Pace Gallery. (2018). Pace Gallery - Random International. [online] Available at: (2018). 'It's not about rain, it's about robots': first permanent Rain Room opens in the UAE. [online] Available at:

Sulcas, R. (2018). Review: In ‘+/- Human,’ Just Us and Our Orblike Shadows. [online] Available at:

YouTube. (2018). Generative Design. [online] Available at:

YouTube. (2018). Jonas Mekas - In Focus - The Artist's Studio. [online] Available at:

YouTube. (2018). The Story of Jonas Mekas. [online] Available at: (2018). Randomness. [online] Available at:

Weiner, E. and Simpson, J. (1989). The Oxford English dictionary. Oxford: Clarendon Press. (2018). Third Workshop on Monte Carlo Methods. [online] Available at:

Haahr, M. (2018). RANDOM.ORG - True Random Number Service. [online] Available at:

Miessen, M., Chateigné, Y., Fürchtjohann, D. and Artières, P. (2016). The archive as a productive space of conflict. Berlin: Sternberg Press.

Statement and counter-statement. Vol. 1. Notes on Experimental Jetset. (2015). Arnhem: Roma Publications.


by José Soares


Chance is defined as the occurrence of events in the absence of any obvious intention or cause. The word obvious is key to understanding the concept. For an event to be considered random or by chance the cause does not need to be absent only untraceable by normal means. For example, by definition the toss of a coin is not random. There are only variables like the initial position, the rotation, the force or forces applied on the coin, its weight and even the features of the surface where it is landing all come into play when the coin is tossed. If we were able to trace all those variables the result would not be a mystery any more. This leads to the question: does real chance exist in the real world? Is there any event that has no cause, or is the ignorance regarding its cause enough for it to be considered chance?

Regarding events like the coin toss wikipedia states the following:

Individual random events are by definition unpredictable, but in many cases the frequency of different outcomes over a large number of events (or "trials") is predictable. For example, when throwing two dice, the outcome of any particular roll is unpredictable, but a sum of 7 will occur twice as often as 4. In this view, randomness is a measure of uncertainty of an outcome, rather than haphazardness, and applies to concepts of chance, probability, and information entropy.

This definition limits and applies the idea of chance and randomness into a practical one that can be usefully applied to the real world. However the definition we are focusing on is an absolute hypothetical randomness that may be defined as an event without cause or impossible to predict. Imagining this kind of chance is as impossible to the human mind as for example imagining a new primary color. This is the argument this essay will be focusing on, as well as analysing a few main different kinds of chance or randomness present in the real world. For clarity I shall be referring to the practical chance that exists in the real world as real chance or real randomness and the hypothetical absolute completely unpredictable chance as true chance or true randomness.

Human chance

As Jonas Mekas stated chance reveals more than the conscious. Jonas was speaking about the random in human action, as in when people use intuition to produce things. Intuition reveals the human subconscious to the world. Similarly to mathematical random, the mind always has a reason to decide something, no matter hidden that reason is. In human decision making, complex systems of interconnected processes happen on both physical and mental levels. On both levels those complex systems can be analysed and studied and divided in order to understand these processes better. However, there is a limit to how deep this analysis can poke through. The whole concept of artificial intelligence relies on the idea that intelligent processes like human decisions can indeed be split into simpler and simpler problems until these can be divided into yes or no, true or false, 1 or 0 problems. This idea is the connection between Human chance and Mathematical chance in its core. There is another school of thought that defends that this is impossible: that intelligent processes cannot be divided into such basic problems. That thought processes cannot be adapted into algorithms or that thoughts are not algorithms at all but are instead spontaneous complex processes of their own.

Depending on whichever school of thought is correct, the reality of human chance changes completely. If human minds can be divided into simpler and simpler problems until it reaches the stage of an algorithm consisting of Boolean problems it proves once again that true chance does not exist in our reality. It is just hidden behind a vast number of virtually untraceable variables that could actually be tracked if enough effort could be put into it. Or on the other hand, if intelligence cannot be split into the most basic problems, where do those problems come from? It might be arguable that intelligence begins in the physical part of the mind and not in the metaphysical, therefore being traceable further back into its origins giving more plausibility to the statement that true chance is not real. However, this question will never be answered due to how complex and deep into the origins of the mind itself it goes. Without an answer there will always be the possibility that true chance might only lie in the intelligent mind.

Universal Chance

In our reality randomness leads to probability which is in itself a kind of order that in big orders of magnitude become more reliable than events that happen on human scale. For example, when predicted, the cosmic microwave background radiation (the light left behind after the events of the Big Bang) was expected to be completely uniform as was calculated using probability. However the tiniest temperature variations in the order of 200 millionths of a degree allowed the formation of matter and all we see in the universe today. The variations or exceptions do exist on universal scales, but 200 millionths of a degree in an area literally the size of the entire universe is a kind of uniformity that absolutely no events on any human scale can even compare to.

