Dark pattern: Difference between revisions

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A [[wikipedia:Dark pattern|dark pattern]] is a manipulative design practice that trick or influence users into making decisions that may not align with their true preferences or interests. These techniques exploit cognitive biases and behavioral psychology to benefit businesses, often at the expense of user autonomy. Initially coined by user experience (UX) designer Harry Brignull in 2010, the concept has evolved into a significant focus of regulatory scrutiny and academic research.<ref name=":0">{{cite web |title=Bringing Dark Patterns to Light |url=https://www.ftc.gov/reports/bringing-dark-patterns-light |archive-date=September 16, 2025 |archive-url=https://archive.ph/TZ5v3 |publisher=Federal Trade Commission |date=September 2022}}</ref><ref name=":1">{{cite web |last1=Brignull |first1=Harry |title=Dark Patterns: inside the interfaces designed to trick you |url=https://www.deceptive.design/ |archive-date= |archive-url= |website=Deceptive.Design}}</ref>

The prevalence of dark patterns is remarkably widespread, and they represent a growing concern in digital interfaces. A 2019 study examining 11,000 e-commerce websites found approximately 10% employed deceptive practices,<ref>{{Cite news |last=Cimpanu |first=Catalin |date=2019-11-11 |title=Study of over 11,000 online stores finds 'dark patterns' on 1,254 sites |url=https://www.zdnet.com/article/user-interface-dark-patterns-are-becoming-common-on-online-stores/ |access-date=2025-11-08 |work=ZDNET}}</ref> while a 2022 European Commission report indicated that 97% of popular apps used by EU consumers displayed them.<ref>{{Cite web |last=Lupiáñez-Villanueva |first=Francisco |last2=Boluda |first2=Alba |last3=Bogliacino |first3=Francesco |last4=Liva |first4=Giovanni |last5=Lechardoy |first5=Lucie |last6=Ballell |first6=Teresa Rodríguez de las Heras |title=Behavioural study on unfair commercial practices in the digital environment |url=https://op.europa.eu/en/publication-detail/-/publication/606365bc-d58b-11ec-a95f-01aa75ed71a1/language-en |access-date=2025-11-08 |website=Publications Office of the EU |doi=10.2838/859030 |isbn=978-92-76-52316-1}}</ref>

The prevalence of dark patterns is remarkably widespread, and they represent a growing concern in digital interfaces. A 2019 study examining 11,000 e-commerce websites found approximately 10% employed deceptive practices,<ref>{{Cite news |last=Cimpanu |first=Catalin |date=2019-11-11 |title=Study of over 11,000 online stores finds 'dark patterns' on 1,254 sites |url=https://www.zdnet.com/article/user-interface-dark-patterns-are-becoming-common-on-online-stores/ |access-date=2025-11-08 |work=ZDNET |url-status=live |archive-url=http://web.archive.org/web/20251114035001/https://www.zdnet.com/article/user-interface-dark-patterns-are-becoming-common-on-online-stores/ |archive-date=14 Nov 2025}}</ref> while a 2022 European Commission report indicated that 97% of popular apps used by EU consumers displayed them.<ref>{{Cite web |last=Lupiáñez-Villanueva |first=Francisco |last2=Boluda |first2=Alba |last3=Bogliacino |first3=Francesco |last4=Liva |first4=Giovanni |last5=Lechardoy |first5=Lucie |last6=Ballell |first6=Teresa Rodríguez de las Heras |title=Behavioural study on unfair commercial practices in the digital environment |url=https://op.europa.eu/en/publication-detail/-/publication/606365bc-d58b-11ec-a95f-01aa75ed71a1/language-en |access-date=2025-11-08 |website=Publications Office of the EU |doi=10.2838/859030 |isbn=978-92-76-52316-1 |url-status=live |archive-url=http://web.archive.org/web/20260118190152/https://op.europa.eu/en/publication-detail/-/publication/606365bc-d58b-11ec-a95f-01aa75ed71a1/language-en |archive-date=18 Jan 2026}}</ref>

