Teams at City University London and the gaming analytics start-up BetBuddy are developing a new software system that provides online gamblers with an “early warning” when they show signs of addiction. The software compares users’ gambling habits to data collected from gambling addicts who have since self-excluded from online gaming sites.
City University Professor Dr. Artur Garcez noted, “All U.K. gambling providers are legally obliged to offer customers a self-exclusion option. Our aim has been to help BetBuddy test and refine their system so that it gives providers an effective way of predicting at an earlier stage self-exclusion as well as other signals or events that indicate harm in gambling. This enables customers to use online gambling platforms more securely and responsibly.” He added a machine learning technique called “random forests” could reach 87 percent accuracy predicting gaming patterns that could develop into a serious problem. The system also allows providers to decide to send marketing materials to the player or even suggest self-exclusion.
Noted Engineering and Physical Sciences Research Council Chief Executive Officer Professor Philip Nelson, “This project is an example of how artificial intelligence and machine learning methods can be used to address an important social problem.”
Researchers estimate there are about 593,000 problem gamblers in the U.K. The European Union expects online gambling revenue to top $14.35 billion this year.
