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The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to identify losing gamblers and target them with promotions. The account is based on reporting by The New York Times; details about the model, its scale and its effects on customers have not been provided in the source material.
The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to find gamblers likely to lose and then target them with promotions to return to the sportsbook. The EFF attributes the account to The New York Times; the reported practice raises questions about how betting data is used to market gambling to people who may be vulnerable to harm.
According to the EFF’s account of The New York Times reporting, DraftKings analyzes customer betting records to identify people whose wagers are likely to lose. The company then directs personalized advertising and promotions at those customers, with the aim of bringing them back to place more bets. The EFF says DraftKings expects those bets to be losing ones.
The EFF argues that this approach creates a financial incentive to re-engage customers who lose money. It says people it describes as problem gamblers—those who continue gambling despite harm to their finances, relationships or well-being—could be especially likely to receive such marketing. The source material does not establish how DraftKings defines or identifies problem gambling, or how many customers the model flags.
The EFF says DraftKings appears to rely on first-party data, meaning information collected directly from its own customers, rather than additional data purchased from outside brokers. That detail matters to proposals focused only on restricting the sale or sharing of third-party data: such limits would not, by themselves, prevent a company from using its own customer records to personalize promotions.
How Targeted Offers Could Affect Gamblers
Targeting promotions at customers expected to lose could turn detailed betting histories into a tool for encouraging further gambling. The EFF says people experiencing gambling-related harm may be among those targeted, though the source account does not quantify the overlap or document specific customer outcomes.
The report also points to a broader privacy issue: behavioral advertising can operate on data a company collects directly, without buying profiles from outside brokers. If policymakers address only data sales, companies may still be able to build targeting systems from records generated through their own services. The EFF therefore calls for a ban on behavioral advertising, a policy position that goes beyond the reported facts about DraftKings.
More broadly, the EFF argues that machine learning can make advertising systems process large data sets faster and increase demand for data to train and refine models. It also warns that information gathered for ad targeting can feed a wider data economy. Those concerns provide the organization’s rationale for opposing behavioral advertising; they are not evidence that DraftKings shared these particular betting records with outside entities.
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Betting Records and Ad Targeting
Behavioral advertising uses information about people’s activity to personalize the ads they see. In this case, the EFF’s account says DraftKings uses records from customers’ betting activity to identify people for promotions on its own platform. The source does not describe which specific data points the model uses, how it predicts losses or how DraftKings assesses whether an offer is appropriate for a particular customer.
The EFF has long opposed behavioral advertising and presents the DraftKings example as an illustration of how personal data can be used to target people in ways it considers harmful. It also cites wider concerns about data gathered for ad technology being sold to insurers, banks and government agencies. The supplied material does not say that DraftKings’ betting records were sold or passed to those organizations.
“DraftKings is using its customers’ betting records to train a machine learning model to find losing gamblers.”
— Electronic Frontier Foundation, citing The New York Times
What the Report Does Not Specify
The supplied account does not include a response from DraftKings or detail the model’s design, accuracy, deployment period or reach. It is not clear how many customers receive these promotions, what criteria classify a bettor as likely to lose, or whether DraftKings tests the model for effects on people experiencing gambling-related harm. The material also does not document individual cases or quantify any resulting increase in betting.
The EFF’s characterization that the model targets “losing gamblers” is based on the Times reporting as summarized by the organization. The source material does not provide the underlying documents or independent technical evidence to assess that characterization. It also says the company appears to use first-party data; the extent of any other data use remains unspecified.
Further Details From DraftKings
The next developments to watch are whether DraftKings comments on the reported system and whether further reporting supplies details about its data inputs, targeting rules and customer safeguards. The source material does not identify a specific regulatory action, company announcement or policy timetable tied to the report.
For now, the EFF is using the case to press its call for a ban on behavioral advertising and to direct readers to its privacy resources, including Surveillance Self Defense and guidance on mobile apps and websites. Whether policymakers take up that proposal, and how any rules would apply to first-party customer data, remains open.
Key Questions
What is DraftKings reported to be doing with AI?
According to the EFF’s account of The New York Times reporting, DraftKings trains a machine learning model on customer betting records to identify gamblers likely to lose and sends those customers targeted promotions.
Does the report say how many customers are targeted?
No. The supplied source material does not state how many customers the model identifies or how many receive promotions.
What does first-party data mean in this report?
It means information DraftKings collects directly from its own customers. The EFF says the company appears to rely on that data for the targeting, rather than buying additional information from third parties.
Has DraftKings responded to the allegations?
The supplied source material contains no response from DraftKings, so its position is not included here.
What policy change does the EFF recommend?
The EFF calls for a ban on online behavioral advertising. That is the organization’s policy recommendation, not a report that such a ban has been enacted.
Source: hn
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