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The Electronic Frontier Foundation says DraftKings uses a machine learning model trained on customers’ betting records to identify people likely to make losing bets, then sends them promotions to return. The account is based on reporting by The New York Times; the model’s criteria, scale and effects have not been publicly detailed in the supplied material.
The Electronic Frontier Foundation says DraftKings uses customer betting records to train a machine learning model that identifies gamblers likely to make losing bets and targets them with promotions to return to the platform. The EFF’s account cites reporting by The New York Times; the targeting could affect people experiencing gambling-related harm, but details about the model and its reach are not provided.
According to the EFF, DraftKings analyzes customers’ betting histories to find users it expects to place losing bets. The company then sends selected customers targeted advertising intended to bring them back to place more bets. The EFF characterizes the approach as behavioral advertising: using information about people’s activity to personalize the ads they receive.
The EFF says DraftKings appears to rely on first-party data, meaning information it collects directly from its own users, rather than additional data purchased from outside brokers. The source material does not provide a statement from DraftKings confirming the system or explaining how it works. It also does not specify how many customers receive these promotions, what data beyond betting records is used, or how the model defines a likely losing bettor.
The EFF argues that people it describes as problem gamblers—those who continue gambling despite harm to their finances, relationships or well-being—may be especially vulnerable to this kind of re-engagement. That is the organization’s assessment of who could be affected; the supplied account does not report an independent measurement of how many targeted customers meet that description or what outcomes followed the promotions.
Promotions Can Reach Vulnerable Bettors
If the EFF’s account is accurate, the practice raises questions about how betting data is used to encourage further gambling. Promotions aimed at customers expected to lose could create a commercial incentive to re-engage people whose betting may already be causing harm. The available information does not establish that every targeted customer has a gambling problem, or that a particular promotion caused financial or personal harm.
The EFF says the case also shows why rules focused only on third-party data brokers may leave a gap. A company can build customer profiles from information it collects directly, then use those profiles to personalize advertising. The organization is calling for a ban on behavioral advertising, arguing that limiting data sales alone would not prevent this type of targeting.
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Betting Data and Ad Targeting
Behavioral advertising uses information about a person’s activity to tailor ads or promotions. In this case, the EFF says DraftKings uses betting records as inputs to a machine learning model. It argues that AI can process large datasets quickly and that the model’s internal workings may be difficult for people outside the company to understand.
The EFF places the issue within broader concerns about data collected for advertising. It says information generated by ad technology can circulate beyond the original advertising use, including to institutions such as insurers, banks and government agencies. The source material describes this as a wider risk of the data ecosystem; it does not say DraftKings shared customers’ betting records with those organizations.
The organization points to a separate example involving U.S. Immigration and Customs Enforcement, which it says issued a Request for Information seeking information about commercial big-data and ad-tech providers. That reference concerns the broader industry and does not establish a connection between ICE and DraftKings’ customer data.
“The EFF says DraftKings uses customers’ betting records to train a machine learning model to find losing gamblers.”
— Electronic Frontier Foundation
Model Scope Remains Undisclosed
The supplied material does not include a response from DraftKings, the model’s technical details, or independent confirmation of how the promotions are selected. The number of customers affected, the duration of the practice and the targeting criteria remain unclear. It is also not established whether the model identifies people with diagnosed gambling disorders or instead predicts betting behavior associated with losses.
The account does not quantify whether targeted promotions increase betting, losses or other harms. The EFF’s concern that people experiencing problem gambling could be targeted is a risk assessment, not a reported count or outcome. More information from DraftKings, regulators or independent researchers would be needed to assess the system’s reach and effects.
Company and Regulators Face Questions
The next developments to watch are whether DraftKings publicly describes its use of betting data for promotion targeting and whether regulators examine the practice. The supplied source does not identify a pending investigation, announced policy change or formal regulatory action, so no specific next step or timetable is confirmed.
The EFF is urging policymakers to address behavioral advertising broadly, including targeting based on data collected directly by a company. Until more information is released, the model’s operation and its effects on customers remain open questions.
Key Questions
What does the EFF say DraftKings is doing?
The EFF says DraftKings uses customer betting records to train a machine learning model that identifies people likely to make losing bets, then sends them promotions to return. The EFF attributes the underlying report to The New York Times.
Does the report show how many people were targeted?
No. The supplied material gives no count of affected customers and does not describe the model’s full criteria or operating period.
Does the account establish that DraftKings caused gambling harm?
No. The EFF warns that people experiencing gambling-related harm may be vulnerable to targeted promotions, but the supplied account does not quantify resulting bets, losses or other outcomes.
What data does the EFF say the model uses?
The EFF says DraftKings appears to use first-party data collected directly from customers, particularly betting records. The material does not provide a complete list of data inputs.
What policy change is the EFF calling for?
The EFF argues for a ban on online behavioral advertising. It says restrictions limited to third-party data sharing would not address advertising based on data companies collect directly from users.
Source: hn
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