==Definition and terminology==

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===Obstruction patterns===

These designs make desired actions (like rejecting tracking) significantly more difficult than accepting alternatives. A classic example is the ''Roach Motel'' pattern, where signing up for a service is straightforward but cancellation is excessively difficult. The FTC highlighted this pattern in their case against ABCmouse, where cancellation was made "extremely difficult" despite promising "Easy Cancellation".<ref>{{Cite web |author=Keller and Heckman LLP |date=2020-09-28 |title=FTC Targets Negative Option Schemes in Two Multimillion Dollar Settlements |url=https://www.lexology.com/library/detail.aspx?g=a2def591-a71f-477d-8f39-55f9b40ec125 |access-date=2025-11-08 |website=Lexology}}</ref>

These designs make desired actions (like rejecting tracking) significantly more difficult than accepting alternatives. A classic example is the ''Roach Motel'' pattern, where signing up for a service is straightforward but cancellation is excessively difficult. The FTC highlighted this pattern in their case against ABCmouse, where cancellation was made "extremely difficult" despite promising "Easy Cancellation".<ref>{{Cite web |author=Keller and Heckman LLP |date=2020-09-28 |title=FTC Targets Negative Option Schemes in Two Multimillion Dollar Settlements |url=https://www.lexology.com/library/detail.aspx?g=a2def591-a71f-477d-8f39-55f9b40ec125 |access-date=2025-11-08 |website=Lexology |url-status=live |archive-url=http://web.archive.org/web/20251114165251/https://www.lexology.com/library/detail.aspx?g=a2def591-a71f-477d-8f39-55f9b40ec125 |archive-date=14 Nov 2025}}</ref>

===Interface interference===

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==Mind tricks and business incentives==

===Cognitive biases exploitation===

Dark patterns trick users by taking advantage of unconscious thoughts. For example, in cookie banners the "Accept All" option is the first option listed and uses a green background. People tend to choose the first option before considering others. Green is associated with good in design. In cookie banners, there is also a "Manage my choices" option that typically involves opting out of each data collection category or website one at a time. It is easier for users to accept all cookies than to decline them, due to using dark patterns.<ref>{{Cite web |last=Stroink-Skillrud |first=Donata |date=2023-02-02 |title=Your Cookie Conset Banner is (Probably) Not Compliant |url=https://mainwp.com/cookie-consent-banner-probably-not-compliant/ |access-date=2025-11-08 |website=MainWP Blog}}</ref><ref name=":2">{{Cite web |last=Keyser |first=Robert |date=2023-10-05 |title=Cookie Consent Dark Patterns: How to Identify and Fix Them |url=https://www.ethyca.com/news/all-about-dark-patterns |access-date=2025-08-11 |website=Ethyca}}</ref>

Dark patterns trick users by taking advantage of unconscious thoughts. For example, in cookie banners the "Accept All" option is the first option listed and uses a green background. People tend to choose the first option before considering others. Green is associated with good in design. In cookie banners, there is also a "Manage my choices" option that typically involves opting out of each data collection category or website one at a time. It is easier for users to accept all cookies than to decline them, due to using dark patterns.<ref>{{Cite web |last=Stroink-Skillrud |first=Donata |date=2023-02-02 |title=Your Cookie Conset Banner is (Probably) Not Compliant |url=https://mainwp.com/cookie-consent-banner-probably-not-compliant/ |access-date=2025-11-08 |website=MainWP Blog |url-status=live |archive-url=https://web.archive.org/web/20260216033732/https://mainwp.com/cookie-consent-banner-probably-not-compliant/ |archive-date=16 Feb 2026}}</ref><ref name=":2">{{Cite web |last=Keyser |first=Robert |date=2023-10-05 |title=Cookie Consent Dark Patterns: How to Identify and Fix Them |url=https://www.ethyca.com/news/all-about-dark-patterns |access-date=2025-08-11 |website=Ethyca |url-status=live |archive-url=http://web.archive.org/web/20251212062415/https://www.ethyca.com/news/all-about-dark-patterns |archive-date=12 Dec 2025}}</ref>

