Art as a replication of reality
Etymologically, art refers to skills and crafts, so all humans are artists in numerous ways. In the post-Renaissance understanding of art, artists interpreted reality and manufactured a different or maybe even flawed version of it. Whether it was a painting or a sculpture, the artist took the original, passed it through their filter and used another medium to code a message. A new reality could also be born from an analogical copy-paste, if we take into account artists that tried to replicate reality. Afterwards, this fabricated reality, a duplicate of the real world, was shared with others.
This interpretation of life was purely human, visibly skewed – at least until 1839, when cameras appeared and the artists were no longer forced to replicate reality. At a later stage, a certain need grew in the artist, that of reducing reality to its very essence, to an aura, a state of feeling or to a concept, when we consider contemporary art.
AI art: mimicking human art or art on its own?
Creativity has always been associated with human intelligence, and for now, AI has mainly copied ‘old art’ masterpieces. Several computer programs were trained on works by artists like Van Gogh or Picasso. Then they tried to understand each style, and after this process of learning, they interpreted images that humans fed them and mimicked the input data based on each style. And here lies a conflict: an artist does not have a permanently defined style. Art can be considered an interpretation of the environment (data) that can be radically different from one moment to another. There is no such thing as a well-defined and set artistic style. Picasso painted radically differently in a matter of a few years.
Therefore, software that replicates Picasso or Van Gogh does not own a real formula of their art, but simply mimics an interpreted sequence of each one’s work.
For Lev Manovich, (Professor at the City University of New York, Lecturer on the PhD Program in Computer Science, the M.S. Program in Data Science, the M.S. Program in Data Analysis and Visualization and the M.A. Program in Digital Humanities), “AI art is type of art that we humans are not able to create because of the limitations of our bodies, brains, and other constraints.” (Defining AI Arts: Three Proposals)
Machine learning is not fully autonomous.“There are at least three points in this process where a human author makes explicit choices and controls what computer [sic] would do. First, a human designs network architecture and also an algorithm used to train a network (or selects from the existing ones). Second, the human creates the training set. Third, the human selects what in her/his views are most successful artefacts from many more the network generates.” (Lev Manovich, Defining AI Arts: Three Proposals)
Alexander Peterhänsel, Professor of Digital Media at the Brandenburg University of Applied Sciences: “What is currently labelled as machine intelligence is in fact advanced pattern recognition. It is for sure amazing to see how machines are able to surpass certain human cognitive abilities, but this has nothing to do with our holistic concept of human intelligence, which involves understanding and making sense of a situation versus merely recognising certain patterns. The development of an understanding of our reality is a creative process in and of itself: we have to create a relationship with our surroundings and situate ourselves in the universe.” – Read the full interviewo of Alexander Peterhänsel
Now, considering this, computer-made art has not made much progress regarding its autonomy since its beginnings. At its core, machine learning has remained the same: it is dependent on the input that humans give it, and dependent on them teaching it. This means that ‘we can’t claim that generation of cultural artefacts [sic] via machine learning/neural networks is more ‘intelligent’, i.e. shows the higher level of autonomy than any other computer art method.’
We could be tempted to state that “all methods developed in computer art since 1950’s [sic] are equally valid parts of ‘AI arts’.“.
If we debate what makes something authentically AI, then it must be tied to a reduced level of human control and a reduced need for guidance from a human agent. Machines could potentially develop their own algorithms, at their own pace, based on their own interests and interpretations.
Henrik Junklewitz, scientist at the Joint Research Centre at the European Commission: “A human artist also learns their craft through repetition, so maybe what we perceive as a new pattern is only an intuitive composite of these learnt things. In that sense, I would be confident that an AI system could eventually, with enough training, combine the patterns it reproduces into something that we as humans perceive as new.” – Read the full interview of Henrik Junklewitz
When will AI art separate itself from the human factor?
Henrik Junklewitz: “Throughout history, works of art have shared similarities tied to the time and place in which they were crafted. Ornaments, materials, musical instruments and pigments were shared across entire continents. In various ways, our culture is the product of what was passed on to us by others who modified it a bit and added something new – a sort of mash-up. AI art basically goes through this human filter: humans are responsible for developing the networks, the algorithms and the machine learning.”
Henrik Junklewitz: “At this point in time, AI is mostly a large collection of tools designed by humans for specific purposes. It’s true that we are living in a time where these tools are becoming extremely powerful and successful, even outperforming humans in specific tasks, such as playing a game or detecting a very specific pattern in data. But it’s also important to realise that the term ‘artificial intelligence’ can be a bit of a misnomer, largely because of the many meanings people associate with the word ‘intelligence’…it is much more useful and also less dangerous to consider AI as a powerful new tool for humans rather than something that is self-aware or capable of agency.”
Artificial intelligence has not proved capable of expanding art mediums and crafting new artistic means of expression. It has always depended on data that humans fed it, within the realm of their imagination and technical abilities.
Can AI step out of the environment it was trained in? If so, when? When will it discover new lands on its own?
Professor Alexander Peterhänsel: “There is a clear distinction between mindlessly mashing up styles or patterns and consciously deciding to combine influences into something new; the former is a description of what so-called AI-generated art is, and the latter is a description of the human creative process. The possibility of machines developing anything remotely similar to human creativity is science fiction; it will not happen before the advent of so-called artificial general intelligence (AGI). AGI, sometimes also referred to as ‘strong AI’, describes the hypothetical ability of a machine to understand or learn any intellectual task a human being would be capable of.”