However, these variations have happened in an apparently true random order. This uniform (or non-uniform) distribution of matter and energy in the universe after the Big Bang apparently has absolutely no previous origin as there was nothing before it. No influence or interference or trackable variable that might have defined how the universe looks today. Everything else from that moment is theoretically predictable or traceable as the immense domino effect with every single particle of the universe interacting with every other leaves a trail of actions. The Schroedinger Equation predicts this by determining the time symmetry of the universe.

Algorithmic Chance

The website provides a service that uses atmospheric noise, which for many purposes is better than the pseudo-random number algorithms typically used in computer programs. (…) The service has existed since 1998 and was built by Dr Mads Haahr of the School of Computer Science and Statistics at Trinity College, Dublin in Ireland. Today, RANDOM.ORG is operated by Randomness and Integrity Services Ltd. True randomness is so hard to create or find that whole research labs and studies are conducted to research the random and find the most approximate way to achieve it. The most useful proof of true randomness being a distant objective is randomness in computer programs.

Random algorithms have been around since the birth of modern computing as both research tools and for practical functions. The first was invented in 1975 by Michael O. Rabin. The issue with random algorithms is that using mathematical functions to create a random output is the blatant proof that true mathematical randomness will never be achieved. A mathematical formula can always be traced back to the initial input that delivered the result in the end making it always predictable to some degree. The main goal of this research is to create the closest possible approximation to true randomness. An interesting example involving randomness and human nature is the random algorithm Apple used in their first version of iTunes to randomise music playlists. After launching the service Apple received complaints from costumers saying that their device was not playing the songs at random. The fact is that the algorithm was too random and that enabled people to find patterns in the order the songs were being played. Apple had to take that human factor into account and had to update their service so that the order of the music was not 100% random but felt more random.

Chance in art and design

The most obvious example of the use of chance in design is in generative design. What generative design does in product design, for example, is it uses an input or an initial idea and takes a function or an objective into consideration. For example, when designing the frame of a car the computer takes into consideration other designs and the objective or the function of the car frame (being light, strong and solid etc.) and then randomly starts changing the initial designs bit by bit and analyses each one of the results until a satisfactory outcome is achieved. This essentially mimics the processes of Darwinian evolution and applies them to the creation of an object, the same way each copy of DNA in organic reproduction has tiny random mutations in it and eventually, if some of them are useful, they are kept for the next generation.

In graphic design chance is often used as a medium to create original content. This is not a justification for chance in itself but the idea of using chance as a medium is to add an element the designer does not control. This brings an element of surprise into the final result giving it an aura that comes from beyond the final piece. Even though it is argued that using chance or random in design might be lazy or an easily justifiable solution the urge to include an input produced by nature derives from the drive to imitate life and nature in art, the same thing Jack Burnham defends regarding Cybernetic Art in his book Beyond Modern Sculpture. The same way in product design the results of generative designing are very organic and natural revealing peaces of nature that would otherwise not be possible to convey in an object, so does graphic design take advantage of nature by letting it have an input when chance is present. Even though coding and programming are easily conveyed as something completely detached from nature and from what is genuinely natural, these not only facilitate the possibility of conveying the subconscious of machines and therefore being a means to convey the deep thinking of non living things, but also are the ultimate tool to connect the natural with the cybernetic and with the art of the 21st century.


On a human scale the roll of dice and algorithmic randomness can indeed be considered random, but real randomness has the peculiarity of actually creating order. If we consider the example about the dice stated above, each individual throw is in fact unpredictable by human standards. However there is the exact same chance of any face showing up. If two dice are thrown the outcome of any particular roll is unpredictable, but a sum of 7 will occur twice as often as 4. That reveals the peculiarity chance or randomness bring to the real world. When snow falls, the position where each snowflake falls is random in practice. Yet it creates a perfect coating in areas as big as cities or even larger. Probability is an absolute truth in our universe that cannot be broken or bent. Even quantum events, that are sometimes considered truly random, obey the laws of probability therefore not being the true random events mentioned before. Chaotic entropy leads to perfect order. If random was real probability would be impossible as no sort of order would come from it.

True chance is a concept that will never be observed or achieved. But like Jonas Mekas said chance reveals more than the conscious, it is fair to believe that this is true not only on a human level but also for events involving things that are considered non living. Using chance into projects is a way of letting nature or something else into the final piece. If it is atmospheric noise from, or an input from a random algorithm, it feels like something external or something higher has an input into the object. By doing that, nature reveals itself bit by bit, the same way a painter or a photographer reveals itself when he lets intuition or instinct come into play when making decisions.