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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 DraftKings’ response are not provided in the source material.
The Electronic Frontier Foundation says DraftKings uses a machine-learning model trained on customers’ betting records to identify gamblers it expects to lose and send them promotions encouraging them to return to the betting platform. The EFF’s account, citing reporting by The New York Times, raises questions about how a major online sportsbook uses customer data to market gambling, including to people who may be experiencing gambling-related harm.
According to the EFF’s description of the Times report, DraftKings analyzes its customers’ betting histories to find people likely to place losing bets. The company then sends those customers targeted advertising intended to bring them back to the site. The EFF says the model uses betting records DraftKings collects directly from users, known as first-party data, rather than additional information purchased from outside data brokers.
The EFF argues that people who repeatedly gamble despite harm to their finances, relationships or well-being may be among those identified and reached by the promotions. That characterization is the advocacy group’s assessment; the source material does not provide figures for how many customers the model identifies, how the company defines a likely losing gambler, or how many people receiving promotions meet a definition of problem gambling.
The EFF also says DraftKings has a financial incentive to keep customers who lose money betting active on its platform. It frames the practice as behavioral advertising: using information about people’s activity to tailor ads. DraftKings’ account of the model and its marketing practices is not included in the supplied material.
Betting Data Shapes Customer Promotions
The report highlights how betting records can serve both as a record of customer activity and as input for decisions about whom to encourage to gamble again. If the EFF’s description is accurate, the model links predictions about betting outcomes to personalized marketing, potentially reaching people whose gambling is causing them harm. The source does not establish how often that occurs or measure the impact of the promotions.
The case also illustrates a limitation in focusing policy only on the sale or sharing of data by outside brokers. The EFF says DraftKings appears to use information it collects directly from customers. Rules aimed solely at third-party data transfers would not necessarily cover a company’s use of its own customer records to personalize promotions.
The EFF calls for a ban on behavioral advertising, arguing that personalized marketing creates incentives to gather extensive data. That is the organization’s policy position, rather than a description of an adopted law or an official finding about DraftKings.
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The EFF’s Case Against Behavioral Ads
The EFF describes behavioral advertising as personalizing advertisements based on data collected about individuals. In its view, machine-learning systems can process large datasets quickly and make targeting more effective, while their complexity can make it difficult to know in advance which information drives a model’s decisions. The source material does not detail DraftKings’ model architecture, training period or safeguards.
The organization places the sportsbook example within broader concerns about the ad-tech industry. It says data gathered for advertising can circulate to other parties, including insurers, banks and government agencies. The EFF points to an Immigration and Customs Enforcement request for information seeking to understand how commercial big-data and ad-tech providers could support investigations. The material does not say DraftKings customer data was shared with those agencies.
Because the EFF says DraftKings is relying on first-party records for the targeting it describes, the example supports its argument that limits on data brokers alone would not address every use of personal information for targeted advertising.
“DraftKings is using AI to target customers who are most likely to place losing bets and respond to gambling promotions.”
— Electronic Frontier Foundation
Model Reach And Safeguards Remain Unknown
The available material does not identify how many DraftKings customers are scored or promoted to, what data points the model uses, or how the company distinguishes likely losing bets from other betting behavior. It also does not describe whether customers can opt out of this targeting or what protections apply to people flagged as being at risk.
The EFF says people experiencing problem gambling are highly likely to be targeted, but the supplied account gives no supporting rate or independent measurement of that likelihood. DraftKings’ response, the model’s results and any regulatory review are also not included. The report therefore describes an alleged marketing practice and the EFF’s concerns, while leaving its scope and effects unquantified.
Responses And Policy Scrutiny
Further clarity would depend on information from DraftKings about how it uses betting records, what promotions the model triggers and what safeguards customers can access. The source material does not identify a company statement, regulator action or scheduled policy decision. The EFF is urging lawmakers to restrict behavioral advertising; whether that proposal advances remains uncertain.
Customers concerned about tracking can consult the EFF’s Surveillance Self-Defense resources and its guidance on privacy settings for mobile apps and websites. Those materials offer general data-protection steps, but the source does not say they prevent DraftKings from using its own betting records for promotions.
Key Questions
What does the EFF say DraftKings is doing with AI?
The EFF says DraftKings trains a machine-learning model on customer betting records to identify people it expects to lose and sends them promotions to encourage further betting. Its account cites reporting by The New York Times.
Does the report say DraftKings buys outside data for this model?
No. The EFF says DraftKings appears to use first-party data collected directly from its customers for the targeting described. The supplied material does not give independent confirmation from the company.
Does the source establish how many people are targeted?
No. It provides no count of customers identified by the model, recipients of promotions or people with problem gambling who are reached.
Has DraftKings responded to the allegations?
No DraftKings response is included in the source material. The model’s safeguards, targeting rules and measured effects are also not described there.
What policy change does the EFF support?
The EFF argues for banning online behavioral advertising. It says limits focused only on third-party data sales would not cover companies’ use of information they collect directly from their own customers.
Source: hn
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