How DraftKings Uses AI and Behavioral Advertising to Target Losing Gamblers
- Online sports betting operator DraftKings is deploying artificial intelligence to train a machine learning model designed to identify customers likely to place losing bets, according to reporting detailed...
- By analyzing user history, the machine learning model pinpoints individuals who are consistently losing money on wagers.
- The integration of machine learning into online behavioral advertising accelerates traditional data collection harms.
Online sports betting operator DraftKings is deploying artificial intelligence to train a machine learning model designed to identify customers likely to place losing bets, according to reporting detailed by the Electronic Frontier Foundation. The system uses first-party user data from betting records to isolate losing gamblers and subsequently serves them targeted promotional ads to lure them back onto the platform.
DraftKings AI Model Targets Losing Bettors
By analyzing user history, the machine learning model pinpoints individuals who are consistently losing money on wagers. DraftKings has a direct business incentive to re-engage these specific users because they generate the actual revenue for the company. Unfortunately, this model frequently targets problem gamblers, who are defined as individuals who continue to wager despite experiencing harm to their personal lives, finances, and relationships. Instead of mitigating player risk or intervention, the targeted promotions capitalize on user vulnerability to drive platform retention and profit.
The Broader Dangers of AI-Powered Behavioral Advertising
The integration of machine learning into online behavioral advertising accelerates traditional data collection harms. AI systems operate as black boxes, making it difficult for engineers to predict which specific data points the model will prioritize, which encourages companies to harvest vast quantities of data continuously. AI processes these massive datasets at speeds that supercharge the scale of behavioral tracking. The surveillance apparatus built to support targeted advertising feeds commercial and governmental data brokers alike. Data collected for ad tech platforms is routinely sold or requested by banks, insurance companies, and law enforcement agencies. Immigration and Customs Enforcement previously published a Request for Information seeking details on how commercial big data and ad tech providers can directly support active investigations.
Why Current Policy Solutions Fall Short
DraftKings relies strictly on first-party data, meaning the company uses information collected directly from its own users without purchasing third-party data packages to fuel its predictive model. This operational structure demonstrates that policy solutions restricting only third-party data sharing and selling are inadequate to stop predatory ad targeting. The Electronic Frontier Foundation argues that because companies exploit internal data just as effectively, policymakers must implement a complete ban on all online behavioral advertising. Banning personalized ads would remove the primary financial incentive for companies to harvest intimate behavioral data in the first place.