===Incentives and short-term gains===

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==Legal and regulatory landscape==

===United States framework===

In the United States, regulation occurs primarily through existing consumer protection statutes . The FTC Act empowers the Federal Trade Commission to take action against "unfair or deceptive acts or practices in or affecting commerce".<ref name=":9">{{cite web |title=FTC Act |url=https://www.ftc.gov/legal-library/browse/statutes/federal-trade-commission-act |publisher=Federal Trade Commission}}</ref>

In the United States, regulation occurs primarily through existing consumer protection statutes . The FTC Act empowers the Federal Trade Commission to take action against "unfair or deceptive acts or practices in or affecting commerce".<ref name=":9">{{cite web |title=FTC Act |url=https://www.ftc.gov/legal-library/browse/statutes/federal-trade-commission-act |publisher=Federal Trade Commission |url-status=live |archive-url=http://web.archive.org/web/20260127043048/https://www.ftc.gov/legal-library/browse/statutes/federal-trade-commission-act |archive-date=27 Jan 2026}}</ref>

In October 2024, the FTC amended its Negative Option Rule to include specific requirements for cancellation mechanisms, implementing a "Click-to-Cancel" provision.<ref name=":10">{{cite web |title=FTC Strengthens Negative Option Rule |url=https://www.ftc.gov/news-events/news/press-releases/2024/10/ftc-strengthens-rule-protect-consumers-deceptive-subscription-practices |publisher=Federal Trade Commission |date=October 11, 2024}}</ref>

===European Union's approach===

The European approach combines general consumer protection laws with data privacy-specific regulations. While the [[General Data Protection Regulation]] (GDPR) doesn't explicitly mention dark patterns, its requirements for valid consent effectively prohibit many deceptive designs.<ref name=":11">{{cite web |title=Guidelines on Dark Patterns in Social Media Platform Interfaces |url=https://edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en |publisher=European Data Protection Board |date=2022}}</ref>

The European approach combines general consumer protection laws with data privacy-specific regulations. While the [[General Data Protection Regulation]] (GDPR) doesn't explicitly mention dark patterns, its requirements for valid consent effectively prohibit many deceptive designs.<ref name=":11">{{cite web |title=Guidelines on Dark Patterns in Social Media Platform Interfaces |url=https://edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en |publisher=European Data Protection Board |date=2022 |url-status=live |archive-url=http://web.archive.org/web/20251217115035/https://www.edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en |archive-date=17 Dec 2025}}</ref>

The [[Digital Services Act]] (DSA) and [[Digital Markets Act]] (DMA) further address dark patterns by prohibiting practices that "deceive or manipulate" users.<ref name=":12">{{cite web |title=Digital Services Act |url=https://digital-strategy.ec.europa.eu/en/policies/digital-services-act |publisher=European Commission}}</ref>

The [[Digital Services Act]] (DSA) and [[Digital Markets Act]] (DMA) further address dark patterns by prohibiting practices that "deceive or manipulate" users.<ref name=":12">{{cite web |title=Digital Services Act |url=https://digital-strategy.ec.europa.eu/en/policies/digital-services-act |publisher=European Commission |url-status=live |archive-url=https://web.archive.org/web/20260216033823/https://digital-strategy.ec.europa.eu/en/policies/digital-services-act |archive-date=16 Feb 2026}}</ref>

===Enforcement cases and penalties===

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*Epic Games paid $245 million to settle charges related to deceptive patterns in Fortnite.<ref name=":13">{{cite web |title=Epic Games to Pay $245 Million |url=https://www.ftc.gov/news-events/news/press-releases/2022/12/epic-games-pay-245-million-ftc-refund-consumers-accused-tricking-users-making-unauthorized-charges |publisher=Federal Trade Commission |date=December 19, 2022}}</ref>

