According to an article published by the Electronic Frontier Foundation (EFF), DraftKings is using artificial intelligence to target customers who are most likely to place losing bets and to respond to gambling promotions. The piece describes this practice as a form of online behavioral advertising, in which companies personalize the ads they show based on data collected about individuals. The article notes that the more data a company possesses, the more personalized the advertising can become. It further states that DraftKings trains a machine‑learning model on its customers’ betting records to find losing gamblers. Once identified, the company sends these users targeted advertising intended to lure them back to the site to place additional bets—bets that DraftKings anticipates will be losing ones. The source explains that DraftKings has a business incentive to keep losing gamblers returning, because those users are the ones that generate revenue for the company. Moreover, the article points out that individuals classified as “problem gamblers”—people who continue gambling despite harm to themselves, their finances, and their relationships—are highly likely to be targeted by this model. By re‑engaging such individuals through promotions aimed at keeping them on the platform, DraftKings is characterized as capitalizing on their vulnerability for profit rather than attempting to mitigate risk. The EFF piece argues that the use of AI intensifies the harms of online behavioral advertising. It explains that AI enables companies to process enormous data sets quickly, which drives further data collection because the inner workings of the models are opaque—a “black box” that makes it difficult for developers to know which data points are most useful. This dynamic, the article says, leads to continual gathering of more information to train and refine AI systems. Additionally, the source highlights that data collected for ad targeting is later sold to other sectors, including insurance companies, banks, and state and federal law‑enforcement agencies such as Customs and Border Protection (CBP). It also notes that Immigration and Customs Enforcement (ICE) has expressed interest in this data, having issued a Request for Information earlier in the year to explore how commercial Big Data and ad‑tech providers might support investigative activities. The article clarifies that DraftKings appears to rely solely on “first‑party data,” meaning it uses only information gathered directly from its own users and does not purchase additional data from third parties to fuel its machine‑learning model. This observation is used to argue that policies limited to restricting third‑party data sharing would not be sufficient to stop such predatory advertising; instead, a broader prohibition on behavioral ads is advocated. Finally, the EFF piece mentions that the organization offers resources such as its Surveillance Self‑Defense project and tips for protecting personal data on mobile apps and websites. It concludes that DraftKings’ use of AI to target losing gamblers exemplifies how ad‑tech evolves and how companies find new ways to employ personal data against users, reinforcing EFF’s stance that all behavioral advertising should be banned because removing the ability to send personalized ads would diminish the incentive to collect the underlying data.
