The creation-machine: recognition of creative automaticity in the artistic institution

By: Ryo Yunuén Rosas Ortiz

lelluds-trig board.png


The thin line between the analogue and the digital has been completely diffused due to the development of the pseudocode that becomes a system of translations between the human code and the machine code, resulting in the existence of entities capable of using visual codes from the algorithms and the writing of the same pseudocode since the intra-action * between the analogue and the digital, in its multiple combinations and possibilities, has endowed the machines with creative capacities.

In the digital age, society faces the rethinking of economic and thought logic that respond only to the tangibility of objects, therefore, these logics have become obsolete before the new scope of technological practice.

Within this same practice the algorithmic revolution is born, where it is evident that a new development around the concept of creation is present, it is current, it is daily, it is evolving and, therefore, it begins to exceed our understanding of what we call " acts of creation "as a human process.

The awareness of this brings to the table the need to develop a new current of thought within the humanities that proposes that machines can create objects of visuality and knowledge resulting from their own interpretative capacity of the world.

This current must recognize that machines create and that their creations can be called art; that the algorithms that make them work are their creative processes; that the pseudocode that makes up their algorithms determines how they interpret the world and the capacity for action they have over it; that the interface and the devices that allow him to communicate with the world are the means he has to perceive it.

The objective of this essay will be to expose the reasons why this current is necessary proposing and arguing to the algorithm as a creative process, analysing some examples of creative algorithms; exposing the differences between generativity and creation-machine; developing the pseudocode as the translation system between the human code and the machine code, and the black box as the point where the analogue and the digital converge to understand that in the pseudocode is the knowledge that machines have of the world and that the Algorithms are the way in which this knowledge is applied.

Algorithms as a creative process

What is an algorithm and what is the pseudocode?

In a formal way we can say that an algorithm is an ordered and finite set of operations that allows finding the solution to a problem. In colloquial words, an algorithm is a cooking recipe or a movie script; a sequence of instructions to do something.

In the structure of an algorithm we find hierarchical steps that define the possibilities of an object to act. The way in which these algorithms are constructed is through writing, a writing that shares characteristics of the human language and the machine language that builds a bridge of communication between both entities: the pseudocode.

The pseudocode are lines of text that define what the machine feels and feels, what determines the way it looks at what it perceives and, of course, also limits and enables actions that it may or may not exercise on what it has in front of it.

In the pseudocode is the knowledge that a machine has of the world, in the algorithms the way in which this knowledge is applied.


The black box: a game of translations

These spaces of knowledge and thought (pseudocode and algorithms) are housed in the black box, the space where the machine performs a discard, transformation and ordering of data or rather where the translation of the world is done to quantify it to know which the possibilities of incoming information are.

In the black box occur writing processes in which a content of ideas and decisions is specified product of the desire of the writer, here occurs a first translation: from desire and the idea to the pseudocode, a language that can be interpreted both by the human as per the machine and that is thought to open channels of communication between both. This script is read by the machine that in turn makes a new translation of the pseudocode to the machine code (binary code), a language that is only understood between machines and that the human cannot access to communicate with them. After making this translation, a new one occurs which is what ultimately produces an action: the projection of an image, a sound, a movement or a decision; we call this output (OUT) and it is the understanding that the machine has of the first wish or idea that a human wrote through the pseudocode so that she understood it and could interpret it in her own way. Thus, we can understand the pseudocode as the interpretative process that the human being has of the world in writing; This would mean that humans have the possibility to teach machines to do and to think, according to how we do and think.


The creative processes of a machine

The algorithmic revolution is a consequence of the rationalization of perception that begins in the first stage of the algoriceno **, in the era of static algorithms, which reaches its peak and maximum power with Cartesian thought, concluding that all movement, object and matter can be calculated, thus giving an exponential value to the algorithmic interpretation.

