Artificial intelligence–commonly known as AI—is increasingly becoming a part of everyday life. We may think of its use in facial recognition apps, health care applications and even in a routine Google search, but what about its potential in problem gambling prevention and diagnosis?
Phil Sherwood, senior director of Responsible Gambling at PrizePicks, feels that AI can be a boon to responsible gambling programs and shared his perspective in a presentation to the MNAPG board in January.
What is AI?
AI is defined as the simulation of human intelligence in machines. It employs machine learning and language processing to automate tasks, enhance decision-making and boost efficiency.
Historic Use of AI
Gambling operators have been using AI for a long time to boost profits. It’s been used to improve marketing and to produce emotional appeals to specific customers, ultimately getting players to play more and more aggressively. AI has also been used to help gambling operators poach business from other operators.
Why use AI in Responsible Gambling Programs?
There are many reasons to employ AI in responsible gambling programs. Perhaps most importantly, AI can detect early signs of problem gambling, especially considering that more gambling and gaming is being done online. There is more data to access, such as time spent gambling, amount of money spent and other forms of gambling an individual might be involved in.
AI also enables personalized, real-time interventions. For example, if a player is exhibiting specific symptoms of problem gambling, the platform can send a personalized notification alerting them to risky behaviors or simply to make them more aware of their play. This notification might also suggest the responsible gambling tools that are available.
Another advantage of AI is that it reduces reliance on manual monitoring of a gambler’s behavior and allows for 24/7 oversight. With so many transactions available for analysis, a properly programmed AI system can identify potentially harmful behavior much better than humans.
AI-Driven Tools for Player Protection
AI can be used to protect players in several ways. It can identify risk behaviors such as loss-chasing and binge gambling. It can provide real-time alerts when it flags sudden changes that suggest immediate review. And it can also empower players gauge their own risk through gamified self-assessments in which they complete questionnaires. The gamified aspect may make players more receptive to the information that’s provided to them.
Interventional Levels Based on AI Insights
AI can suggest interventions commensurate with risk levels it assesses. For example, a system could address low-risk behaviors with basic pop-up reminders or session time limits. When a player exhibits moderate risk behavior, such as using different credit cards to gamble, the system can provide more tailored advice or impose or suggest temporary timeouts. When AI detects behaviors considered high-risk, it can instigate personalized care calls, exclusion options or even refer a customer to online behavioral counseling.
The U.S. is Behind in Use of AI
Phil noted that some operators, particularly those outside of the U.S. and those subject to regulations requiring the use of AI to monitor behavior, are incorporating AI to monitor player behavior and encourage player safety. However, he expressed concern that the U.S. is fearful of AI and that it’s use is discouraged, something he says would be an egregious mistake.
Challenges and Considerations in AI Implementation
While AI appears to hold considerable promise in protecting players from harm, there are challenges in its implementation. Some of those include privacy concerns (ensuring responsible use of player data), regulatory compliance (aligning AI tools with different jurisdictional standards) and the need for continuous improvement (models need regular updates based on evolving behaviors and research).
The Future of AI in Responsible Gaming and Problem Gambling
Looking ahead, Phil sees increased realization of the potential of AI with additional automation of support options for at-risk players, more predictive modeling for early intervention and standardization across operators for greater impact
“There will be so much innovation that comes from AI,” says Phil. “It’s evolved so much, even in the last year. I think the biggest things that will come from AI are things that we haven’t even thought of yet.”