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The Electronic Frontier Foundation, citing a New York Times report, says DraftKings uses customer betting records to identify losing gamblers and target them with promotions. DraftKings’ explanation of the model, its safeguards and its effect on customers is not included in the source material.
The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to identify people likely to lose and send them targeted gambling promotions. Citing a New York Times report, EFF says the practice could draw vulnerable customers back to the betting platform; DraftKings’ account of the model is not included in the available source material.
According to the EFF account of the New York Times reporting, DraftKings analyzes its customers’ betting records to identify people who lose bets and may respond to promotions. The model’s results are then used to direct advertising intended to bring those customers back to the site to place more bets. The source does not describe the model’s inputs beyond betting records or explain how it defines a customer as likely to lose.
EFF characterizes the practice as online behavioral advertising: tailoring ads using information collected about users. It says DraftKings appears to use first-party data collected directly from its customers, rather than buying additional information from data brokers. That distinction matters because restrictions aimed only at third-party data sales would not, by themselves, address targeting based on a company’s own records.
EFF argues that people it describes as problem gamblers—those who repeatedly gamble despite harm to their finances, relationships or well-being—could be among those targeted. That is the organization’s assessment of potential harm; the supplied report does not quantify how many customers are targeted, establish how the model identifies problem gambling, or provide DraftKings’ response.
Promotions May Reach Vulnerable Bettors
The reported use of betting histories to target people expected to lose puts the platform’s commercial incentives at the center of the debate. EFF says customers who lose money generate revenue for DraftKings and argues that promotions can encourage them to continue betting. The source material does not provide financial figures or independently document the company’s motives, so that interpretation remains attributable to EFF.
The account also illustrates a gap in data policy: a company may build a detailed advertising profile from information customers provide or generate on its own service, without purchasing outside data. In EFF’s view, that means limits on data brokers alone would leave this form of first-party targeting possible. The group argues for a broader ban on behavioral advertising, a policy position rather than a description of current law.
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How Betting Records Feed Ad Targeting
Behavioral advertising uses information about people’s activity to personalize promotions. In this case, the data identified by EFF is customers’ betting history, which the organization says DraftKings uses to train a machine learning model. The source does not say whether other personal or device data is used.
EFF argues that machine learning can increase the scale and speed of this process, while making it harder to determine which data points drive a model’s predictions. The group also places the case within a broader concern about ad-tech data being shared with organizations such as insurers, banks and law enforcement. It cites an Immigration and Customs Enforcement request for information on commercial big-data and ad-tech providers, but the supplied material does not establish that DraftKings’ customer records were shared with government agencies.
“people who repeatedly gamble despite harm to themselves, their finances, and their relationships”
— Electronic Frontier Foundation, describing people it calls problem gamblers
Model Rules and Customer Reach Unknown
The source material does not establish when DraftKings began using the model, how many customers have received targeted promotions, how the company determines who is likely to lose, or whether customers can opt out. It also does not include DraftKings’ response or details about safeguards, such as limits on marketing to people at risk of gambling harm.
The claim that the model targets chronic or problem gamblers should be treated cautiously: EFF says those customers are likely to be targeted, but the material does not show that DraftKings labels users as problem gamblers or provide independent evidence of the model’s accuracy. The scale and consequences of the practice remain unquantified.
Company Response and Safeguards
The next details needed to assess the report include DraftKings’ explanation of its targeting practices, the model’s criteria and the safeguards applied to promotions. Information on customer reach, opt-out choices and any steps to prevent marketing to people experiencing gambling harm would help clarify the practice’s effects. The source material does not identify a regulatory action or an announced company response.
EFF points readers to its Surveillance Self-Defense project and guidance on protecting data on mobile apps and websites. Those resources address individual privacy measures; EFF’s broader recommendation is that policymakers ban behavioral advertising.
Key Questions
What does the report say DraftKings is doing?
EFF, citing New York Times reporting, says DraftKings trains a machine learning model on customers’ betting records to identify losing gamblers and send them promotions intended to bring them back to the platform.
Does the source prove DraftKings targets people identified as problem gamblers?
No. EFF says people experiencing problem gambling are likely to be targeted, but the supplied material does not establish that DraftKings labels customers this way or detail the model’s criteria.
What is first-party data in this report?
It means data DraftKings collects directly from its users. EFF says this appears to be the data used for targeting, rather than information purchased from outside data brokers.
Has DraftKings responded or announced changes?
No response or change is included in the source material. The company’s model rules, safeguards and customer opt-out options are also not described.
Source: hn
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