Deceptive patterns trick people into doing things they didn’t mean to.
Also known as “dark patterns” — they’re features of apps, websites and AI systems that stop you doing what you want, or steer you into harmful decisions that you would not have made, had you understood at the time.
Addictive Design The user interacts with the product excessively, because its design exploits psychological vulnerabilities to foster compulsive behaviour. Comparison prevention The user struggles to compare products because features and prices are combined in a complex manner, or because essential information is hard to find. Confirmshaming The user is emotionally manipulated into doing something that they would not otherwise have done. Currency Confusion The user is misled about how much they are really spending, because real money is converted into a virtual currency that obscures the true cost. Disguised ads The user mistakenly believes they are clicking on an interface element or native content, but it's actually a disguised advertisment. Fake scarcity The user is pressured into completing an action because they are presented with a fake indication of limited supply or popularity. Fake social proof The user is misled into believing a product is more popular or credible than it really is, because they were shown fake reviews, testimonials, or activity messages. Fake urgency The user is pressured into completing an action because they are presented with a fake time limitation. Forced action The user wants to do something, but they are required to do something else undesirable in return. Hard to cancel The user finds it easy to sign up or subscribe, but when they want to cancel they find it very hard. Hidden costs The user is enticed with a low advertised price. After investing time and effort, they discover unexpected fees and charges when they reach the checkout. Hidden subscription The user is unknowingly enrolled in a recurring subscription or payment plan without clear disclosure or their explicit consent. Nagging The user tries to do something, but they are persistently interrupted by requests to do something else that may not be in their best interests. Obstruction The user is faced with barriers or hurdles, making it hard for them to complete their task or access information. Preselection The user is presented with a default option that has already been selected for them, in order to influence their decision-making. Sneaking The user is drawn into a transaction on false pretences, because pertinent information is hidden or delayed from being presented to them. Trick wording The user is misled into taking an action, due to the presentation of confusing or misleading language. Visual interference The user expects to see information presented in a clear and predictable way on the page, but it is hidden, obscured or disguised.
Amazon 30 examples Google 21 examples Microsoft 21 examples Facebook 20 examples Twitter 14 examples Adobe 13 examples HP 11 examples Instagram 9 examples Linkedin 9 examples Trump 9 examples Apple 7 examples Meta 7 examples Yahoo 7 examples New York Times 6 examples Doordash 5 examples 5 examples 5 examples Tiktok 5 examples
GDPR (EU) 70 enforcements Spanish Law on Information Society Services 22 enforcements FTC Act (US) 15 enforcements Restore Online Shoppers’ Confidence Act (US) 7 enforcements Consumer Protection Laws (UK) 5 enforcements ePrivacy (EU) 5 enforcements District of Columbia Consumer Protection Procedures Act 3 enforcements Italian Consumer Law (EU) 3 enforcements PECR (UK) 3 enforcements Electronic Fund Transfer Act (US) 2 enforcements Unfair Competition Law (US) 2 enforcements Austria Data Protection Law (EU) 1 enforcement
EU & UK Meta Platforms Ireland Limited, and Instagram Social Media Network's Investigation by DPC USA In the Matter of Epic Games, Inc EU & UK Ireland's Data Protection Commission Investigation into WhatsApp Ireland Limited USA FTC v. Prog Leasing EU & UK Deliberation of the Restricted Committee concerning Google LLC and Google Ireland Limited USA Federal Trade Commission v. Vonage Holdings Corporation USA State of Arizona, ex rel. Mark Brnovich, Attorney General v. Google, LLC EU & UK Deliberation of the Restricted Committee concerning Microsoft Ireland Operations Limited EU & UK Deliberation of the Restricted Committee concerning Facebook Ireland Limited USA Geraldine Mahood v. Noom, Inc. EU & UK NGO la Quadrature du Net (LQDN) and Noyb (Complainant) v. Google LLC USA United States of America v. MyLife.com, Inc., and Jeffrey Tinsley
Regulator or Lawmaker CCPA Acts Against Dark Patterns on Digital Platforms Consumer Group or NGO Dark Patterns in AI Chatbots: A Taxonomy to Inform Better Design Consumer Group or NGO Good Luck Opting Out: Manipulative Design Patterns in Opt-Out Processes Academic Scholar A Systematic Review of User Experiments on the Effects of Dark Patterns Academic Scholar The Dark Patterns Knowledge Stack: Exploring New Ways to Negotiate Context, Law, and Design Journalist or Media Airline seating policy takes aim at dark patterns in bookings Journalist or Media US appeals court voids much of injunction against California children’s online safety law Regulator or Lawmaker Conclusions on the 2030 Consumer Agenda Regulator or Lawmaker Commission preliminarily finds TikTok’s addictive design in breach of the Digital Services Act Academic Scholar A cautionary tale: Children, dark patterns and normative perspectives Academic Scholar Dark patterns in online gambling: A scoping review and classification of deceptive design practices Regulator or Lawmaker Protecting consumers from unfair trading practices: Decision Regulation Impact Statement