TL;DR
The Electronic Frontier Foundation says DraftKings uses a machine-learning model trained on customer betting records to identify losing gamblers and target them with promotions. The account is based on EFF’s summary of reporting by The New York Times; the model’s criteria, reach and effects are not detailed in the supplied material.
DraftKings is using a machine-learning model trained on customers’ betting records to identify losing gamblers and send them promotions, according to a September report by the Electronic Frontier Foundation (EFF), which attributes the account to The New York Times. The report says the targeting could reach people experiencing gambling problems, raising questions about how betting data is used to encourage customers to return to a gambling platform.
EFF says DraftKings uses customers’ betting histories to train a model that identifies gamblers whose bets are likely to lose. The company then directs advertising to those customers to encourage them to place more bets, the group says, citing The New York Times. The supplied report does not describe the model’s inputs, how it defines a likely losing gambler or how many customers receive such promotions.
EFF says DraftKings appears to rely on first-party data—information collected directly from its own users—to power the targeting, rather than buying additional information from data brokers. That distinction matters because limits on third-party data sales alone would not necessarily stop a company from using its own customer records to personalize promotions.
The report connects the practice to a broader concern about behavioral advertising: companies collect and analyze personal data to select ads for particular people. EFF argues that machine-learning tools can process large data sets quickly and intensify the incentives to gather data. Those broader points are EFF’s analysis; the supplied material does not independently establish the scale of DraftKings’ data collection or the model’s effects on users.
Promotions May Reach Vulnerable Bettors
The reported approach puts the use of customer data in a high-stakes setting: promotions may be directed at people whose betting patterns suggest they are losing money. EFF says people it describes as problem gamblers—those who continue gambling despite harm to their finances, relationships or well-being—could be especially likely to fall within the model’s target group. The report does not say that every customer identified as a likely loser has a gambling disorder, or provide evidence about how many people are affected.
For readers, the central issue is whether betting records are used only to operate an account or also to predict behavior and encourage more wagering. If the report’s description is accurate, a customer’s past losses could help determine whether they see an inducement to return. That raises questions about responsible-gambling safeguards, customer consent and oversight of automated targeting.
EFF calls for a ban on behavioral advertising, arguing that restrictions focused only on data brokers would leave companies able to target users with information they collected themselves. That is the organization’s policy position, rather than a description of an adopted rule or a finding by a regulator.
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The Data Behind Targeted Betting Ads
Behavioral advertising uses information about people to personalize the advertising they receive. EFF’s report says DraftKings’ described system uses its own betting records, which can reveal customers’ wagering patterns. The report does not specify which records the model analyzes, how long it retains them or whether other data is involved.
EFF also warns that information gathered for advertising can circulate beyond the original company. It points to sales of ad-tech data to entities including insurers, banks and government agencies, and cites an Immigration and Customs Enforcement request for information seeking to understand how commercial big-data and ad-tech providers might support investigations. The supplied material does not say DraftKings shared customer betting records with those entities; its discussion concerns the wider data industry.
The EFF report is an advocacy account that summarizes reporting by The New York Times and advances the group’s argument against behavioral advertising. The distinction is relevant: the account of DraftKings’ model is attributed to the newspaper, while the case for banning targeted ads is EFF’s interpretation and policy recommendation.
„DraftKings is using AI to target customers who are most likely to place losing bets and respond to gambling promotions.“
— Electronic Frontier Foundation
Model Scope and Safeguards Unknown
The supplied source material does not include a response from DraftKings, a full account from The New York Times, or documentation of the model. It is not clear how DraftKings defines customers likely to lose, what data points the system uses, how often it updates its predictions or how many users have received targeted promotions.
The material also does not establish whether the model identifies people with gambling disorders, whether promotions are restricted for customers showing signs of harm, or whether users can opt out of this targeting. EFF says people experiencing gambling problems may be likely to be targeted, but provides no figures or independent evaluation of that risk here. The model’s real-world effects remain unclear.
Company Response and Oversight
The supplied report does not identify a regulatory action, a company response or a scheduled next milestone. Further reporting or a statement from DraftKings could clarify the model’s design, the data it uses and what protections apply to customers who may be at risk.
EFF is urging policymakers to ban behavioral advertising and points readers to its Surveillance Self-Defense resources for data-protection guidance. Whether lawmakers or regulators act on the issue, and whether DraftKings changes its targeting practices, is not established by the source material.
Key Questions
What does EFF say DraftKings is doing?
EFF says DraftKings trains a machine-learning model on customers’ betting records to identify losing gamblers and send them promotions encouraging more bets. EFF attributes the account to The New York Times.
Does the report say how many customers are targeted?
No. The supplied material gives no count of customers reached, no share of users affected and no details on how often the model sends promotions.
Does the report establish that DraftKings uses third-party data?
No. EFF says DraftKings appears to use first-party data collected from its own users. The report does not provide technical documentation confirming the data sources.
Has DraftKings responded to the report?
No DraftKings response is included in the supplied material, so the company’s position and any explanation of its targeting safeguards are not available here.
What does EFF want policymakers to do?
EFF argues for a ban on online behavioral advertising. That is the organization’s recommendation; the source does not describe it as an enacted policy.
Source: hn