*Noom paid $62 million to settle charges regarding deceptive subscription practices.<ref name=":14">{{cite web |title=Noom to Pay $62 Million |url=https://www.ftc.gov/news-events/news/press-releases/2024/03/noom-pay-62-million-settle-ftc-charges-it-misled-consumers-about-its-diet-programs-use-consumer-data |publisher=Federal Trade Commission |date=March 7, 2024}}</ref>

*TikTok received multimillion-euro fines for failing to protect children's data through manipulative consent practices.<ref>{{Cite web |date=2023-09-15 |title=Irish Data Protection Commission announces €345 million fine of TikTok |url=https://www.dataprotection.ie/en/news-media/press-releases/DPC-announces-345-million-euro-fine-of-TikTok |access-date=2025-11-08 |website=Data Protection Commision}}</ref>

*TikTok received multimillion-euro fines for failing to protect children's data through manipulative consent practices.<ref>{{Cite web |date=2023-09-15 |title=Irish Data Protection Commission announces €345 million fine of TikTok |url=https://www.dataprotection.ie/en/news-media/press-releases/DPC-announces-345-million-euro-fine-of-TikTok |access-date=2025-11-08 |website=Data Protection Commision |url-status=live |archive-url=http://web.archive.org/web/20260201165638/https://www.dataprotection.ie/en/news-media/press-releases/DPC-announces-345-million-euro-fine-of-TikTok |archive-date=1 Feb 2026}}</ref>

==Impact on consumers and businesses==

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==Detection, avoidance and mitigation==

===Technical detection and tools===

Efforts to automatically detect dark patterns are evolving but face significant challenges. A comprehensive study found that existing tools could only identify 31 of 68 identified dark pattern types, a coverage rate of just 45.5%.<ref name=":3">{{Cite web |last=Li |first=Meng |last2=Wang |first2=Xiang |last3=Nei |first3=Liming |last4=Li |first4=Chenglin |last5=Liu |first5=Yang |last6=Zhao |first6=Yangyang |last7=Xue |first7=Lei |last8=Kabir Sulaiman |first8=Said |date=2024-12-12 |title=[2412.09147] A Comprehensive Study on Dark Patterns |url=https://arxiv.org/abs/2412.09147 |access-date=2025-11-08 |website=arXiv |doi=10.48550/arXiv.2412.09147}}</ref> The study proposed a Dark Pattern Analysis Framework (DPAF) to address existing gaps.

Efforts to automatically detect dark patterns are evolving but face significant challenges. A comprehensive study found that existing tools could only identify 31 of 68 identified dark pattern types, a coverage rate of just 45.5%.<ref name=":3">{{Cite web |last=Li |first=Meng |last2=Wang |first2=Xiang |last3=Nei |first3=Liming |last4=Li |first4=Chenglin |last5=Liu |first5=Yang |last6=Zhao |first6=Yangyang |last7=Xue |first7=Lei |last8=Kabir Sulaiman |first8=Said |date=2024-12-12 |title=[2412.09147] A Comprehensive Study on Dark Patterns |url=https://arxiv.org/abs/2412.09147 |access-date=2025-11-08 |website=arXiv |doi=10.48550/arXiv.2412.09147 |url-status=live |archive-url=http://web.archive.org/web/20251109221611/https://www.arxiv.org/abs/2412.09147 |archive-date=9 Nov 2025}}</ref> The study proposed a Dark Pattern Analysis Framework (DPAF) to address existing gaps.

