Can machines be artists?
By: Deborah M.
Tags: Art, Machine Learning, Artificial Intelligence, Technology, AI

Creators explore artificial intelligence’s potential to innovate.

F L O W by Karl Sims | MIT CSAIL

Pictures have been created with artificial intelligence programs that, even for experts in Baroque Art, are indistinguishable from an authentic Rembrandt. The Daddy’s car song has been composed, which sounds like the Beatles from the Revolver era. It is a matter of time before a compelling story or novel is written. And the debate is open on whether one-day writing decent poetry will ever be achieved. But what no artificial intelligence program has been able to do is break rules, create something new, and know that what it has created makes sense, which is precisely what Rembrandt, the Beatles, or Pollock did.

Thousands of people working in the emerging field of computational creativity aim to build programs capable of human-equivalent creativity. The historian Yuval Noah Harari predicts, in the best seller 21 lessons for the 21st century (2018), states that “in the long term, algorithms can learn to compose entire songs by playing with human emotions. (…) If the art is to inspire (or manipulate) emotions, few or no human musicians will be able to compete with such an algorithm ”. For Harari, “in the long run no job will be safe from automation; Even artists must be forewarned.”

The strong point

Deep learning systems create compelling works if they find recognizable patterns

Instead, astrophysicist Martin Rees predicts, in the no less recommendable On the future (Princeton University Press, 2018), that with automation “there will be an erosion of routine work […] and a revival of arts and crafts. We have seen famous chefs appear. There will be more possibilities for other arts and more respect for their most talented exponents ”.

For now, one of the most emblematic examples of computational creativity is The Next Rembrandt project, carried out between 2015 and 2016 on behalf of ING and with the support of Microsoft. An artificial intelligence program was instructed with multiple variables of Rembrandt’s paintings: colors in use, percentage of men and women, facial proportions, gaze directions, even paint thickness in the different areas of each painting … After the Learning, the program created its own Rembrandt, which was painted with a 3D printer and presented at the Cannes Lions International Festival of Creativity, where it was awarded.

The main limitation

Artificial intelligence programs are unable to create new styles because they do not know if what they are doing is right.

The key is that deep learning systems work as long as there are patterns to detect. The visual arts lend themselves especially to the identification of patterns, which is what allows us to recognize at first glance whether a painting is (or appears to be) a Rembrandt.

Music is also provided because all the components of rhythm, harmony, melody, and timbre can be mathematically described to feed algorithms. This is what allowed François Pachet to create the first songs entirely composed with AI when he worked at the Sony Computer Science Laboratory in Paris — in 2017 he joined Spotify. The best known of these songs is Daddy’s car, which imitates the style of the Beatles, although the expert fan will notice that it is a fake, because no trace of Lennon or McCartney can be recognized in the composition; It sounds vaguely Harrison, but it doesn’t sound convincing either.

Innovative in their way

Machines find ingenious solutions if they have clear instructions on what their objective is.

David Cope, with his project EMI (Experiments in Musical Intelligence), has created compositions that imitate the style of composers such as Bach, Mozart, or Vivaldi based on pattern recognition.

On the contrary, the literature resists artificial intelligence because all text is based on misunderstandings that escape programming. And within the literature, poetry is especially refractory because rhyme and rhythm can be imitated, but everything that appeals to the imagination is lost.

Still, the main limitation of creating pattern recognition is that it imitates, not innovates. Or, more exactly, it innovates in the artificial intelligence section, not in the artistic expression one. Rembrandt’s painting, despite being a technical milestone, does not contribute anything new to the painter’s work, since it is implicit in his previous work. Therefore, it is expendable. Nor does Daddy’s car add anything to the Beatles legacy or the EMI project to classical music.

Artwork created with artificial intelligence by graphic artist Karl Sims

To go a step beyond pattern recognition, graphic artist Karl Sims has chosen to generate random abstract images from mathematical formulas and ask viewers to evaluate them. This allows an artificial intelligence system to evolve the images according to the valuations expressed by the observers. Similar to a human artist, the system progresses in its creations.

But in this case, too, the process of creating the machine is not equivalent to that of a person. For an AI-based learning system to progress, we must be programmed with clear instructions on the goals to be achieved. In this way, it can evaluate the results and correct itself. It’s not that it can’t be creative, but it is functional goal-oriented creativity.

Good at painting and music

In visual and sound arts, artificial intelligence has achieved plausible aesthetic results

This is demonstrated by the example of AlphaGo, the artificial intelligence program developed by Google DeepMind to play Go. It demonstrated its talent by defeating Lee Sedol, the best human player in the world. Later AlphaGo was defeated by AlphaGo Zero, another deep learning program capable of even more ingenious plays. But for the programs applied to games, the objective is obvious. It is simply about winning games.

Google DeepMind — AlphaGo

For programs applied to artistic creation, the goal is more ethereal. With Karl Sims images, the feedback that tells the machine if it’s on the right track is based on audience behavior. Thus, what makes their creations progress is external evaluation, like that of the performer who plays to please, rather than an internal impulse, like that of the artist who innovates without making concessions.

Bad in literature

Experiences in narrative and poetry have so far been disappointing

The essential problem is that the artificial intelligence program is unable to validate by itself what it generates. Unlike Picasso or Miles Davis, who knew that their innovations were different from any previous work and that they were also transcendent, artificial intelligence has no way of knowing if their creations are breakthrough advances or irrelevant fortunes.

In the end, the answer to the question of whether machines can be artists depends on how each one defines art. If defined from the perspective of viewers, readers, or listeners, artificial intelligence can be artistic to the extent that it can generate emotions and aesthetic sensations.

We can not say that artificial intelligence is not creative. What happens is that it is not creative in the same way that a person is.

If defined from the perspective of creators who are on the frontier of innovation, experimenting with sounds, colors, words, and textures, and expanding the sensory and emotional heritage of humanity, artificial intelligence does not reach the category of artist. This just because it is unable to break the rules and create new styles.

Still, how many artists are capable of inventing new styles? And we do not say that the others are not creative, do we? Creativity is a matter of degree, of more or less. I would not say that artificial intelligence is not creative. What happens is that she is not creative in the same way that a person is. But it is not bad where it has reached so far.