top of page

Could machines be creative?

Computational creativity is the use of artificial intelligence (AI) and computational algorithms to generate new ideas and produce creative work, such as art, music, writing, and design. It is an interdisciplinary field that combines elements of computer science, psychology, and the arts to explore the nature of creativity and how it can be replicated or enhanced by machines. Computational creativity can take many forms, from simple algorithms that randomly generate new images or sounds, to more complex models that can understand and replicate existing art styles or genres. One of the key techniques used in computational creativity is machine learning, which allows computers to learn from and make predictions based on large datasets of existing creative work.

Overall, it's the study of building software that exhibits behavior that would be deemed creative in humans. This subfield of Artificial Intelligence is aimed at understanding human creativity and producing programs for creative people to use, where the software acts as a creative collaborator rather than a mere tool. It has historically been difficult for society to accept machines that are intelligent and even harder to accept that they might be creative. There is still skepticism about software's creative potential, even within the field of Computer Science.

Creative software can be used for autonomous creative tasks, such as inventing mathematical theories, writing poems, painting pictures, and composing music. However, it's important to understand that creativity is not some mystical gift that is beyond scientific study but rather something that can be investigated, simulated, and harnessed for the good of society. Computational creativity as a discipline has come of age, maturity is evident in the amount of activity related to computational creativity in recent years; in the sophistication of the creative software we are building; in the cultural value of the artifacts being produced by our software.

One of the most interesting examples of computational creativity in visual arts is AARON, a robotic system developed by the artist and programmer Harold Cohen. AARON can pick up a paintbrush with its robotic arm and paint on canvas on its own. AARON’s knowledge and the way AARON uses its knowledge are not like the knowledge that we, humans, have and use because human knowledge is based on experiencing the world, and people experience the world with their bodies, their brains, and their reproductive systems, which computers do not have. AARON’s paintings have been exhibited in London’s Tate Modern and the San Francisco Museum of Modern Art.

Another very interesting example of computational creativity is Simon Colton’s Painting Fool, which is much more autonomous than AARON. The software simulates many styles digitally, from collage to paint strokes, and it runs its own web searches and crawls through social media websites.

Another area where computational creativity is being applied is in music and one of the most interesting results is the music style and harmony transfer, genre to genre, developed at the SONY Computer Science Lab in Paris. The system assists composers in harmonizing a music piece in a genre according to the style of another completely different genre. For instance harmonizing a jazz standard in the style of Mozart.

An important aspect of computational creativity is the democratization of creativity by means of assisting and augmenting human creativity. Douglas Engelbart wrote about a “writing machine that would permit you to use a new process of composing text” that would augment the collective intelligence and creativity of groups by improving collaboration and group problem-solving ability.

However, the increasing use of AI in the art industry does pose a challenge for human artists. Digital artists who choose not to use AI may be left behind, unable to keep up with the rapid iteration and lower costs of AI-enhanced artists. But the use of AI in the art industry also opens up new possibilities, such as AI-generated art being used as a starting point for human artists to improve upon, or AI being used to assist in the discovery of stolen art.

In conclusion, while AI has demonstrated an ability to be creative, the debate over whether it can truly be considered creative remains. Some argue that creativity is an inherently human trait and that machines can only mimic human creativity. Others argue that the process of creating art is not solely about the physical act of painting or drawing, but also about the ideas and concepts behind it. As AI continues to evolve, it will be interesting to see how it will impact the art industry and the role of human artists in the future.

Harold Cohen's art:

21 views0 comments

Recent Posts

See All


  • Instagram
bottom of page