===Ethical design alternatives===

@@ Line 3: / Line 3: @@
 A [[wikipedia:Dark pattern|dark pattern]] is a manipulative design practice that trick or influence users into making decisions that may not align with their true preferences or interests. These techniques exploit cognitive biases and behavioral psychology to benefit businesses, often at the expense of user autonomy. Initially coined by user experience (UX) designer Harry Brignull in 2010, the concept has evolved into a significant focus of regulatory scrutiny and academic research.<ref name=":0">{{cite web |title=Bringing Dark Patterns to Light |url=https://www.ftc.gov/reports/bringing-dark-patterns-light |archive-date=September 16, 2025 |archive-url=https://archive.ph/TZ5v3 |publisher=Federal Trade Commission |date=September 2022}}</ref><ref name=":1">{{cite web |last1=Brignull |first1=Harry |title=Dark Patterns: inside the interfaces designed to trick you |url=https://www.deceptive.design/ |archive-date= |archive-url= |website=Deceptive.Design}}</ref>
-The prevalence of dark patterns is remarkably widespread, and they represent a growing concern in digital interfaces. A 2019 study examining 11,000 e-commerce websites found approximately 10% employed deceptive practices,<ref>{{Cite news |last=Cimpanu |first=Catalin |date=2019-11-11 |title=Study of over 11,000 online stores finds 'dark patterns' on 1,254 sites |url=https://www.zdnet.com/article/user-interface-dark-patterns-are-becoming-common-on-online-stores/ |access-date=2025-11-08 |work=ZDNET}}</ref> while a 2022 European Commission report indicated that 97% of popular apps used by EU consumers displayed them.<ref>{{Cite web |last=Lupiáñez-Villanueva |first=Francisco |last2=Boluda |first2=Alba |last3=Bogliacino |first3=Francesco |last4=Liva |first4=Giovanni |last5=Lechardoy |first5=Lucie |last6=Ballell |first6=Teresa Rodríguez de las Heras |title=Behavioural study on unfair commercial practices in the digital environment |url=https://op.europa.eu/en/publication-detail/-/publication/606365bc-d58b-11ec-a95f-01aa75ed71a1/language-en |access-date=2025-11-08 |website=Publications Office of the EU |doi=10.2838/859030 |isbn=978-92-76-52316-1}}</ref>
+The prevalence of dark patterns is remarkably widespread, and they represent a growing concern in digital interfaces. A 2019 study examining 11,000 e-commerce websites found approximately 10% employed deceptive practices,<ref>{{Cite news |last=Cimpanu |first=Catalin |date=2019-11-11 |title=Study of over 11,000 online stores finds 'dark patterns' on 1,254 sites |url=https://www.zdnet.com/article/user-interface-dark-patterns-are-becoming-common-on-online-stores/ |access-date=2025-11-08 |work=ZDNET |url-status=live |archive-url=http://web.archive.org/web/20251114035001/https://www.zdnet.com/article/user-interface-dark-patterns-are-becoming-common-on-online-stores/ |archive-date=14 Nov 2025}}</ref> while a 2022 European Commission report indicated that 97% of popular apps used by EU consumers displayed them.<ref>{{Cite web |last=Lupiáñez-Villanueva |first=Francisco |last2=Boluda |first2=Alba |last3=Bogliacino |first3=Francesco |last4=Liva |first4=Giovanni |last5=Lechardoy |first5=Lucie |last6=Ballell |first6=Teresa Rodríguez de las Heras |title=Behavioural study on unfair commercial practices in the digital environment |url=https://op.europa.eu/en/publication-detail/-/publication/606365bc-d58b-11ec-a95f-01aa75ed71a1/language-en |access-date=2025-11-08 |website=Publications Office of the EU |doi=10.2838/859030 |isbn=978-92-76-52316-1 |url-status=live |archive-url=http://web.archive.org/web/20260118190152/https://op.europa.eu/en/publication-detail/-/publication/606365bc-d58b-11ec-a95f-01aa75ed71a1/language-en |archive-date=18 Jan 2026}}</ref>
 ==Definition and terminology==
@@ Line 16: / Line 16: @@
