One of the big topics today is generative AI systems - almost everyone has probably tried tools like ChatGPT or Dalle-2, or at least read about them. But what exactly is the relationship between these tools and creativity? At the turn of 2022 and 2023, a considerable debate has opened up about what role AI can and should play in human work, creativity or uniqueness, and what makes humans unique and irreplaceable.

Try to write a haiku on creativity and humanity in three minutes. If you put such a request into ChatGPT, you'll get something like this:

Creativity,

A soul that shines to the world,

Humanity's footprint.

Judging the quality of such a "poem" is tricky, but formally, it is a haiku. If one were to read it dispassionately, one might not be able to tell whether it is a text by a self-taught poet or a text generated by artificial intelligence. At this point, we run into the problem noted by Peter Singer's ethics. This Australian ethicist observes that defining a human being by a set of specific functions or characteristics is difficult. For example, if we were to say that a human being is capable of drawing pictures, we would either have to include elephants or chimpanzees in the set of humans or raise the bar and then the number of persons would not fall into it. We would get similar results for arithmetic, logic problem-solving, or social relationships.

An even more complex situation than between humans and chimpanzees is between humans and AI systems. That sense of social upheaval was (and perhaps still is) genuinely existential - what can we create better than machines? One definition of a human is that it is an animal capable of creating art. Of course, not every human being creates art, but perhaps they could be educated to do so. But then, what do we do when we can't distinguish between the average student and ChatGPT?

The search for a distinguishing feature between man and all other beings (technology, animals,...) is long, and it seems not entirely productive. Modern technology makes it possible to automate many activities to such an extent that it is impossible to say that there are tools that cannot or will not, in principle, do something. Artificial intelligence will probably soon be better at running companies, writing documentation for computer programs, or analyzing the spectra of stars than humans. When Nietzsche says that man is an animal capable of promise, he is referring to three critical levels of humanity as he might have understood them in the 19th century:

1. One can use language. But modern systems using generative artificial intelligence can do that, too.
2. Man can orient his thinking to the future. But what does it mean to think into the future? It is weighing risks and probabilities, which current Bayesian decision-making systems can do - statistically, better than humans.
3. A man has credibility. His promise can be believed and acted upon. However, we commonly use expert systems for decision-making as well. We go on the bus because we know it will run at a specific time according to IDOS or Google Maps, we buy stocks according to financial market models, etc.

AI systems seem to be able to take over all this for humans. Except for one thing - they're not an animal. But this leads us back to wondering if this is enough, and it seems that most people will intuitively feel that it is not - namely, that a mouse with a smartphone on its back is not the same as a human. But how to proceed in such a situation?

The first step to deal with this problem (and perhaps even the anxiety of being replaced by machines) is to abandon the entity thinking model. For a relatively long time, we have imagined that creativity is a characteristic of the individual - some people have it higher, others lower, some cultivate it through coursework, and others attach no specific importance to it. But if we look, for example, at the history of science or art, we can observe something entirely different. To illustrate this, let us take two measures.

In medieval art, perspective was not used - the size of figures and other objects usually corresponded to their importance or hierarchical arrangement. However, when Filippo Brunelleschi (1377 - 1446) came up with the use of perspective in architecture, there was a relatively rapid expansion of the technique in architecture and later in painting - Leonardo da Vinci (1452-1519) worked with it routinely, and other artists would hardly question it for centuries to come. The perspective would become a thought construct that would spread to other artists and be one of the pillars of art until the 19th century.

An example from science is the use of matrices. Matrices are mathematical structures that allow you to perform calculations in linear algebra. The concept of matrices has evolved, but the "inventors" of matrices are James Joseph Sylvester (1850), who first used the term, and Arthur Cayley, who defined the basic operations with matrices shortly afterwards. Matrices did not seem to have much practical use for a long time. It was not until the beginning of the 20th century that they became a fundamental mathematical formalism, which made it possible to think about spacetime in the context of general relativity or the basic properties of solids.

Perhaps an even more remarkable example is the dispute over who first discovered special relativity - Albert Einstein or Henri Poincaré. Both came up with essentially the same equations at the same time. And Einstein was indeed able to describe and understand them much better. The point of all these examples is not to tell history in caricatured shorthand but to show that creativity is not a matter of one man independent of the culture and other discoveries of his time but is part of the environment in which he finds himself.

