FTC Announces Workshop to Address Digital “Dark Patterns”

On April 29, 2021, the Federal Trade Commission (FTC) will host a public workshop to examine consumer protection issues related to "dark patterns"—website and app interface features designed to subvert or impair consumer autonomy, decision-making, or choices. 

In a recent statement, FTC Commissioner Rohit Chopra defined dark patterns as "design features used to deceive, steer, or manipulate users into behavior that is profitable for an online service, but often harmful to users or contrary to their intent." According to Chopra, examples of dark patterns include "misdirection, confusing language, hidden alternatives, or fake urgency to steer people toward or away from certain choices."  The FTC recently warned against employing a "roach motel" dark pattern scenario, specifically where it is easy for consumers to enter into a digital subscription program, but nearly impossible to escape (unsubscribe). The FTC's workshop, "Bringing Dark Patterns to Light," will gather representatives from the research community, consumer advocacy groups, and industry professionals to explain what dark patterns are and the potential impacts on consumers and the marketplace. Discussion topics will include:

• how dark patterns differ from analogous sales tactics used by brick-and-mortar stores;
• how they affect consumer behavior, including potential harms;
• whether some groups of consumers are unfairly targeted or could be especially vulnerable;
• applicable laws, rules, and norms; and
• whether additional rules, standards, or enforcement efforts are needed to protect consumers.

The free workshop open to the public will be held virtually and webcast on FTC.gov. See the FTC event webpage for more information about the workshop. Key Takeaways: Dark patterns are squarely on the FTC's radar, so brands should stay current on FTC actions and guidance in this area and take care to avoid practices that could be viewed as unduly confusing, misleading, or unfairly manipulative to consumers.