Under this logic of the calculation of the world, cybernetics and computer science are developed, which represents the beginning of the second stage of the algoriceno, which Jaime del Val names as the era of the dynamic algorithm, where other types of interpretative practices are being developed. derived from the algorithmic logic that can only take place in digital spaces since only in these places are hybridizations between the concepts "real" and "virtual" evidencing a new thought around the concept "creation", which is in constant transmutation but that launches a totally revolutionary proposal with the arrival of AI (Artificial Intelligence).

The search of the improvement of the AI proposes new creative scopes of the algorithm that put in check several archaic cultural questions that limit the cultural transformation only to the human practices. Now it seems that the idea of a non-human being is beginning to overtake us, and it will be necessary to think about the new cultural directions that implies the existence of entities with the capacity to use systems of meaning as complex as human beings.

To understand how it is possible for a machine to create, understanding that creating is a process of perceiving and thinking the world, I will propose an assumption: Every perceptive entity function, in greater or lesser complexity, as a question-answer. This proposes that our way of relating to the world and in community is possible due to our perceptive capacity that raises the question about what is around permanently. The question-answer system of a machine is found in its code and although it is not as complex as that of a human being, it makes them a perceptive entity insofar as they are in a permanent state of question regarding their environment. It should be noted that up to this point, we only recognize machines as creators and not exactly as creators of art.

A machine that has the possibility of interpreting is a perceptive entity and therefore loses its automatic character since an interpretive question-answer process necessarily leads to analysis, which is why we resort to systems of rules and positions before the world, a kind of comparative system that allows us to understand what is in front of us. That is, ask and think about what to do with the information received.

This system of rules that allows thought processes we can call internal mould *** that proposes an order of interpretation of incoming information to create new possibilities to do. The internal mould is constructed by complex (and not so complex) step structures, this means that the internal mould is an algorithm.

From the era of dynamic algorithms, there is the possibility of making these sequences of steps more complex to the degree of autonomy, which allows machines to have creative processes in all their formality, since the genetic algorithms that make up some artificial intelligences can to be fed with information which allows them to learn by apprehending the interactions with their environment, which means that they absorb referents of what they perceive to transform it into an action.


Creative algorithms: the difference between creation and generativity

Here it has been proposed that any creative process can be converted into well-defined and finite structures of a processual and iterative nature which means that any machine can become a creator, however, this is not entirely accurate.

What is the difference between a machine that paints a portrait and a machine that paints the Mona Lisa on the body of a car? They are doing the same, they build a two-dimensional image on an object with the materials and information to which they have access, but here are some fundamental conditions that have nothing to do with machines and that make one a creator and the other do not.

One of these conditions is the intention. While one totally ignores the systems of meaning about pictorial practice, the other makes use of them because he knows about the technique, knows how to apply the materials and is even influenced by referents that allow him to paint as a painter; her internal mould makes her a painter because she knows and follows the system of rules that position her as a painter.

Understanding this we must assume that any machine that can make use of any system of meaning, even if it does not understand it, becomes a creator of visuality while the machine that ignores these systems is limited to generating objects, images or sounds.


Creative algorithms

An algorithm that exposes perfectly the previously argued is GAN (Generative Adversarial Network) which is an algorithm that has the intention of painting and that made the first pictorial piece auctioned in an art gallery: The portrait of Edmond Belamy (Figure 1).

Figure 1: “Edmond de Belamy, from La Famille de Belamy” (2018), Obvious.

Figure 1: “Edmond de Belamy, from La Famille de Belamy” (2018), Obvious.


The portrait of Edmond Belamy is part of a series of retired of the Belamy family, this family does not exist. GAN has created the Belamy family using references (15,000 portraits that were loaded into their system) and painted all its members from 0 using an equation that allows it to produce quite expressive images. Hugo Caselles-Dupré, a member of the Obvious collective says that these portraits show that an algorithm can emulate creativity.

There is another example, much more every day, that leaves in total evidence to the creation as a system of rules: literary algorithms and poetic bots.

These entities that live only in the network (therefore, their creations too), have the sole purpose of producing and generating content. They are a direct response to network needs **** and to the e-image. These algorithms propose literature and the act of writing itself as a series of established forms and structures that are so unconsciously rigid and accepted that it has become impossible to question them.

