Privacy Class Actions and AI-Based Tools: Impact of Algorithmic Disgorgement and FTC Enforcement

Description

Privacy class action lawsuits often allege that companies used algorithms, both true AI or quasi-AI technologies, to secretly collect and use consumers' private data in violation of state or federal law causing consumers harm. Although in recent class lawsuits the type of data being collected has often been geolocation data, in prior suits plaintiffs have complained about facial recognition or allegedly biased decision-making software. How these matters end is unpredictable for both sides because the law in this area is evolving, incomplete, and inconsistent.

Also, the FTC could step into the fray. The FTC is charged with protecting the public from deceptive or unfair business practices. Something is "unfair" if it "causes or is likely to cause substantial injury to consumers which is not reasonably avoidable by consumers themselves and not outweighed by countervailing benefits … ." If the FTC considers a company's use of AI or quasi-AI technology is at odds with its privacy obligations to consumers, and therefore "unfair," then the FTC might bring an enforcement action. Resolution of that action might require the defendant to disgorge any computer data, data models, or algorithms that were developed or trained with improperly obtained data. Such a result could be financially ruinous to defendants and financially disappointing to potential class plaintiffs.

Listen as the premier panel of experts discusses algorithmic disgorgement, its role in FTC enforcement, and the impact of the FTC remedy on how to assess and proceed with class litigation alleging privacy violation claims.