AI and player risk identification and response research report

This report summarizes evidence and provides commentary regarding regulation and potential measures around the use of artificial intelligence (AI) in the gambling industry, use of behavioral risk identification, and financial risk identification. To explore these topics, the researchers conducted three studies: a focus group study, a systematic review, and a series of in-depth interviews. The report details each topic and study in sequence, with recommendations based on findings. See also the accompanying summary and presentation.

Findings include:

• AI is being used to personalize gambling products, which may enhance engagement, but also increase risk of harm from gambling.
• There was a lack of evidence to support several indicators for detection of risk that had been recommended.
• The strongest evidence was for indicators for risk detection related to payments.
• Barriers to risk identification using financial indicators involve: the need for sharing data across operators, concerns about privacy, issues related to consent, and regulatory blocks. 
• Recommendations for regulators include developing formal guidance that outlines expectations for the use of AI in gambling, transparent evaluation frameworks for tools used to detect harm in commercial environments, and cross-operator tracking.