Consumer Harm

Consumer harm refers to damage or injury suffered by end users of AI systems, ranging from financial loss and privacy violations to physical injury or emotional distress caused by AI decisions or outputs. For enterprise governance, this matters because organizations deploying AI face direct legal liability, regulatory penalties, and reputational damage when their systems cause consumer harm, particularly in high-stakes domains like lending, hiring, healthcare, and content moderation. Establishing clear accountability mechanisms and harm monitoring processes is critical to identifying problems before they scale and to demonstrating due diligence if incidents do occur.

1 item

Corporate PolicyUS2026-09-30

DraftKings AI Model Targets Chronic Losing Gamblers With Promotional Ads

DraftKings is training machine learning models on customer betting records to identify chronic losing gamblers, then serving them promotional advertising to drive re-engagement. The Electronic Frontier Foundation published an analysis naming DraftKings and framing the practice as AI-amplified consumer harm enabled entirely by first-party data. The case illustrates that existing data-minimization and consent frameworks do not prevent companies from using lawfully collected data in ways that systematically harm vulnerable customers.

DraftKings behavioral advertising consumer harm AI targeting data ethics vulnerable populations FTC enforcement model governance