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The Electronic Frontier Foundation reports that DraftKings uses machine learning trained on customers’ betting records to identify gamblers likely to lose, then sends them targeted promotions to bring them back to the platform. EFF, citing New York Times reporting, argues this magnifies the harms of behavioral advertising and is renewing its call for a ban on the practice.
The Electronic Frontier Foundation (EFF) reported in September 2026 that DraftKings is using artificial intelligence to identify customers most likely to place losing bets and respond to gambling promotions, then targeting those users with advertising designed to draw them back to its platform. The digital rights group, citing reporting by the New York Times, said the practice illustrates how AI intensifies the harms of online behavioral advertising and renewed its call for the practice to be banned outright.
According to the EFF, citing the New York Times, DraftKings is using its customers’ own betting records to train a machine learning model that identifies gamblers expected to lose money. Once identified, those customers receive targeted advertising and promotions intended to bring them back to the site to place more bets — bets the model predicts will be losing ones. Losing gamblers are the customers who actually generate DraftKings’ revenue, the EFF noted, giving the company a business incentive to keep them active on the platform.
The EFF stated that people considered “problem gamblers” — those who repeatedly gamble despite harm to their finances, relationships, and wellbeing — are highly likely to be swept up by this targeting model. Rather than mitigating risk for these users, the group argued, DraftKings is capitalizing on their vulnerability for profit through re-engagement promotions.
The EFF also observed that DraftKings appears to use only “first-party data” — information collected directly from its own users — rather than purchasing additional data from third-party brokers. This detail, the group argued, shows the limits of policy solutions focused narrowly on restricting third-party data sales and sharing.
Why AI-Driven Gambling Ads Raise Stakes
The EFF’s argument centers on how AI changes the scale and character of behavioral advertising. Because machine learning models operate largely as a black box, the group said, engineers often cannot predict which data points will prove useful, which drives continuous collection of ever-larger data sets. AI also allows companies to process enormous amounts of data far faster than before, which the EFF said magnifies the harms of an already problematic advertising model.
The report also connected ad tech data flows to broader surveillance, noting that data collected for targeted advertising is sold to insurance companies, banks, and law enforcement agencies including CBP. The EFF pointed to a Request for Information published by ICE earlier in 2026 seeking to understand how commercial Big Data and ad tech providers could support investigations.
For gambling regulators and policymakers, the report lands amid ongoing debate over how sports betting operators handle customers showing signs of gambling harm, and whether self-reported responsible gambling programs are adequate when platforms profit most from their heaviest losers.
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EFF’s Longstanding Position on Ad Targeting
Online behavioral advertising — personalizing ads based on data collected about individual users — predates AI, and the EFF has long argued that all behavioral advertising should be banned, not merely regulated. The group’s position is that if companies cannot send personalized ads, they lose the incentive to collect the behavioral data that powers them.
The DraftKings example fits into a broader pattern the EFF describes of companies finding new ways to use consumer data as ad tech evolves. The group maintains resources such as its Surveillance Self Defense project with guidance on limiting data exposure in mobile apps and on websites. The report’s claims about DraftKings’ model rely on the EFF’s account of New York Times reporting; DraftKings’ own description of its practices was not included in the EFF’s published account.
“DraftKings is using its customers’ betting records to train a machine learning model to find losing gamblers. Once found, DraftKings sends these customers targeted advertising designed to lure them back to the site to place more bets.”
— Electronic Frontier Foundation
Unverified Details in the DraftKings Claims
The specifics of DraftKings’ model — how it is trained, what data points it weighs, and how customers are scored — are not independently detailed in the EFF’s report, which attributes the core findings to the New York Times. It is not clear whether DraftKings uses any safeguards that exclude users flagged as problem gamblers from promotional targeting, or whether such flags exist within the model at all.
DraftKings’ direct response to the EFF’s characterization was not included in the source material, and the company’s own account of its marketing practices remains unavailable here. The exact scale of the targeting — how many users are affected — is also unstated. The EFF’s assertion that problem gamblers are “highly likely” to be targeted is presented as the group’s assessment rather than a measured finding.
Regulatory and Advocacy Pressure Ahead
The EFF said it will continue advocating for an outright ban on behavioral advertising, arguing that restrictions limited to third-party data sales leave practices like DraftKings’ first-party targeting untouched. Readers can expect ongoing debate in state legislatures and gambling regulators over whether operators should be required to exclude at-risk customers from promotional targeting.
The report also points toward greater scrutiny of ad tech data flows to government agencies, following ICE’s 2026 Request for Information. For consumers, the EFF directs users to its Surveillance Self Defense resources for steps to limit data collection in apps and on websites. Any response from DraftKings or from gambling regulators to the report had not been made public at the time of publication.
Key Questions
What is DraftKings accused of doing?
According to the EFF, citing New York Times reporting, DraftKings trains a machine learning model on customers’ betting records to identify gamblers likely to lose money, then sends them targeted promotions to bring them back to place more bets.
Is DraftKings buying third-party data for this targeting?
No, according to the EFF. The group said DraftKings appears to rely solely on “first-party data” — information collected directly from its own users — which is why it argues that policies limited to restricting third-party data sales would not address the practice.
Has DraftKings responded to the report?
The EFF’s published account did not include a response from DraftKings, and no company statement was available in the source material. The company’s own description of its marketing practices remains unclear.
Why does the EFF want behavioral advertising banned entirely?
The EFF argues behavioral advertising incentivizes mass data collection, that AI magnifies the harm by processing larger data sets faster and less transparently, and that the resulting data feeds other industries including insurance, banking, and law enforcement.
What can individuals do about behavioral ad targeting?
The EFF points to its Surveillance Self Defense project and other guidance for reducing data exposure in mobile apps and on websites, while maintaining that individual protections are not a substitute for a ban on behavioral advertising.
Source: hn
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