Creativity is, therefore, a shared phenomenon that can be well supported. For example, Niels Bohr ran his physics institute in Copenhagen, which - thanks to Bohr's careful efforts - was an extremely creative environment. This meant that some of its members won Nobel Prizes - Bohr, Franck, Heisenberg, Dirac, Urey, Hevesy Rabi, Pauli, Bloch;... Creativity is not a vice that flows from the individual no matter where they are, but rather the manifestation of a specific ability to exploit the intersection of forces and interactions that act on the individual, as Bruno Latour argued.

In other words, every expression of creativity is linked to social, cultural and informational interactions. A work of art, a scientific discovery or any other product of invention is part of a broader context without which it could not have been created. The boundaries between art and science, for example, politics or the social situation, are thin because they influence and stimulate each other.

This perspective can also be used to understand the relationship between artificial systems and humans. This perspective doesn't need to look for a separated dualistic structure - human and technology, soul and body, knowledge and skill - but instead seeks to create systems and practices that will lead to a truly functional and creative collaboration. If we look at contemporary society, we can say that even 'simple things' like a computer mouse or a pen cannot realistically be created by one person, but always by a team in which there are different roles. For example, saying who created the Skoda Octavia or Google Docs is not good enough. This question, often associated with the school experience of dabbling with inventors and discoverers, no longer makes any sense today.

There are artefacts that humans create routinely - computer processors, mobile phones or operating systems - that are so complex that no one can understand them in detail. Working together is the only way to continue research, development, and innovation. A highly innovative person with creativity and a lot of experience is worthless in today's world of work if they can't work with others.

This cooperation is not just a question of a team of people but already has a broader perspective. In factories, we commonly see workers and robots working together, which may be skilled work but is not very creative. Programming, for example, offers a much more exciting model today. When we program something, we never start from scratch. We look for ways to use codes that someone else has already created, how to adapt them and put them together in the right way so that they do what they are supposed to do. The rate of creating entirely new algorithmic structures is relatively minimal (though essential). Whereas programmers used to focus on getting their "inspiration" from repositories and forums, today, much of the work is done by GitHub Copilot, which can write code based on what the user needs. It relies on data from GitHub repositories, the largest code repository ever. So, the programmer sets the direction for a particular problem, and Copilot does much of the routine work for him. The resulting work is thus the product of collaboration between the programmer and the AI.

The goals of the relationship between creativity and artificial intelligence should be - ideally - to seek forms of collaboration that enable results that would be difficult or impossible for one member of such a sociotechnical system to achieve.

Another example might be writing an essay on Murakami's novels, where the writer has the basic idea but may ask the expert system which book features the Sheep Man or the successful student who commits suicide. The author knows the books but may not see the plot's name or specific anchoring, which an AI system (such as Google Bard) can do. The next step is to have the text translated from English to English (DeepL) and proofread (Grammarly). The result is thus a highly creative product in which various AI systems have been involved at multiple stages.

If we look at the literature, we can say that the relationship between creativity and AI is unclear. However, it can still be linked to several principles or ideas that we will develop further:

• AI literacy is a prerequisite for developing creativity. It is not possible to pit technology and creativity against each other. One is impossible without the other. When you can be creative in working with AI, it is essential to understand it as much as possible and know its limits and possibilities. Many people perform unnecessary tasks simply because they cannot automate them.
• Creativity presupposes the presence of abstract synthesizing system models and the ability to think deeply and understand the world. Sound theoretical knowledge in specific disciplines is essential for creativity. Returning to the reflections of Giotto - without expertise, there is no creativity and (for some) paradoxically, theoretical knowledge and models are more valuable than practical skills, which can often be delegated to AI.
• Creativity about AI enables new problems and challenges that are future-oriented. Creativity is not divorced from the real world; ideally, we are looking for opportunities to use AI systems to solve problems in a real-world complexity. Humans are creative, where they see the interest and understand the social meaning of their behaviour.
• It is appropriate to think about the possibility of developing computational thinking, not just algorithmization and programming. Emphasis should be placed on general mental models and ways of solving problems. It is not necessary to learn to program but to think computationally - to analyse a problem, to complete it, not to be afraid to try different ways of solving it, to look for ready-made procedures, etc.