 ===Obstruction patterns===
-These designs make desired actions (like rejecting tracking) significantly more difficult than accepting alternatives. A classic example is the ''Roach Motel'' pattern, where signing up for a service is straightforward but cancellation is excessively difficult. The FTC highlighted this pattern in their case against ABCmouse, where cancellation was made "extremely difficult" despite promising "Easy Cancellation".<ref>{{Cite web |author=Keller and Heckman LLP |date=2020-09-28 |title=FTC Targets Negative Option Schemes in Two Multimillion Dollar Settlements |url=https://www.lexology.com/library/detail.aspx?g=a2def591-a71f-477d-8f39-55f9b40ec125 |access-date=2025-11-08 |website=Lexology}}</ref>
+These designs make desired actions (like rejecting tracking) significantly more difficult than accepting alternatives. A classic example is the ''Roach Motel'' pattern, where signing up for a service is straightforward but cancellation is excessively difficult. The FTC highlighted this pattern in their case against ABCmouse, where cancellation was made "extremely difficult" despite promising "Easy Cancellation".<ref>{{Cite web |author=Keller and Heckman LLP |date=2020-09-28 |title=FTC Targets Negative Option Schemes in Two Multimillion Dollar Settlements |url=https://www.lexology.com/library/detail.aspx?g=a2def591-a71f-477d-8f39-55f9b40ec125 |access-date=2025-11-08 |website=Lexology |url-status=live |archive-url=http://web.archive.org/web/20251114165251/https://www.lexology.com/library/detail.aspx?g=a2def591-a71f-477d-8f39-55f9b40ec125 |archive-date=14 Nov 2025}}</ref>
 ===Interface interference===
@@ Line 32: / Line 32: @@
 ==Mind tricks and business incentives==
 ===Cognitive biases exploitation===
-Dark patterns trick users by taking advantage of unconscious thoughts. For example, in cookie banners the "Accept All" option is the first option listed and uses a green background. People tend to choose the first option before considering others. Green is associated with good in design. In cookie banners, there is also a "Manage my choices" option that typically involves opting out of each data collection category or website one at a time. It is easier for users to accept all cookies than to decline them, due to using dark patterns.<ref>{{Cite web |last=Stroink-Skillrud |first=Donata |date=2023-02-02 |title=Your Cookie Conset Banner is (Probably) Not Compliant |url=https://mainwp.com/cookie-consent-banner-probably-not-compliant/ |access-date=2025-11-08 |website=MainWP Blog}}</ref><ref name=":2">{{Cite web |last=Keyser |first=Robert |date=2023-10-05 |title=Cookie Consent Dark Patterns: How to Identify and Fix Them |url=https://www.ethyca.com/news/all-about-dark-patterns |access-date=2025-08-11 |website=Ethyca}}</ref>
+Dark patterns trick users by taking advantage of unconscious thoughts. For example, in cookie banners the "Accept All" option is the first option listed and uses a green background. People tend to choose the first option before considering others. Green is associated with good in design. In cookie banners, there is also a "Manage my choices" option that typically involves opting out of each data collection category or website one at a time. It is easier for users to accept all cookies than to decline them, due to using dark patterns.<ref>{{Cite web |last=Stroink-Skillrud |first=Donata |date=2023-02-02 |title=Your Cookie Conset Banner is (Probably) Not Compliant |url=https://mainwp.com/cookie-consent-banner-probably-not-compliant/ |access-date=2025-11-08 |website=MainWP Blog |url-status=live |archive-url=https://web.archive.org/web/20260216033732/https://mainwp.com/cookie-consent-banner-probably-not-compliant/ |archive-date=16 Feb 2026}}</ref><ref name=":2">{{Cite web |last=Keyser |first=Robert |date=2023-10-05 |title=Cookie Consent Dark Patterns: How to Identify and Fix Them |url=https://www.ethyca.com/news/all-about-dark-patterns |access-date=2025-08-11 |website=Ethyca |url-status=live |archive-url=http://web.archive.org/web/20251212062415/https://www.ethyca.com/news/all-about-dark-patterns |archive-date=12 Dec 2025}}</ref>
