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The Electronic Frontier Foundation, citing a New York Times report, says DraftKings uses customers’ betting records to identify people likely to make losing bets and sends them targeted promotions. The EFF argues the practice could reach people experiencing problem gambling, but the model’s operation and the scale of its use have not been detailed in the supplied reporting.
The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to identify people likely to make losing bets and send them targeted promotions. The report, which attributes the description of the system to The New York Times, raises questions about whether betting data is being used to bring vulnerable customers back to gambling.
According to the EFF’s account of The New York Times report, DraftKings analyzes customers’ betting histories to find gamblers it expects to lose. The company then sends those customers personalized advertising intended to encourage them to return to the platform. The supplied material does not describe the model’s technical design or quantify how many customers receive these promotions.
The EFF says DraftKings appears to rely on first-party data—information collected directly from its users—to train and operate the model. It says the company does not appear to be buying additional third-party data for this purpose. That distinction matters because rules focused only on the sale or sharing of data between companies may not prevent targeting based on information a business gathers from its own customers.
The EFF characterizes the practice as a form of online behavioral advertising, in which personal data is used to tailor ads. It argues that people who repeatedly gamble despite harm to their finances, relationships or well-being may be among those the model reaches. That is the advocacy group’s assessment; the supplied material does not establish how DraftKings defines or identifies problem gambling.
Betting Data Can Drive Promotions
The report highlights a potential conflict between customer protection and a betting company’s commercial incentives. If a model identifies customers expected to lose, promotions aimed at bringing them back could expose people already experiencing gambling-related harm to further inducements. The EFF says this risks capitalizing on vulnerability rather than reducing it.
The case also illustrates a limit of data policies that focus solely on third-party brokers. If DraftKings can build targeting profiles from betting activity collected through its own service, restrictions on purchasing or selling outside data may leave that use untouched. The EFF says broader limits on behavioral advertising are needed. That is its policy position, not a confirmed description of current law or a finding by regulators.
More broadly, the EFF argues that machine learning can make behavioral targeting more powerful by processing large data sets quickly and prompting companies to gather more information to train and refine models. The supplied report does not establish what additional data DraftKings collects for this model or how its use affects individual customers.
How DraftKings Uses Betting Records
Online behavioral advertising tailors promotions using information about a person’s activity. In the account cited by the EFF, DraftKings’ relevant input is customers’ betting records, and the model is used to identify customers considered likely to lose. The company then directs promotions to those customers.
The EFF has long called for a ban on behavioral advertising, saying the practice encourages extensive data collection. It also warns that information gathered for advertising can circulate beyond its original purpose, including to companies and government agencies. The supplied material mentions interest by U.S. agencies in commercial data and ad technology, but it does not say those agencies obtained DraftKings’ betting records or were involved in this targeting system.
The EFF points readers to its Surveillance Self-Defense resources and guidance on protecting data in apps and websites. These are general privacy resources; they do not establish specific steps DraftKings customers can take to stop the promotions described in the report.
“DraftKings is using its customers’ betting records to train a machine learning model to find losing gamblers.”
— Electronic Frontier Foundation
Model Reach Remains Unspecified
The supplied material does not establish how many DraftKings customers are targeted, how the model defines a likely losing gambler, or what signals beyond betting records it uses. It also does not say how often promotions are sent, whether customers can opt out of this specific targeting, or whether the company has safeguards for people experiencing gambling harm.
The account is presented by the EFF and relies on a New York Times report. DraftKings’ response is not included in the source material. No regulator’s findings or independent assessment of the model’s accuracy are provided, so claims about the system’s effects and the customers it reaches remain unverified here.
Company and Regulatory Responses
The next developments to watch are whether DraftKings publicly explains its targeting practices, data inputs and customer protections, and whether regulators examine the use of betting histories for promotional targeting. The supplied material does not identify an announced investigation, regulatory action or company response.
Readers seeking to reduce data exposure can consult the EFF’s Surveillance Self-Defense project and its privacy guidance for mobile apps and websites. Those materials offer general steps; whether they change the targeting described in this report is not specified.
Key Questions
What does the EFF say DraftKings is doing?
The EFF says DraftKings uses a machine learning model trained on customers’ betting records to identify people likely to lose and send them promotions intended to bring them back to the platform. The EFF attributes the account to 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 and does not appear to buy extra third-party data for the model. The supplied material does not include a company confirmation.
Are people with problem gambling confirmed to be targeted?
The EFF says people experiencing problem gambling may be highly likely to be targeted. The supplied material does not explain how DraftKings identifies problem gambling or confirm which individual customers receive promotions.
Has DraftKings or a regulator responded?
No company response or regulatory finding is included in the source material. The model’s reach, safeguards and effects on customers also remain unspecified.
Source: hn
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