Online gambling has been a game changer in both the gambling and the gaming industry, mostly in positive ways.
First, online gambling achieved a critical thing: the removal of the stigma that followed gambling for many years, especially in the 20th century, when slot machines, video poker, and casinos became more and more prominent throughout the world.
Second, online gambling presented another platform for the gaming industry, and today, we even have online casinos embracing virtual reality and enhanced reality to create an even more casino-like experience for players, who do not have to leave their homes to enjoy it.
Today, you can find a lot of different forms of gambling online. A simple Google search will lead you to online casinos where you can do anything from wagering on the slots to betting on the newest match – in almost every sport there is and then some (including video gaming tournaments). Even if you wish to interact with real people, today’s online casinos give you the option to play live via your webcam. That means you can play blackjack with a live dealer, play poker with people from around the world without leaving your home or play roulette.
Whatever you want to play – online gambling has got your back and then some. In the meantime, slots appear to have received the best treatment. With technology advancing more and more every year, the most current online slots do not leave a lot to be desired when it comes to graphics and gameplay. In the meantime, almost every online casino has both a desktop and a mobile version. You can play anywhere as long as you have an internet connection.
However, what seems to be the dawn of the golden age of online gambling might be seriously threatened by advancements in technology. Mainly, if we manage to create the ultimate artificial intelligence – it’s highly possible that the artificial intelligence will put an end to online gambling as we know it.
What is artificial intelligence?
The thing with artificial intelligence is that the single definition of what is currently considered artificial intelligence changes along with advancements in technology.
The broadest definition, however, refers to an intelligent machine or a computer. The field is led by computer science, and the goal is to enable a robot to take input from its environment and to act accordingly to reach a certain goal.
We’ve seen many examples of artificial intelligence recently. For example, did you know that voice recognition and speech recognition is considered artificial intelligence? Yes, the Siri you have in your phone exists thanks to advancements in this field.
We’ve all heard of an AI beating a human at a chess game, and there are estimations already that we can create an AI that will teach itself as it develops.
Basically, artificial intelligence focuses on enabling machines to reach a level of cognitive thinking that involves problem-solving, recognizing its environment, processing of complex data and understanding communication patterns and speech. But it does not stop there.
Artificial intelligence research is focused on creating an AI that will be able to gain knowledge – commonly referred to as machine learning – then reasoning and using that knowledge to plan, perceive and achieve a general intelligence that will be similar – if not even superior – to human intelligence.
Machine learning raises many ethical questions of the nature of the human mind and of the ethics of enabling a machine to think “like a human” when it would lack the two most fundamental things that make us human: our aging bodies, and our emotions, especially since the first affects the second. A sufficiently developed AI will not be encumbered by time, nor will it be hampered by an aging brain. In fact, the ultimate artificial intelligence that most people think of will be able to keep on gaining knowledge and input for as long as its mechanical parts are functional.
What is machine learning?
Machine learning and artificial intelligence are often thought to be the same thing. The truth is that, as fields, they are connected, but different in essence. While the ultimate artificial intelligence research goal is to create a machine that can have nearly human intelligence, machine learning is teaching a computer or a computer program to gain knowledge and perform a task in a better way.
In this manner, machine learning is closely connected to data mining and statistics, rather than artificial intelligence itself. The computer program uses previous data, or experience, to perform a task better. In fact, today’s smartphones exist because of machine learning, and their functions continuously improve as the field of machine learning advances.
For example, if you teach a program to play a game by giving it a particular set of winning combinations, that’s not machine learning. But, if you show a program the rules of the game without giving it winning combinations, then the program will need to play many times before it can win – in other words, the program needs to learn the winning combinations.
There is three types of machine learning: supervised, unsupervised and reinforced machine learning.
Supervised learning is when you teach and train a program or a computer a particular set of correctly labeled data. In other words, you present both problems and solutions, outcomes, etc. Then, you give the program a new set of unlabeled data or problems. The machine, or its learning algorithm, will use the previous information, or the previous experience, to provide a solution to the problem.
Unsupervised learning, on the other hand, is when a machine is learning from a set of data that does not have labels. Or, you present the machine with problems without an input of what the problem is or what the outcome is supposed to be like. The algorithm, using the input of data, will start to see the patterns and begin to recognize and learn the labels by itself.
Reinforced, or reinforcement, machine learning, is when you give data to the program without labeling it. However, you ask it questions and present problems to it, and then offer grades for the answers. That way, the machine learns the outcomes independently but with a supervised prodding to come to the right result. A good example of this is playing a game. When the computer or the program wins, the winning combination will be traced back, and the computer will learn it. Of course, it takes a lot of games for the machine to be able to find out how to win the game, but it will do so through this type of reinforced learning.
What does the future hold for AI and machine learning?
