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Artists working with code, hacking and new media have been around for as long as there has been code. And yet the veritable Cambrian explosion of generative AI that we have experienced in the last two years has cut just as deep a swathe through the art world as it has in many other areas of our lives. Ever since applications such as Dall-E, Midjourney and Stable Diffusion have been available to virtually everyone, artists and designers have been experimenting with them and using AI to search for new subjects and visual languages. The results have been more or less directly incorporated into artistic works: generated visuals have been painted by hand on canvas or embedded into videos, artificial reality and virtual reality works.

These creations, often referred to as AI art, are increasingly raising the question of whether these machines can be creative in and of themselves. And whether they could replace artists, designers and other creatives in the foreseeable future. In certain areas of applied art, such as illustration and photography, the extent of the upheaval is already foreseeable: processes are being streamlined, with artificial intelligence scaling up individual work steps or taking them over completely - for example, when subjects of a photograph are to be mounted in front of a different background.

But what about the visual arts? One clue could be the historical role of photography: it once freed painting from the need to depict reality, paving the way for new art movements - starting with Impressionism and Cubism. Without photography, neither Van Gogh nor Picasso would have taught us to see the world in new ways. In this sense, we can also trust generative AI to revolutionise the art world and usher in completely new art forms. What could the first steps in this development look like in concrete terms? Three possible answers are emerging:

1. A return to the artisanal aspects of creating art

In a world in which artists define themselves first and foremost through innovative ideas, generative AI tools could draw attention back to the craftsmanship of painting, sculpting and modeling. However, this prospect, although fascinating, seems unlikely. In the near future, advanced AI will also be able to handle brushes, paper and canvas independently. Artists are already experimenting with painting robots that handle traditional materials. The more successful this becomes, the more the importance of artistic craftsmanship will be called into question again.

From an art historical perspective, this would not be as new as it might seem at first glance. Constructive Art, Concrete Art and Minimal Art were also looking for ways to get rid of the human element and paint pictures and produce objects that were "industrially manufactured". And more than a century ago, the followers of the avant-garde wanted to abolish the creative genius. If we can achieve this with the new, generative applications, it would be entirely in the spirit of art history. However, it is more likely that the exact opposite will be the case - that the artist as an author will become even more important.

2. Redefining creativity

From the Romantic era, when we invented the "singular creative genius", until today, when our society operates within the framework of a creativity dispositive, the concept of creativity has been constantly changing. After talking about the "creative economy" and "creative thinking" not long ago, we are now referring to "artificial creativity". In its essence, however, it remains - just like art - an unsolved mystery. Both creativity and art are constantly being negotiated in discourse and cannot be conclusively described by means of definitions and axioms.

Here, too, generative AI is proving to be astonishingly connected to the history of artistic practice as here, too, essential moments lie in the unknown: we do not know in detail and we can never know conclusively what happens in the many layers of artificial neural networks. The moment a diffusion model starts detecting an image in the noise of latent space - i.e. in all higher-dimensional possibilities - can be compared with the moment in which a painter stands in front of an empty canvas and projects their imagination onto the empty surface to give it form with paint and brush.

Minimal art artist Robert Ryman, who only painted white pictures, called the white surface "total sensitivity". In his spirit, the latent space of AI could be described as the "total sensitivity" of the machine. Training an AI with images from the past would, correspond to an artist's art-historical education, experience and recollected impressions.

3. Écriture automatique as an artistic strategy

A century ago, the surrealists put an artistic strategy called écriture automatique, spirit writing or psychography into practice. The idea was to create text and image from the unconscious, without intellectual control. This approach has a modern equivalent in the use of generative AI for art production. (The fact that one of the best-known text-to-image programs, DALL-E, is named not only after the lonely robot WALL-E but also after the most famous surrealist painter Salvador Dalí would appear to be no coincidence). Dalí saw himself as a medium, shifting the authorship of his art to his unconscious and his dreams. This did not diminish his influence as an artist. Ever since, avant-garde has no longer been the craftsmanship and personal expression of an artist but rather the idea and inspiration that is seen as the essence of an artwork.

Here, too, generative AI is proving to be astonishingly connected to the history of artistic practice as here, too, essential moments lie in the unknown: we do not know in detail and we can never know conclusively what happens in the many layers of artificial neural networks. The moment a diffusion model starts detecting an image in the noise of latent space - i.e. in all higher-dimensional possibilities - can be compared with the moment in which a painter stands in front of an empty canvas and projects their imagination onto the empty surface to give it form with paint and brush.

Minimal art artist Robert Ryman, who only painted white pictures, called the white surface "total sensitivity". In his spirit, the latent space of AI could be described as the "total sensitivity" of the machine. Training an AI with images from the past would, correspond to an artist's art-historical education, experience and recollected impressions.

These considerations show that generative AI technologies not only take up and revitalise various currents in art history but may also lead us to the threshold of a new era of art - an era in which generative AI tools act not only as aids but as partners in the creative process and assist with the birth of previously unimaginable forms of creativity.

Today, AI is helping us to recognise patterns in almost all areas of knowledge and to extract meaning from them. In the future, this could also apply to the fine arts. We should therefore speak in terms of "artificial augmented creativity" - extended creativity that gives rise to new, contemporary avant-gardes. Just like photography did around two centuries ago.

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