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The Electronic Frontier Foundation says DraftKings uses customer betting records to train a machine-learning model that identifies losing bettors and targets them with promotions. The account is based on reporting by The New York Times; details about the model, its safeguards and its effects have not been made public in the supplied material.
The Electronic Frontier Foundation says DraftKings is using customer betting records to train a machine-learning model that identifies people likely to make losing bets and respond to gambling promotions. Citing The New York Times, the digital-rights group says the company then targets those customers with ads intended to bring them back to bet, raising concerns about the use of personal data to reach people who may be vulnerable to gambling harm.
According to the EFF’s account of the Times reporting, DraftKings uses its customers’ betting histories to train a model that looks for people likely to lose. The company then sends targeted promotions to those identified customers. The EFF says the promotions are designed to encourage them to return to the platform and place more bets. The source material does not describe the model’s inputs in detail or provide independent performance data.
The EFF argues that the approach may reach people it describes as problem gamblers: people who continue gambling despite harm to their health, finances or relationships. That is the group’s characterization of who may be affected; the supplied account does not establish how many customers were targeted, how the company defines risk, or whether every customer selected by the model experiences gambling-related harm.
The EFF says DraftKings appears to rely on first-party data—information collected directly from its users—rather than buying additional information from outside data brokers to train the model. The group says this matters for proposed limits focused only on third-party data sales: such limits may not stop a company from using its own customer records to personalize gambling promotions.
Promotions Based on Betting Records
The reported practice links a customer’s past gambling behavior to the promotions they receive. If the account is accurate, the system could use patterns associated with losing bets to decide whom to encourage to return, creating a conflict between commercial targeting and reducing the risk of harm. The EFF says customers identified as likely to lose may include people experiencing problem gambling, though the source does not quantify that overlap.
The case also illustrates a policy question beyond DraftKings: whether rules should address companies’ use of data they collect themselves, as well as information bought or shared by third parties. The EFF advocates a ban on behavioral advertising. That is the organization’s policy position; the report does not establish that such a ban is current law or that it is the only available response.
How the Model Uses Customer Data
Behavioral advertising uses information about people to personalize the ads or promotions they see. In the DraftKings account described by the EFF, betting records serve as training data for a machine-learning system that predicts which customers may make losing bets and return after receiving promotions. The source does not explain how the predictions are made, what other information is used, or how often the model is updated.
The EFF places the practice within a wider debate about data collection in advertising technology. It argues that machine-learning systems can process large datasets quickly and that uncertainty about which data points drive their outputs can encourage continued collection. The group also points to broader concerns about data gathered for advertising being accessed or used by other organizations. Those wider concerns provide the EFF’s policy context; they are not evidence that DraftKings shared customer betting records with outside entities.
Model Scope and Safeguards
The supplied source does not say how many customers DraftKings has targeted, when the practice began, how long it has operated, or which promotions were sent. It also does not provide the model’s accuracy, the criteria used to classify customers, or information about safeguards, customer notification or opt-out choices.
The account is presented by the EFF and attributed to reporting by The New York Times. The source material includes no response from DraftKings, no company explanation of the model’s purpose, and no regulator’s findings. It remains unclear whether the company disputes any part of the account or whether authorities are examining the practice.
Company Response and Policy Debate
The next developments to watch are whether DraftKings publicly describes its use of betting data, including the model’s scope and any protections for customers, and whether regulators or lawmakers address personalized gambling promotions. The source material does not identify a scheduled announcement, investigation or policy decision.
The EFF urges policymakers to restrict behavioral advertising and directs users to its Surveillance Self-Defense resources for ways to protect personal data on apps and websites. Those resources are general privacy guidance; the source does not say they prevent DraftKings from using information already collected through its service.
Key Questions
What does the EFF say DraftKings is doing?
The EFF says DraftKings uses betting records to train a machine-learning model to find customers likely to lose bets, then targets them with promotions intended to bring them back to the platform. The EFF attributes the account to reporting by The New York Times.
Does the source say DraftKings buys data from brokers for the model?
No. The EFF says DraftKings appears to use first-party data collected directly from its users. The supplied material does not document the model’s full data inputs.
How many customers were targeted?
The supplied source gives no figure for the number of customers targeted and does not state how long the practice has been in use.
Has DraftKings responded to the report?
No DraftKings response is included in the source material. It does not say whether the company disputes the account or has announced changes.
What policy change does the EFF support?
The EFF argues for banning behavioral advertising. It says limits focused only on third-party data sales would not address targeting based on information a company collects directly from its customers.
Source: hn
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