DraftKings Is Using AI to Behaviorally Target Chronic Gamblers

DraftKings is using customers’ betting histories to train machine learning models that identify people most likely to place losing bets, then sends targeted promotions to lure those users back. The platform’s business model rewards repeated losses, so the algorithm specifically re-engages vulnerable or “problem” gamblers who generate profit for the company despite personal harm. By applying AI to customer behavior, DraftKings shifts from blunt mass marketing to precision outreach that exploits addiction patterns, turning detailed first‑party records into tools for sustained monetization rather than mitigation.

This practice illustrates a broader critique of online behavioral advertising: AI magnifies its harms by encouraging ever-larger data collection, using opaque models that push operators to continuously harvest more signals, and enabling faster, more granular targeting. Because DraftKings relies on first‑party data, limiting third‑party data sharing would not prevent such predation. The same data streams also feed a broader surveillance ecosystem and attract interest from insurers, banks, and law enforcement. The remedy proposed is structural: end behavioral advertising so companies lose the incentive to collect and weaponize personal data, and use privacy tools and practices to limit exposure in the meantime.