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NYT: DraftKings used a machine-learning 'elasticity' score to aim promotions at bettors most likely to keep losing; Massachusetts opens review

★★after cutoffpolicy-safetyDraftKingsMassachusetts Gaming Commissionconfidence: medium

A New York Times investigation published Sept 19, 2026 reported that DraftKings built a 2023 machine-learning model scoring online-casino customers by the losses a promotional dollar would generate (an "elasticity" score) and used AI to personalize about $400M of promotions in 2025. Former staff said the score in effect picked out problem gamblers. DraftKings denied targeting anyone based on losses. The Massachusetts Gaming Commission said on Sept 24 it would examine sportsbooks' AI use, and the EFF called for a ban on behavioral advertising.

Key facts

What happened

The NYT investigation itself was not fetchable (paywall), so the figures above come from secondary summaries and are marked confidence medium. The regulator's statement and DraftKings' denial are quoted from Yogonet.

Why it matters

A concrete case of ordinary machine learning optimized for revenue learning to target vulnerable people. It feeds the push to regulate AI-driven personalization, in gambling (the SAFE Bet Act) and in advertising more broadly, just as chatbots add ads.

Changelog

  • 2026-09-30: created (sweep 2026-09-29: Techmeme Sept 24 + HN 519 points)

Sources (5)

id: 2026-09-19-nyt-draftkings-ai-targets-losing-gamblers · updated 2026-09-30 · open in the interactive timeline