 ===Incentives and short-term gains===
@@ Line 43: / Line 43: @@
 ==Legal and regulatory landscape==
 ===United States framework===
-In the United States, regulation occurs primarily through existing consumer protection statutes . The FTC Act empowers the Federal Trade Commission to take action against "unfair or deceptive acts or practices in or affecting commerce".<ref name=":9">{{cite web |title=FTC Act |url=https://www.ftc.gov/legal-library/browse/statutes/federal-trade-commission-act |publisher=Federal Trade Commission}}</ref>
+In the United States, regulation occurs primarily through existing consumer protection statutes . The FTC Act empowers the Federal Trade Commission to take action against "unfair or deceptive acts or practices in or affecting commerce".<ref name=":9">{{cite web |title=FTC Act |url=https://www.ftc.gov/legal-library/browse/statutes/federal-trade-commission-act |publisher=Federal Trade Commission |url-status=live |archive-url=http://web.archive.org/web/20260127043048/https://www.ftc.gov/legal-library/browse/statutes/federal-trade-commission-act |archive-date=27 Jan 2026}}</ref>
 In October 2024, the FTC amended its Negative Option Rule to include specific requirements for cancellation mechanisms, implementing a "Click-to-Cancel" provision.<ref name=":10">{{cite web |title=FTC Strengthens Negative Option Rule |url=https://www.ftc.gov/news-events/news/press-releases/2024/10/ftc-strengthens-rule-protect-consumers-deceptive-subscription-practices |publisher=Federal Trade Commission |date=October 11, 2024}}</ref>
 ===European Union's approach===
-The European approach combines general consumer protection laws with data privacy-specific regulations. While the [[General Data Protection Regulation]] (GDPR) doesn't explicitly mention dark patterns, its requirements for valid consent effectively prohibit many deceptive designs.<ref name=":11">{{cite web |title=Guidelines on Dark Patterns in Social Media Platform Interfaces |url=https://edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en |publisher=European Data Protection Board |date=2022}}</ref>
+The European approach combines general consumer protection laws with data privacy-specific regulations. While the [[General Data Protection Regulation]] (GDPR) doesn't explicitly mention dark patterns, its requirements for valid consent effectively prohibit many deceptive designs.<ref name=":11">{{cite web |title=Guidelines on Dark Patterns in Social Media Platform Interfaces |url=https://edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en |publisher=European Data Protection Board |date=2022 |url-status=live |archive-url=http://web.archive.org/web/20251217115035/https://www.edpb.europa.eu/our-work-tools/documents/public-consultations/2022/guidelines-32022-dark-patterns-social-media_en |archive-date=17 Dec 2025}}</ref>
-The [[Digital Services Act]] (DSA) and [[Digital Markets Act]] (DMA) further address dark patterns by prohibiting practices that "deceive or manipulate" users.<ref name=":12">{{cite web |title=Digital Services Act |url=https://digital-strategy.ec.europa.eu/en/policies/digital-services-act |publisher=European Commission}}</ref>
+The [[Digital Services Act]] (DSA) and [[Digital Markets Act]] (DMA) further address dark patterns by prohibiting practices that "deceive or manipulate" users.<ref name=":12">{{cite web |title=Digital Services Act |url=https://digital-strategy.ec.europa.eu/en/policies/digital-services-act |publisher=European Commission |url-status=live |archive-url=https://web.archive.org/web/20260216033823/https://digital-strategy.ec.europa.eu/en/policies/digital-services-act |archive-date=16 Feb 2026}}</ref>
