The hit Netflix series Altered Carbon has one of the most memorable depictions of Artificial Intelligence in recent memory. In its cyberpunk future, an entire hotel is staffed and operated by a single advanced AI – which chose the colourful personality of the great Edgar Allan Poe for added effect.
While we are still a long way away from some of the technologies shown in this series (it is set hundreds of years in the future), AI research is still at a very exciting phase in 2020. New paradigms in natural language processing (NLP) and machine learning (ML) is bringing humanity ever closer to truly intelligent AI.
Smarter AI is already having a huge impact in many industries, and even aspects of our personal lives through smart assistants like Siri and Alexa. The casino industry, with its increasing reliance on digital and software technologies, will be profoundly transformed by advances in machine learning and AI in the coming years.
Understanding Machine Learning
All computers use algorithms – a set of clear and detailed instructions on how to get certain things done, solve a problem, or perform mathematical calculations. Smarter software requires very complex algorithms, runnings into billions of lines of code.
A really smart artificial intelligence should be able to do things autonomously, without the need for exact instructions for everything. This requires machine learning – the creation of algorithms that give AI systems the ability to process information and learn new things without being programmed.
Machine learning is used to create algorithms that can acquire knowledge and improve certain abilities. This requires training – for example, a by showing an AI a large number of images of skin cancer lesions, you can teach it to identify new cases by looking at other images from patients.
Using similar machine learning principles, AI can also be taught to detect instances of financial fraud in transactions (by learning to identify suspicious activity), recognize faces from images and video, predict consumer behaviour, and many other complex systems.
The link between ML and Casinos
The gambling industry of the 21st century is incredibly complex. It already uses digital technologies in a big way. Take the modern slot machine for instance – the bread and butter of any casino or gambling establishment, these machines account for nearly 90% of the revenues in the industry.
And they also use algorithms to provide a truly random gambling experience to players. The games inside the machines use systems called Random Number Generators (RNG) in place of outdated mechanical calculators to decide the outcome of each bet.
Marketing, customer relations management, and security are other areas where the gambling industry is starting to rely more on digital technologies including ML and AI. And all this is before we talk about the online gambling industry.
Called iGaming, this sector has seen rapid growth in the last decade, especially after the outbreak of COVID 19. Everything here is digital, in the form of online casino websites, gaming apps, online sportsbooks, and live gambling portals.
Here, the rapid evolution of digital technology is disrupting the user experience in ways that were not foreseen. From online casinos that adopted Flash in the early 2000s to online casinos adopting complex machine learning models that increase the amount of money gamblers spend on their sites.
Ways in which ML can change the Casino Industry in the next decade
Machine learning innovations will affect nearly every aspect of the casino industry in the coming years. The benefits will be felt by both the casinos as well as their player base. Here are some of the most plausible changes we can expect in casino gaming thanks to machine learning by 2030:
Enhanced customer experience
Netflix uses AI to suggest shows and movies to individual users based on their viewing history at the site. Casinos can do something similar in their resorts and online portals using machine learning. AI can analyze player behaviour and create highly customized game suggestions. The whole system could be tied to the smart membership/visitor cards for maximum efficiency.
Improved marketing and promotions
Casinos online and offline require constant marketing efforts to retain and expand their player base. Finding and attracting regular players or “whales” can make a huge difference to the business bottom-line. Using online consumer big data analysis, AI will play a huge role in finding potential customers and offering customized bonuses to bring them to your gambling site/resort.
Better player protection
The gambling industry gets a bad rep because of the social problems caused by addiction and problem gambling. Some individuals, a minority, are vulnerable to addiction. With proper screening, it is possible to identify the telltale early signs of problem gambling.
But keeping track of each player’s activity would be impractical for humans, but easy for AI with machine learning. A pilot project of this sort has already shown promise among online casino players in the UK. This will become a central part of the casino industry in the future.
Smarter AI opponents
Skill-based gambling games like poker are fun because playing against human opponents brings a different level of challenge. Using machine learning, researchers have already created AI that can beat humans at complex games like Go. Using AI bots, casinos could start offering exciting new games and increase revenue streams.
Final thoughts on the COVID impact
The pandemic has raised serious challenges to the entertainment industry, and casino gambling has been one of its victims. We could very well see a pivot to digital gambling if a quick cure to the virus is not forthcoming in the next 2-3 years.
In that scenario, the importance of AI and machine learning will only increase. Using AI instead of humans will lead to cost savings and efficiency in a multitude of spheres, like customer support, payments, and online security, to name a few.
Regardless of the outcome, there is no doubt that the casino industry will be transformed for the better by machine learning in the next ten years.
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