Who is the author when a machine creates a work of art?

Can an image created by Artificial Intelligence be considered a work of art? And if so, who should be recognized as its author?

These questions no longer belong only to technology laboratories and have become part of everyday life in the art world.

In recent years, generative Artificial Intelligence tools have started to produce increasingly sophisticated images. Using a few words, you can request a painting, an imaginary photograph, an illustration or a visual composition in different styles.

The ease of production, however, raised a series of issues that go far beyond technology.

One of the main discussions involves the data used to train the systems. Many models are developed from huge sets of digitally available images, texts and other information. This raised questions among artists who want to know whether their works were used in training in these technologies and under what conditions.

The problem is especially complex because Artificial Intelligence does not learn like a student who consciously observes a work. Its models identify statistical patterns present in the data used during training.

Even so, for many artists, a fundamental question remains: to what extent is it legitimate to use existing works to develop systems capable of generating new images?

There is also the problem of authorship.

When an artist writes a command to generate an image, chooses from dozens of results, modifies certain elements and finally uses that image in an exhibition, campaign or publication, human participation can be significant.

On the other hand, the greater the autonomy of the system in generating the result, the more difficult it becomes to define where the human contribution ends and the machine contribution begins.

This discussion could transform the very idea of authorship in the 21st century.

For centuries, the artist was seen as the one who controls the creative process from conception to execution of the work. With Artificial Intelligence, this model can be replaced by a more collaborative dynamic, in which the artist defines objectives, selects possibilities and interferes with the results produced by the algorithm.

There is yet another concern: access to technology.

Advanced Artificial Intelligence tools can expand the creation possibilities, but the development of these systems is concentrated in large technology companies. This means that a significant part of the new cultural production infrastructure is in the hands of private organizations.

The question, therefore, is not just whether Artificial Intelligence can produce art. It is also who controls the tools, data and platforms used to produce this art.

For artists, the challenge will be to learn how to use these technologies without losing the critical dimension of creation.

Artificial Intelligence can generate images in seconds, but it does not eliminate the need to choose, interpret, question and attribute meaning.

Perhaps the future of art will not be a competition between humans and machines. It could be a fight over the ability to decide how these machines will be used.

In this scenario, the artist will continue to play a fundamental role: not just producing images, but formulating questions about the world in which these images are created.