In the early years of online casinos, credibility was one of the biggest problems faced by the industry. The question on most players’ minds was the following: How can you trust that the outcomes of online casino games are well and truly random, without any manipulation by the casino in question? It's a fair question and one which reputable online casino operators worked incredibly hard to dispel. 

The answer to the credibility issue is deeply rooted in the concept of an RNG, a.k.a. Random Number Generator. Together with independent auditors, online casino watchdog authorities, and reputable software providers, online casinos have established an ironclad reputation as providers of transparent, fair, and trusted game outcomes.At the heart of this issue is an RNG. Players want to be doubly sure that every time they spin the reels of their favorite slot machine game, draw a card in Blackjack, Baccarat, Video Poker, or place a bet on Roulette, that the outcomes of these actions are 100% random. 

With regards to slots, the outcome of every single spin is completely independent of the previous spin and has absolutely no bearing on the next spin either. It's the same with cards drawn in Baccarat, Blackjack, Video Poker, and Caribbean Stud Poker. In fact, virtually every online casino game outcome, except for live dealer games is governed by RNGs. In order to be believable, there can be no discernible patterns, and the result must be as close to a completely random outcome as possible.

There is just thing that irks online casino players: Somebody had to program the RNG to begin with, and if it was is programmed, there is an algorithm that governs the outcomes?

Pseudo-RNGs and True RNGs – Unravelling the Code

To better understand how an RNG really works, we have to do delve deeper into the technical specifications, programming language, and ultimately the highly-complex functionality of RNGs. The core of a software RNG is a carefully constructed mathematical algorithm which works in tandem with a computer, through repetitive operations to generate a truly random seed value. When we focus our attention on hardware RNGs, there are no seeds required because hardware RNGs do not focus on computed values. These operate on the basis of digital ‘snapshots’ of natural occurrences. The beauty of hardware RNGs is that they are impervious to the nefarious advances of hackers attempting to manipulate outcomes. It is impossible to predict future outcomes, since there are no sequences that repeat, and there is no algorithm in play.

The concept of an RNG is difficult to comprehend for a layperson, so it's worth delving a little deeper into the mechanics of these systems for a closer look. The pseudo-RNGs that many of us are familiar with use a seed, and a table of preset constants working with mathematical algorithms. The hardware RNGs that we have alluded to above use no such seeds and focus only on naturally occurring noise. The seed is akin to the base value that is used to initiate proceedings. Once the computer program has that base value with the software RNG, it can utilize all other numbers that are contained within the program to formulate results. Some computer whiz kids have attempted to explain the concept of seeds in the following way:

Seeds and RNGs for pseudo-RNGs

‘If you think of a stand-alone freezer as a seed with lots of lollipops in it, the RNGs are the lollipops. Now, if there are thousands of seeds a.k.a. stand-alone freezers, each with thousands of lollipops in them, one of these freezers can serve as the seed, and one of the lollipops contained within that seed can be randomly selected.’ The mathematical formulae used by random number generators play an important part in the process. 

One such system is known as the Linear Congruential Generator. The functionality of a Linear Congruential Generators falls well outside the scope of this introductory guide to how RNGs work, but it is certainly worth reading for those who are interested in the mathematics and programming language behind it. What is clear is how important RNGs are in the online casino world. The takeaway from the information that has been provided until this point is the following:

•    There are true RNGs (Random Number Generators) & there are pseudo RNGs.

In all cases, the objective of the system is to generate a random result for online casino players. By creating a random result, there is no possible way to predict the outcome. The point is that online casinos can ill afford to have hackers infiltrating systems for their own gain. For true randomness to be measured, the computer must evaluate and assess a physical phenomenon. It could be something in deep space, or something subatomic. 

In quantum mechanics, the concept of detecting the onset of radioactive decay is impossible to determine. In other words, it is completely random. By not knowing when something is going to occur, third party sources intent on manipulating information, or functionality are effectively shut out of the prediction business. On a more practical level, RNGs may focus attention on the precise times that users are punching the keyboard to generate these true random numbers.

Of course, there are Pseudorandom Numbers which we can focus our energy on. Recall the seed value we spoke of earlier with the standalone freezers and the lollipops within them? These are pseudo random numbers. It must be said that these seed values can be predicted since the computer is no longer assessing random information from the environment like radioactive decay of atoms.

The hacker with the right skills could technically work backwards to figure out the pseudorandom number that was chosen, in the absence of an encryption key with no additional randomness. Once again, the theoretical complexity of RNGs comes into play. There is a real fear that RNGs lack credibility, particularly with chipmakers which may offer backdoors to RNGs, allowing hackers to gain access to a user's information. Several chipmakers like VIA and Intel have experienced several problems with this in recent years.

Quantum Physics & Subatomic Particles – RNGs are in The Domain of Rocket Scientists

Dr. Mads Haar penned an article about ‘Introduction to Randomness and Random Numbers’ in which several important aspects of pseudo-RNGs and true RNGs were highlighted. Dr Haar found that PRNGs were excellent in terms of efficiency while TRNGs were poor in terms of efficiency. PRNGs are also deterministic while TRNGs are nondeterministic. In terms of periodicity, PRNGs are periodic and TRNGs are aperiodic. When it comes to randomness, the jury is out on precisely what is considered to be random in the universe. 

On a subatomic level, when quantum physics is brought into the picture, there are those who believe that there is a predetermined basis for subatomic particle behavior, much like there is for everything else in the universe. While it is theoretically possible to argue this way or that and possibly deduce systems for unravelling the complex code of randomness, the fact of the matter is that the notion of random describes any phenomenon that cannot realistically be predicted by human beings.

This highfalutin discussion, technical though it may be, is precisely what governs the gameplay of a seemingly innocuous slot machine game. Given that all RNGs are independently tested and verified by oversight agencies such as TST (Technical Systems Testing) and eCOGRA Safe & Fair, online casino players can rest assured that they are in safe hands whenever they click the spin, deal, roll or draw button.