by Diego Maria Cappiello
Sometimes in conflict, sometimes in collaboration, the relationship between art and technological progress is probably as old as civilisation itself. In recent decades, there has been no area of the visual arts that has not had to contend with the electronic revolution in all its forms: from the home personal computer to corporate digitisation, from digital photography to vector design. More recently, generative artificial intelligences (AI) have come to the fore. In fact, they have been existing and operating for about two decades, and their first theorisation goes back even further 〈1〉.
However, their recent and sudden improvement (mainly in the last two years) has drawn the attention of the international public, specialists and non-specialists alike, to the opportunities and dangers of this technological revolution. A revolution that is having a very significant impact on markets, means of production and culture, and on art itself, which is conceived as the product of specifically human skills.
With the wide range of AI suggestions designed with a creative function in mind, it’s not easy to determine the actual adherence of the medium to the decorator’s craft. The ability to come up with a good concept in a matter of seconds with a small number of inputs can certainly raise questions and fears in the field of graphic design and illustration. But when it comes to decorating, contextual functionality and the practical and productive translatability of an idea are undeniable facts, so it is inconceivable, at least for now, that AI can go beyond the rough outline of the initial intuition. For those like me who have always used the traditional pencil as a drafting medium, integrating AI into design was not easy at first, despite my growing confidence with digital languages. However, after much trial and error, I cannot give up a medium that is as useful as it is sometimes – I have to admit – inconclusive.
Without going into too much technical detail, an AI generates images using advanced learning models that are trained on a very large visual database to create new images – similar to those that already exist, but original – based on complex patterns and logical relationships. These models are capable of generating new visual representations from both random input and directed commands. Of course, the ‘intelligence’ of AIs is largely determined by the databases on which they are trained. This means that, given the size of current generative AIs, most of them are trained on images belonging to any branch of art (historical period, style, artist…), all of which can be freely accessed.
Let’s start with the benefits. The first is the efficiency and speed of the AI’s processing power, which allows it to generate a large number of design options of all kinds in a very short time. This means that as an artist I can focus more on refining ideas and compositional choices, saving valuable time and resources. Moreover, the AI is not just a passive tool, but actively contributes to the process, like a valuable creative assistant. There is also the observation that even the most precise AI tends to spontaneously generate additional elements not anticipated by the user, thus stimulating inspiration and experimentation with new possibilities. Finally, through its ability to explore vast creative spaces, AI encourages the designer to break out of conventional patterns. This freedom to explore can lead to unexpected and unique solutions.
Let’s move on to the disadvantages. The first, and most practical, is the inability of the AI to correctly interpret the function of the element being designed. See, for example, the chess images (made with the Midjourney platform) that illustrate this article: although interesting in form, the pieces are impractical on the chessboard because of the double colouring. In fact, the AI used had no small amount of trouble separating black from white, and seemed deeply confused when faced with such a trivial alternative. From an aesthetic point of view, however, there is a strong risk of trivial and repetitive solutions. In other words, there is a real possibility that certain dominant styles or trends will be excessively perpetuated, leading to a loss of originality and an overabundance of similar projects. Human creativity, which as such is capable of breaking the mould and embracing the unexpected, risks being stifled by excessive and homogenised production. AI can thus run into problems of overfitting, i.e. the tendency to generate images based solely on the source data on which the AI has been trained, without introducing new and unexpected elements. This limitation can be fatal, leading the artist to design in an excessively “safe” and uninnovative way.
At present, and especially in the field of decoration – an artistic field characterised by the attention to detail applied to space – the advantages that AI can bring to the artist’s productivity are potentially enormous: thanks to them, a ubiquity and complexity of definition, previously unthinkable in such a short time, becomes achievable. However, the partial reading of elements, the risk of repetition and the general tendency to visual overload make AI a double-edged sword, no more or less than any other tool that the professional must know how to use wisely and consciously.
Based on the current state of knowledge, I would like to say the following. It is true that most of the AIs on the market have neither a database nor training that is designed for strictly decorative composition. However, the results so far suggest that within a few years, or even months, the results will be largely positive. Perhaps more than any other art form, decoration relies on archives and formulae, making it an ideal interlocutor for hypothetical dedicated AIs. However, even if AIs do become the new design standard, it is difficult to imagine them being competitive without a skilled designer who knows how to bend them to a precise and consistent intent.
〈1〉 Bibliographical directions: 1) J. Shane, You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It's Making the World a Weirder, Voracious Books, Boston 2019; 2) M. du Sautoy, The Creativity Code: Art and Innovation in the Age of AI, Harvard University Press, Cambridge (Massachusetts) 2019 ; 3) O. Theobald, Generative AI Art: A Beginner's Guide to 10x Your Output with Smart Text Prompts, Amazon 2023. The first is a brilliantly popular text introducing AI to a wide audience. The second, wide-ranging and more analytical than practical in nature, deals with the medium itself: it is a mathematician's view of the ability of AIs to assist in creative fields. The third is a technical but fluent text, ideal for learning the basics of generative art: it compares the main models of AIs and also the cross-method (text generators used to generate images, as proposed in this article). Homepage; Pompeo Borra, Knights (part.), oil on canvas, 1948, Modena, Museo Civico (photo credits Paolo Pugnaghi/Museo Civico di Modena). Below; renderings of chess redrawn from the concept generated with AI.
