:

hidden information;

false representation;

unequal choice;

exploitation of vulnerability.

Issue 4 — Was there legally recognised harm?

Establish:

financial loss;

privacy injury;

reputational harm;

other recognised damage.

Issue 5 — Is there causation?

Connect:

design → manipulation → decision → loss.

54. Attention Manipulation Claim Formula

A useful legal formula is:

Manipulative Attention Design + Legal Duty + Deception/Coercion/Unlawful Profiling + Material Influence + Legally Recognised Harm + Causation = Potential Attention Manipulation Claim

For constitutional claims:

State Action + Attention-Shaping Mechanism + Fundamental Right + Arbitrariness/Disproportionality/Privacy Violation + Constitutional Injury = Potential Public-Law Claim

For consumer claims:

Consumer Relationship + Manipulative Design + Unfair/Misleading Practice + Consumer Harm = Potential Consumer Claim

55. Conclusion

Attention manipulation claims represent an emerging area of Indian technology, consumer, privacy and constitutional law rather than a standalone cause of action.

The strongest legal framework presently comes from combining:

Consumer Protection Act, 2019;

2023 Dark Patterns Guidelines;

Information Technology Act, 2000;

Digital Personal Data Protection Act, 2023, subject to applicable commencement;

Contract Act, 1872;

constitutional privacy and autonomy principles;

tort/negligence principles;

competition law, where market power is involved;

advertising and consumer-protection rules;

child-protection safeguards, where children are affected.

The most important judicial foundations are Puttaswamy, Puttaswamy (Aadhaar), Shreya Singhal, Anuradha Bhasin, Internet and Mobile Association of India, Lucknow Development Authority, Central Inland Water Transport, LIC v Consumer Education & Research Centre, Suchita Srivastava, E.P. Royappa, and Maneka Gandhi.

The central legal principle is that attracting attention is not itself unlawful. Liability becomes substantially stronger where attention is captured through deception, coercive interface design, unlawful profiling, exploitation of vulnerability, unfair commercial practices, or disproportionate interference with legally protected rights, and where the claimant can establish a recognised legal injury and causation.