The possibilities appear to be limitless. The truth, however, is far more complicated.
Alan Feldman strolled onto the exhibition hall at ICE London, a big gaming industry event, a few years ago.
Mr. Feldman worked at MGM Resorts International for 30 years, focused on compulsive gambling and its financial, psychological, and professional consequences. Prior to his departure from the company, he assisted in the development of a national responsible-gambling programme aimed at assisting players in changing their behaviour in order to lessen the danger of becoming problem gamblers.He observed a few companies touting new devices that would utilise artificial intelligence to not only identify but also forecast problem gambling while on the ICE floor. Mr. Feldman was doubtful right away. He felt A.I. could accomplish a lot of things, but he’d never heard of it being used to anticipate a state of mind.
Artificial intelligence as a solution to problem gambling “Raised many more issues than it answered,” said Mr. Feldman, who is now a distinguished fellow in responsible gaming at the University of Nevada, Las Vegas’ International Gaming Institute. “It was polished, fascinating, and intellectually compelling.” But whether it was really going to achieve anything, I thought, was still up in the air.”
Another obvious question: Isn’t it true that a problem gambler is exactly what a casino needs financially? In a nutshell, no. Even if regulatory difficulties aren’t an issue — gaming operators can be punished or lose their licences if they don’t monitor problem gambling and intervene when necessary – it’s not in their best financial interest.
Mr. Feldman explained, “Casinos must have clients in order to survive.” “And the only way to have customers is to have consumers who are healthy, prospering, and capable of paying their bills and returning the next time.” He went on to say that problem gamblers “usually end up the same way.” “With all of them, the end of the road is the same: they don’t have any money.”
The combination of A.I. with gambling makes perfect sense in a broader sense: infinite and constant data; decision-making; automated systems. With the rise of internet gaming, the possibilities for harnessing this combination for the greater good appear limitless. The reality is far more complicated: understanding human behaviour, navigating privacy regulations, and dealing with regulatory difficulties.
Mr. Feldman was challenging those potential remedies at the same time that Danish experts were attempting to solve the same challenges. Mr. Feldman was wary about Mindway AI, a startup that evolved out of Aarhus University, because it forecasts future problem gambling. The company, which was founded on Kim Mouridsen’s study at Aarhus University, uses psychologists to train A.I. algorithms in spotting behaviours associated with compulsive gambling.
One key obstacle, according to Mindway CEO Rasmus Kjrgaard, is that there is no single signal of whether someone is a problem gambler. In most casinos, human detection of problem gambling is based on only a few factors, primarily the amount of money spent and the amount of time spent playing. The Mindway system considers 14 different dangers. Money and time are among them, but so are cancelled bank withdrawals, adjustments in the player’s playing time, and irregular wager modifications. Each component is assigned a score between one and one hundred, and the A.I. then creates a risk estimate for each player, improving with each hand of poker or spin of the roulette wheel. Players are graded on a scale of green (excellent) to blood red (immediately step down).
Mindway gives its data to a group of experts and psychologists specialised in spotting such behaviour in order to adjust the algorithm to a new casino or internet operator. (The firm said they were compensated independent consultants.) They evaluate each client’s customers and utilise that model as a benchmark. After that, the algorithm repeats its diagnostic throughout the whole client database.
“We can do something about it as soon as a player profile or player conduct goes from green to yellow, and then to the next phases,” Mr. Kjrgaard added. The program’s value isn’t just in detecting those blood-red problem gamblers; it also predicts and catches players when their play devolves by monitoring the jumps throughout Mindway’s colour spectrum. Casinos and online operators currently focus their attention on the blood-red gamblers, he said, but with Mindway, they can detect gamers before they reach that point.
Taking that data and communicating it to a player, according to Brett Abarbanel, head of research at U.N.L.V.’s International Gaming Institute, is the most difficult step.
“If my system labels someone as a possible problem gambler, I’m not going to send them a note saying, ‘Hey, fantastic news, my algorithm has identified you as a problem gambler.'” You should stop gambling right away!’” “That’s what will happen,” Dr. Abarbanel remarked, pointing to the sky with his middle finger.
The question of how to convey that information — and what to tell the gambler — is still being debated. Pop-up messaging is used by some online gaming companies, while texts and emails are used by others. Mr. Kjrgaard expects that clients will use his data to contact the player directly by phone, depending on the level of danger; the specificity of the data, he claims, helps customise such calls.
Since its inception in 2018, Mindway has worked with seven Danish operators, two in Germany and the Netherlands, one global operator, and a US sports betting operator, according to Mr. Kjrgaard. Flutter Entertainment and Entain, two of the largest online gaming companies, have also joined with Mindway, according to their annual reports.
Mindway and similar companies are essentially on their own for the time being because this technology is so new and there is no regulatory authority setting a standard. Mr. Kjrgaard explained, “We wanted to be able to say to you, to anyone else — operators, certainly — that not only do we provide this scientific-based software, but we also want a third party to test the validation of what we do.” “However, it’s perplexing because there are no clear requirements that I can expect my team to meet.”
Mindway’s technology is now used mostly in online gaming. When operators connect Mindway’s GameScanner system to their portal, it assesses not only individual dangers, but also the system’s overall risk. It’s considerably more difficult to apply that level of regulation to in-person gaming.
In Macau, one example of a metric of success may be found. Hidden cameras and facial-recognition technology, as well as poker chips with radio-frequency identification technology and sensors on baccarat tables, are used by casino operators to track gamblers’ betting habits. This information is then sent to a central database, where a player’s performance is tracked and interplayer collusion is monitored.
This is the future, according to Mr. Kjrgaard: financial incentives will drive success. “Smart tables,” as well as initiatives to combat money laundering and financial restrictions, may eventually offer the data needed to supercharge the use of artificial intelligence in in-person gaming.
(It also brings up another issue with using artificial intelligence to gambling: cultural differences.) Players in Chinese casinos, according to Dr. Abarbanel, are accustomed to this amount of surveillance; however, this is not the case in the United States.)
Mr. Feldman believes that artificial intelligence (AI) might be beneficial to casinos in terms of marketing, promotions, and game suggestions, but despite recent advances, he remains wary of its application to assist problem gamblers. He feels that, like the “Your spending is 25% greater than last month” warnings that crop up in online banking accounts, such a tool would be better used personally rather than generally.
“It’s similar to drinking.” Is there anyone you know who has never had a drink in their life? “That doesn’t make somebody an alcoholic,” he clarified. “But maybe you want to bring that one drink a night that’s turned into one and a half, two, three — maybe you want to bring that in a little bit.” But you don’t want the bar to keep track of every record, do you?”
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