TL;DR
Get smart everyday buys delivered free — and shop member deals
- Fast, free delivery on millions of items
- Access to Prime Big Deal Days deals on October 6–7
- Prime Video, Amazon Music and more included
The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to identify people likely to place losing bets and target them with promotions. The account, which EFF attributes to The New York Times, raises questions about how the sportsbook uses customer data and whether its targeting reaches people experiencing gambling-related harm.
The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to identify people likely to place losing bets, then sends those customers promotions intended to bring them back to the sportsbook. EFF attributes the account to The New York Times; the reported practice raises concerns about personalized marketing reaching people who may be experiencing gambling-related harm.
According to EFF’s account of The New York Times report, DraftKings analyzes its customers’ betting histories to find gamblers it believes are likely to lose. The company then directs targeted promotions at those customers, with the aim of encouraging further betting. The source material does not provide the model’s technical design, the size of the audience identified or examples of specific promotions.
EFF says DraftKings appears to rely on first-party data—information collected directly from its own users—rather than purchasing additional data from outside brokers to train the model. That distinction matters to proposals focused on limiting third-party data sales: such restrictions alone would not prevent a company from using its own customer records for behavioral targeting.
EFF argues that the business incentives are troubling because customers who lose money can generate revenue for a sportsbook, and people described as problem gamblers may be particularly susceptible to efforts to draw them back. That is EFF’s characterization of the risk; the supplied material does not establish how DraftKings defines a likely losing gambler or whether its model specifically identifies people with a gambling disorder.
Promotions Reach Vulnerable Bettors
The report spotlights a conflict between personalized marketing and customer welfare. A system that identifies customers based on patterns associated with losses and then encourages more betting could expose people already facing financial or personal harm to additional inducements. The source describes the targeting method, but does not quantify its effects on customers or establish that any individual suffered further losses because of a promotion.
The data source also broadens the policy debate. Rules aimed only at data brokers may leave companies able to profile their own customers using records collected through their services. EFF says the case supports its call to ban behavioral advertising, a policy position rather than an existing finding about DraftKings’ legal obligations.
Top picks for "draftking behaviorally target"
As an affiliate, we earn on qualifying purchases.
How Betting Records Feed Ad Targeting
Behavioral advertising uses information about people’s activity to personalize the advertisements or promotions they see. In this account, the relevant activity is DraftKings customers’ betting history, which EFF says is used to train a machine learning model. The report therefore concerns a company using its own service data to decide which customers should receive marketing.
EFF argues that AI can increase the scale and speed of data analysis, while the complexity of machine learning can make it difficult to determine which data points drive a model’s decisions. The organization also warns that information gathered for advertising can circulate more widely through the data economy. Its broader examples include data access sought by insurers, banks and government agencies; those examples do not show that DraftKings shared this betting data with those parties.
““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 Effects Remain Unknown
The supplied account does not include a response from DraftKings or independent technical documentation about the model. It is unclear how many customers are targeted, what signals the system uses beyond betting records, how often it is updated, or how promotions are selected and delivered. The source also does not say whether customers can opt out of this type of targeting.
It is also unclear how closely the model’s category of likely losing gamblers overlaps with people who meet clinical or other definitions of problem gambling. EFF says such people are highly likely to be targeted, but the provided material does not give a measured rate or explain how that conclusion was reached. The account does not establish the model’s accuracy or quantify any resulting changes in betting behavior.
Questions for DraftKings and Regulators
Further details from DraftKings or additional reporting could clarify how the model works, what safeguards apply and whether customers can limit the use of their betting histories for promotions. Regulators and policymakers may also examine whether existing consumer protection and privacy rules cover first-party behavioral targeting by gambling platforms. EFF is urging a broader ban on behavioral advertising, but the source material identifies no specific legislative action or regulatory decision prompted by this report.
Key Questions
What does the report say DraftKings is doing?
EFF says DraftKings trains a machine learning model on customer betting records to identify people likely to place losing bets, then directs promotions at them to encourage more betting. EFF cites The New York Times for the account.
Does the report prove the model targets people with gambling disorders?
No. EFF says people it describes as problem gamblers are highly likely to be targeted. The supplied account does not explain how that likelihood was measured or show that the model identifies a clinical diagnosis.
What data does DraftKings reportedly use?
EFF says the targeting appears to use first-party data collected directly from DraftKings users. The account does not describe the full set of data points used by the model.
Has DraftKings responded to the claims?
No company response is included in the supplied source material. Details about the model’s reach, safeguards and effects on customers remain unclear.
What policy change does EFF support?
EFF argues that policymakers should ban online behavioral advertising. That is the organization’s recommendation; the supplied material does not report a new ban or a specific policy decision.
Source: hn
Fall Picks
fall essentials
As an affiliate, we earn on qualifying purchases.
