50 Years of Innovation
Back in 1961, Edward E. Thorp and Claude Shannon developed the first prototype of a wearable computer and used it to bring the house down at Vegas casinos. After devising card counting with the help of an IBM 700, Thorp was curious to see if he could use mathematics to win at roulette the way he had managed to do with blackjack. The device may be considered simple by today’s definition of a computer, as it was designed with the sole purpose of beating roulette. Thorp discusses the computer and how it facilitated successful prediction of roulette in the second edition of Beat the Dealer, published in 1966. Although he didn’t go into many details, he pointed out that “in an hour’s run, betting no more than $25 per number, we won a fictional $8,000!”
While Thorp’s programme was aimed at helping the player against the house, another software developed a year later, put the AI and the gambler at the opposing ends of the table. In 1962 a programme developed by American cybernetic scientist Arthur Samuel beat R. Neely, the best USA checker player of that time. The software allowed mainframe computers to play checkers with humans, all the while learning by itself, improving its gaming skills based on previous experience. It was this incident in particular that triggered further observations and started the AI software evolution.
Benchmarks in 2017
Obviously, technology with its progressive nature has come a long way since the early 1960s and artificial intelligence has become increasingly sophisticated and prevalent in the gambling industry. It’s used by operators to improve playing experience, blurring the real and virtual in live casinos and to predict and accommodate the needs of players for an immersive gameplay designed for effortless transition across platforms. Of course, AI is also used to develop bots and algorithms like the ones we’ve got used to playing with chess, backgammon, and more. Now, with all the leaps and bounds that the AI has been making, we’ve seen software so sophisticated that it beat the best players in complex games like poker and go.
In May 2017, Google’s AlphaGo — the AI developed to tackle the world’s most demanding strategy game — is stepping down from competitive matches after defeating the world’s best talent. The latest to succumb is Go’s top-ranked player, Ke Jie, who lost 3-0 in a series hosted in China. The AI, developed by London-based DeepMind, which was acquired by Google for around $500 million in 2014, also overcome a team of five top players during a week of matches. AlphaGo first drew headlines last year when it beat former Go world champion Lee Sedol, and the China event took things to the next level with matches against 19-year-old Jie, and doubles with and against other top Go pros.
“Alpha Go played many surprising moves in the game… Playing games like this will give us new ideas about how to play… If there’s an opportunity, we should do more of these”
Gu Li, 9 Dan Professional
AI Is Used in the Prevention of Gambling Addiction
In recent years, many countries have been seriously considering the gambling addiction problem. In order to prevent ludomania, lawmakers have been continuously introducing different bans on gambling activities, measures that turn out to be not very beneficial for the development of the said industry. As it has been shown in recent studies, the AI systems can be very effective in combating gambling addiction and its consequences. Consequently, recent studies carried out by the University of London have a significant value for the entire gaming industry. According to the scientists, they managed to elaborate a unique system based on the AI allowing to detect a pathological addiction to gambling, even before it transforms into a real addiction.
In order to create such a unique gaming platform, researchers have teamed up with a well-known software developer BetBuddy.The new version of BetBuddy platform has become one of the most advanced solutions in the gaming industry. It keeps track of user’s gambling behavior in casinos through using AI technologies. Player’s behavior model is identified through using inference mechanisms and neural networks, as well as random forest algorithms, indicating and signalizing the exact time when players reach problematic levels. This mechanism enables online casino operators to decide either to block problematic accounts or to apply some limitations to them, etc.
“As soon as it starts functioning, we no longer call it artificial.”
John McCarthy on the concept of AI
What Does the Future Hold?
An industry built on probabilities, odds and statistics, there has always been an inherent link between science and gambling, but almost across the board the information inequalities between bookmakers and punters are being eroded by advances in science and technology. The interesting question for the industry is to consider the effect of information parity. What does it mean for the house advantage? Will margins reduce to unsustainable levels? Will prices reduce to levels uninteresting for punters? If it becomes common practice for punters to look to science, it is not unreasonable to think it could shrink or at least significantly change the shape of the industry altogether.