Phil Parker, owner of the automated writing company ICON Group International, maintains through the dynamics of his company that literature can be reduced to formulas, codes and repetitions. So much so, that we find these structures infinitely in the network, thousands of books have been written through them, there are published research that has been done entirely by algorithms and there are several companies that offer the same services focused on different types of content.

Both examples are very important because an institution (artistic, in this case) assumes that making a machine in effect is art only because the support, technique and structure of the process are already validated as such, and in turn the market makes the same, what is the difference between an automatic creation and the human creation processes themselves when there is no conceptualization process and a criticism of doing?


Creation-machine: evidence of the automation of creation

Artistic practices are entering a crisis because there is no conceptual training for artistic producers, that is why the creation-machine has become a fact assumed by the artistic institution and, nevertheless, the problem that has been recognized has not been recognized. it implies that many of the current visual proposals are the product of an automation (not always of a machine) of the doing that uses, without reasoning, systems of meaning that have been inherited, learned and taught; just as we program the machines so that they make use of this same system.

This precludes the critique of visuality in art and proposes that art, in so far as it does not exercise a critique of itself, is no longer a purely human practice, this situation is fully evident in the algorithmic practices that create visual products. in the strict order and structure of an artistic construction prioritized as such.

Recognizing that a machine creates forces us to consider the possibility that the work of human artists is in the criticism of the practice rather than in the doing itself. He proposes that more than art creators or art researchers, there is a need for research artists.



Is it necessary to recognize that machines can create? Maybe, but what becomes indispensable is to understand that the creation-machine exists and that there is a lot of creation-machine made by humans. Therefore, a current of thought within the humanities that recognizes that algorithms are the creative processes of machines is necessary.



* Karen Barad, Post humanist Performativity: Toward an Understanding of How Matter Comes to Matter. Specifies that there are not two or more bodies (subject and object) interrelated, but two or more entities can be present in two or more bodies while they relate to each other in such a way that the cuts between phenomena, actions or entities disappear.

** Jaime del Val, Major and minor ecologies in the Big Data era. It proposes to the algoriceno as the geological era in which the human begins to divide the whole world in a grid way with the objective of obtaining a totally objective reading of the world; This conditioned division provoked by the rationalization of perception has therefore the algorithmic logic that has been evolving since then.

*** Leonardo Solaas, Generativity and Internal Form: Proposes the internal mould as a mechanism of order to which the subject / information is incorporated, complying with some type of rule: "Propositions expressed in words, computer code, forces of attraction and repulsion, transmission of impulses between physical parts: everything can be a rule if it fulfils the requirement of transforming or translating an order into another, of generating an output with a certain formal organization from an input of information, matter or energy. "

**** When reference is made to the needs of the network, reference is made to the search for the excessive production of content and the transit of information at uncontrolled speeds that only take place in Internet practices.



1. Barad, K. (2003). Posthumanist Performativity: Toward an Understanding of How Matter Comes to Matter. Signs: Journal of Women in Culture and Society, no. 3, pp. 801-831.

2. Val, J. (2017). Algoriceno. Ecologías mayores y menores en la era del Big Data. En Debates sobre la Investigación en Artes, 48-61. Septiembre 2, 2018. Guayaquil: UArtes Ediciones. 6&masterkey=59e7ea85dae70

3. Solaas, L. (2010). Generatividad y Molde Interno. En Invasión Generativa(pp. 9-24). Buenos Aires: Invasores de la generatividad.

4. CHRISTIES. (2018). Is artificial intelligence set to become art’s next medium?. Agosto 29, 2018, de CHRISTIES Sitio web: one-a-machine-9332-1.aspx

5. Brea, J. L. (2010). Las tres eras de la imagen (pp. 67-127). Madrid, España: Akal.

6. Popescu, A. (2013). Why Write Your Own Book When An Algorithm Can Do It For You?. Junio 16, 2018. De readwrite Sitio web: can-do-it-for-you/