 ===Enforcement cases and penalties===
@@ Line 56: / Line 56: @@
 *Epic Games paid $245 million to settle charges related to deceptive patterns in Fortnite.<ref name=":13">{{cite web |title=Epic Games to Pay $245 Million |url=https://www.ftc.gov/news-events/news/press-releases/2022/12/epic-games-pay-245-million-ftc-refund-consumers-accused-tricking-users-making-unauthorized-charges |publisher=Federal Trade Commission |date=December 19, 2022}}</ref>
 *Noom paid $62 million to settle charges regarding deceptive subscription practices.<ref name=":14">{{cite web |title=Noom to Pay $62 Million |url=https://www.ftc.gov/news-events/news/press-releases/2024/03/noom-pay-62-million-settle-ftc-charges-it-misled-consumers-about-its-diet-programs-use-consumer-data |publisher=Federal Trade Commission |date=March 7, 2024}}</ref>
-*TikTok received multimillion-euro fines for failing to protect children's data through manipulative consent practices.<ref>{{Cite web |date=2023-09-15 |title=Irish Data Protection Commission announces €345 million fine of TikTok |url=https://www.dataprotection.ie/en/news-media/press-releases/DPC-announces-345-million-euro-fine-of-TikTok |access-date=2025-11-08 |website=Data Protection Commision}}</ref>
+*TikTok received multimillion-euro fines for failing to protect children's data through manipulative consent practices.<ref>{{Cite web |date=2023-09-15 |title=Irish Data Protection Commission announces €345 million fine of TikTok |url=https://www.dataprotection.ie/en/news-media/press-releases/DPC-announces-345-million-euro-fine-of-TikTok |access-date=2025-11-08 |website=Data Protection Commision |url-status=live |archive-url=http://web.archive.org/web/20260201165638/https://www.dataprotection.ie/en/news-media/press-releases/DPC-announces-345-million-euro-fine-of-TikTok |archive-date=1 Feb 2026}}</ref>
 ==Impact on consumers and businesses==
@@ Line 69: / Line 69: @@
 ==Detection, avoidance and mitigation==
 ===Technical detection and tools===
-Efforts to automatically detect dark patterns are evolving but face significant challenges. A comprehensive study found that existing tools could only identify 31 of 68 identified dark pattern types, a coverage rate of just 45.5%.<ref name=":3">{{Cite web |last=Li |first=Meng |last2=Wang |first2=Xiang |last3=Nei |first3=Liming |last4=Li |first4=Chenglin |last5=Liu |first5=Yang |last6=Zhao |first6=Yangyang |last7=Xue |first7=Lei |last8=Kabir Sulaiman |first8=Said |date=2024-12-12 |title=[2412.09147] A Comprehensive Study on Dark Patterns |url=https://arxiv.org/abs/2412.09147 |access-date=2025-11-08 |website=arXiv |doi=10.48550/arXiv.2412.09147}}</ref> The study proposed a Dark Pattern Analysis Framework (DPAF) to address existing gaps.
+Efforts to automatically detect dark patterns are evolving but face significant challenges. A comprehensive study found that existing tools could only identify 31 of 68 identified dark pattern types, a coverage rate of just 45.5%.<ref name=":3">{{Cite web |last=Li |first=Meng |last2=Wang |first2=Xiang |last3=Nei |first3=Liming |last4=Li |first4=Chenglin |last5=Liu |first5=Yang |last6=Zhao |first6=Yangyang |last7=Xue |first7=Lei |last8=Kabir Sulaiman |first8=Said |date=2024-12-12 |title=[2412.09147] A Comprehensive Study on Dark Patterns |url=https://arxiv.org/abs/2412.09147 |access-date=2025-11-08 |website=arXiv |doi=10.48550/arXiv.2412.09147 |url-status=live |archive-url=http://web.archive.org/web/20251109221611/https://www.arxiv.org/abs/2412.09147 |archive-date=9 Nov 2025}}</ref> The study proposed a Dark Pattern Analysis Framework (DPAF) to address existing gaps.
 ===Ethical design alternatives===