Dark pattern

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A dark pattern is a manipulative design practice that tricks or influences 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.

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, while a 2022 European Commission report indicated that 97% of popular apps used by EU consumers displayed them.

Definition and terminology

The term dark patterns was originally defined by Harry Brignull as "design tricks that manipulate users into taking actions they didn't intend to". The Federal Trade Commission (FTC) describes them as "design practices that trick or manipulate users into making choices they would not otherwise have made and that may cause harm".

There is ongoing discussion regarding the most appropriate terminology. Alternative labels include deceptive design, manipulative UX, coercive design, or anti-patterns. Some advocates argue for terms like deceptive patterns to more accurately describe the intentional nature of these designs and avoid potential racial connotations. Brignull himself has transitioned to using deceptive.design.

What distinguishes dark patterns from merely persuasive design is their exploitative nature – they are not about creating value for users but about benefiting the service provider through manipulation and deception.

Common types and examples

Research has identified numerous specific dark patterns, with one comprehensive study proposing a taxonomy comprising 68 distinct types. These manifest across various industries and digital contexts.

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".

Interface interference

This category includes designs that manipulate interface elements to steer user behavior. Misdirection focuses user attention on one element to obscure another critical detail. Disguised ads blend advertisements with genuine interface elements, like fake "Download" buttons on software websites.

Forced action

These patterns require users to complete unnecessary actions to access desired functionality. Forced registration demands that users create an account to complete a task. Forced continuity involves automatically transitioning users from free trials to paid subscriptions without adequate notification. The FTC alleged that Adobe violated regulations by "tricking customers into enrolling in subscription plans without proper disclosure".

Sneaking and information hiding

These practices involve concealing or obscuring material information from users, such as

• Hidden costs reveal unexpected fees only at checkout, a practice employed by ticketing platforms
• Drip pricing advertises only part of a product's total price initially and then imposes other mandatory charges later
• Checking a box by default that installs potentially-unwanted software, such as an "anti-virus" that's actually spyware or a crypto-miner

Social proof and urgency

These patterns exploit social influence and time pressure to manipulate decisions. False activity messages misrepresent site activity or product popularity. False scarcity creates pressure to buy immediately by claiming limited inventory. Baseless countdown timers display fake countdown clocks that reset when expired.

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.

Incentives and short-term gains

Editor note: This section is overly technical language and needs to be simplified, as well as include citations. It's also clearly made by AI/LLM.

The persistence of dark patterns is driven by their effectiveness in achieving short-term business objectives like increased conversion rates. Additionally, the competitive landscape fosters copycat behavior, as companies mimic their rivals' strategies.

Research suggests these short-term gains often come with long-term consequences. Studies indicate that "once users feel manipulated, they don't just avoid your settings—they avoid your brand". The erosion of trust can have significant business implications.

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".

In October 2024, the FTC amended its Negative Option Rule to include specific requirements for cancellation mechanisms, implementing a "Click-to-Cancel" provision. The FTC later voted on 9 May 2025 to extend the original 14 May 2025 compliance deadline by sixty days.

On 8 July 2025, the Eighth Circuit Court of Appeals vacated the entire 2024 change to the Negative Option Rule on procedural grounds in Custom Communications, Inc. v. Federal Trade Commission. Despite the legal setback, the FTC carried out findings against Match.com, Chegg Inc., Cleo AI and Amazon based on the Restore Online Shoppers' Confidence Act (ROSCA) and Section 5 of the FTC Act.

On 30 January 2026, the FTC indicated renewed interest in updating the Negative Option Rule by submitting a draft Advance Notice of Proposed Rulemaking (ANPRM) to the Office of Management and Budget (OMB) for review. It was opened to public comment on 11 Mar 2026.

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.

The Digital Services Act (DSA) and Digital Markets Act (DMA) further address dark patterns by prohibiting practices that "deceive or manipulate" users.

Enforcement cases and penalties

Recent years have seen significant enforcement actions:

• Epic Games paid $245 million to settle charges related to deceptive patterns in Fortnite.
• Noom paid $62 million to settle charges regarding deceptive subscription practices.
• TikTok received a €345 million fine for failing to protect children's data through manipulative consent practices.

Impact on consumers and businesses

Consumer harms

A dark pattern is harmful to consumers in many ways, often leading to financial loss, violations of privacy, and emotional distress.

Dark patterns could manipulate consumers financially by faking urgency, importance, scarcity, and sales to trick them into making purchases they might not have made if they were able to make a properly informed decision.

They could also be used violate the consumers privacy by hiding information on what data a service collects and how that data is used, and hiding or excluding options to stop data collection or delete already collected data.

The above examples of how consumers may be affected are often combined with or directly involve dark patterns that cause emotional distress, often attempting to frustrate the consumer enough to accept what patterns are being used against them, and stop looking for any in-site settings or other methods to bypass the patterns.

The most vulnerable consumers are those who are unfamiliar with computers and the internet, and those with mental or physical disabilities that impair them from either recognizing dark patterns or avoiding them if possible.

Impact on businesses

Dark patterns are often effective enough to be used by a wide range of businesses regardless of how successful they are. Even when consumers discover that a service they use contains dark patterns, they're highly unlikely to stop using the service or inform other users which in turn makes it highly unlikely a business will stop using dark patterns. Despite consumer backlash being unlikely to lead to any change, many dark patterns violate consumer protection laws and could lead to heavy lawsuits against businesses which are much more effective.

Detection, avoidance and mitigation

Editor note: This entire section reads as LLM.

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%. The study proposed a Dark Pattern Analysis Framework (DPAF) to address existing gaps.

Ethical design alternatives

Companies can implement ethical alternatives that respect user autonomy. They should provide a balanced choice architecture where users can decline as easily as they accept represents an ethical approach for obstruction patterns. Designers should implement neutral default settings that don't assume consent.

Transparency and clear communication are essential. Companies should provide honest explanations of data practices and costs in clear, understandable language.

Consumer protection and advocacy

Consumer education plays a crucial role. Initiatives like the Dark Patterns Tip Line allow users to report deceptive designs they encounter. Advocacy organizations provide resources to help identify and avoid dark patterns.

Further reading

• Artificial intelligence

Gallery

Examples of dark patterns, with notes.

Carly

• 
  An example of manipulating the user by minimizing the noticeability of the "More" option while emphasizing only the "Accept" button.
• 
  Diving deeper shows Marketing enabled by default and using a color to match the font text. The "Deny" option is dark text and uses a light-gray color border that is both harder to see and generally associated with denial of action.
• 
  Mixpanel is labeled as "essential", but hidden within the collapsed section is an explanation that it's a tracker. MyCarly may genuinely consider it necessary, but a tracker is still a tracker. Google Tag Manager is also enabled by default, with the same issue as the previous image.

The Economist

• 
  The message that appears on user's visit to the website. Cookie management is located closely above the bright Continue button.
• 
  "Do not sell or share" is enabled by default, but comes with a disclaimer. (See file page for further notes.)