On the one hand, it’s difficult to predict where AI and machine learning as fields will be in the next few months, let alone one year, or even ten years from now. For example, today, a lot of experts in the field are talking about the neural network method of machine learning, which is based on the way our neurons work in the brain. With that method, the machine is given an input, and it releases a signal via an activation function depending on how it interprets the data it received. However, technology went further than that, and today, we see the use of deep neural networks made of several layers. For example, today’s Google, with its use of deep neural networks, can not only do voice and language recognition, but it can also translate. Google’s speech recognition function improved to 92% accuracy when back in 2012-2013, speech recognition accuracy was 75%.
On the other hand, it’s not difficult at all to imagine what the future holds with AI and machine learning. Many people think of future AIs as robots with the mind of humans, but we have already built machines to do most of the physical work that humans used to do back in the 17th century. Of course, robot AIs will be useful, for there are certain tasks that have not been eradicated yet. But, what we are actually creating the AIs for is knowledge. With AIs, the amount of knowledge will grow exponentially at a very fast rate. So, the following scenarios will not be difficult to imagine:
- Having a computer in your brain with connection to an AI that holds vast knowledge;
- Seeking cures in medicine in a virtual environment where new drugs are tested on virtual humans instead of animals;
- Getting an update where all the new information you need is accessible with a mere thought;
- Going to the doctors and getting not a cure that could work, but a cure that definitely will work, which the doctor will know thanks to an AI enabled simulation program, and many others.
What we can quickly conclude is that AI and machine learning will take over almost every field known to man. We will make advancements in technology with the help of AIs, advancements in medicine. Our quality of life will improve, and we might even be able to solve today’s most pressing problems with ease.
But what does all of that hold for the future of online casinos?
Could AI robots learn to understand casino algorithms?
The crux of online casinos lies in the Random Number Generators, which enable a game to be played fairly. Most of the online casinos today undergo audits that check that they are offering their visitors fair play.
But, a generator is still a program. An AI robot with advanced machine learning capabilities will be able to figure out the pattern in the algorithm. Let’s take a look at a fictitious example:
An AI is being taught to play the slots. The sole nature of the slots with its many winning combinations, depending on the number of lines and symbols in the game. Leave the AI playing the slots for some time, and it will be able to figure out when the winning combination will occur – at the first, fourth, or twelfth spin. Or, it will know how many spins will be needed to win a jackpot – just by taking in the winning combinations as input and hours of experience in playing the slot.
Yes, the random number generators are made to have unpredictable patterns – but for the human brain. The human brain just cannot take that much input of seemingly random data to construct a pattern, which is why the random number generators are so useful in online casinos because they prevent players from figuring out the pattern and cheating. On the other hand, online casinos keep their credibility for fair play because they cannot be rigged with the random number generator. On the contrary, AIs have a much greater capability for gathering and mining data. In fact, machine learning is already being used to find patterns in an immense amount of data that would take the human brain too much time to do. An AI could do that within a few days, or hours, or weeks, but it will still be faster than the human brain.
How AI can Calculate the expected value to master poker, roulette, and other pre-calculated games
Similarly to the example above with the slots, an AI can use the same technique to guess the outcome of poker, roulette, and even blackjack. Think about it. In table games, such as poker and blackjack, the dealer uses a single deck of cards. There are 52 cards in a deck. By teaching the AI the rules of the game and the winning combinations, and by teaching the AI all the possible combinations that a deck of cards can produce in poker or blackjack games, within a certain period, the AI will be able to guess each outcome of the game correctly.
Can you setup an AI bot to cheat an online casino?
AI bots cheating online casinos is indeed a possibility, considering just how fast the fields of artificial intelligence and machine learning are advancing.
With enough time and effort, you can teach the AI to play the games first, and after a while, the AI will know when to place the right wager at the right moment to not only get a win – but to get the highest win possible.
On the other hand, artificial intelligence is not only focused on learning and recognizing patterns. The goal of artificial intelligence is to create a machine that can think, intelligently, without being told to do so. This means that on the one hand, you need an advanced enough AI to be able to do the calculations – but AIs will receive input to gain general intelligence in many different fields and tasks. As a result, the AI might not be willing to just rinse casinos out of money for you.
However, the possibility of creating AIs especially for casino rinsing should not be discarded. These AIs will receive input that will enable them to become the best casino players ever without receiving additional information as to what the impact of winning a major casino jackpot ten times in a row will be.
How can online casinos prepare for what’s to come?
As previously stated, artificial intelligence is slowly taking over every field in the world. In fact, even the random number generator used in casino games is a result of advancements in these areas. It’s not difficult to imagine that on the other side of the AI bot set up to rinse a casino out of money, another AI, who will take over the random number generators of today, will be there to prevent this from happening.
The best thing that casinos can do to prepare is to devise ways of using an AI to protect themselves from AI bots. The AI technology could technically be used either as a security layer against cheating. Moreover, we could soon see individual AIs running as administrators of each casino game. The second way will not only ensure the safety of the casinos and ensure fair play on both sides, but it will also enable game providers to create online casinos games a lot more enhanced (and maybe even different) from what we have today. In any event, the future of casinos might not just be as grim – but bright and worth to look forward to!