Dark patterns are digital practices typically found in online user interfaces that lead consumers into making decisions that are not in their best interests. These practices exploit biases to extract more money, personal data, or attention. They are embedded in many online business models and common in e-commerce websites, apps, and cookie consent notices. Common tactics include preselecting choices by default, creating false urgency, generating misleading social proof, forcing personal information disclosure, and making it difficult to cancel services.

Consumers are frequently affected by dark patterns that lead to negative outcomes, including financial loss, privacy breaches, and psychological harm. These strategies also erode trust and competition in the digital marketplace, with certain groups such as children and less educated individuals being disproportionately impacted. Studies suggest that these tactics are most effective when used on mobile devices and subtle and difficult to detect. Advancements in machine learning may further enable the targeting of these tactics at individual consumers.

Addressing dark patterns requires more than market forces alone. Consumer and data protection authorities in various jurisdictions are taking action to combat them. However, enforcement faces challenges due to limited evidence or legal gaps. Simply providing more information to consumers isn't enough to protect them. Therefore, new measures are being proposed or put into effect to ban specific dark patterns, empower regulators, and promote consumer-friendly practices.

Effectively addressing dark patterns demands a mix of robust regulatory and enforcement measures, technical tools, and consumer awareness campaigns. However, more evidence is needed to inform policy and enforcement strategies. To address this gap, the OECD is spearheading new empirical research on dark patterns based on consumer surveys and behavioural experiments across 20 countries.