Creativity, AI art, and the impact on the diversity of cultural expressions.
What do we mean when we talk about being creative?
Prodigious people ruminate long and hard to solve the problems they have at hand. Ideas don’t leap from anywhere into consciousness. In 1908, there was a pioneering French mathematician, scientist, and philosopher, Henri Poincaré, who laid out how he came about discovering a new perspective of a mathematical problem that surrounded non-Euclidean geometry. His discovery was a major breakthrough in discovering a new class of mathematical functions. The interesting thing is that in his publication, he said that he wasn’t thinking about mathematics at all during that moment.
He shared that the key element to seeing the solution was unconscious thought.
But does this still apply in today’s complex world? Especially as we continue to integrate machines into our very own thinking process?
In a study published in 2016, computational scientist Anna Jordanous of Kent University in England and linguist Bill Keller of Sussex University analyzed 90 creativity-related papers over nearly six decades, searching for similar ways to describe creative processes across different fields. The result of that study was that that they landed on 14 combined components and emphasized that they don’t equal a definition of creativity, so much as elements of the process. The 14 building blocks can be assembled in different combinations or proportions depending on the creative activity demands, and the study doesn’t attempt to rank any component against another.
There is no doubt that today we are developing ever more sophisticated computers that can think. Will computers be able to be creative as well?
What do the experts currently developing AI have to say about computable creativity?
- Ian Goodfellow of Google, inventor of the groundbreaking generative adversarial network (GANs) — says: “machines are already creative.”
- Gerfried Stocker of Ars Electronica suggests that “we might need machines to create art as a way of communicating with them and understanding them.”
- Hod Lipson of Columbia University says that “the more intelligent Ai becomes, the more sophisticated its art will be.”
- Kevin Warwick, a renowned British engineer who studies cyborgs at Convetry University, says that “creativity in machines is there, whether we humans understand it or not. If we can figure out how memory works, then chips will go beyond memory and will improve our creativity enormously.”
- And lastly, Murray Shanahan of Imperial College in London, the technical adviser on the film Ex Machina states, “In principle, because the brain obeys the laws of physics, computers can do anything the brain can do.”
But how close is the human thought processes to the way computers work?
The brain uses chemicals to transmit information; the computer uses electricity. Even though electrical signals travel at high speeds in the nervous system, they travel even faster through a computer's wires. Here is a simple comparison of the similarities between a human neuron and an artificial neuron. They both process inputs and generate outputs (as processed information or actions).
It is much easier and faster for the brain to learn new things. Yet, the computer can do many complex tasks simultaneously (“multitasking”) that are difficult for the brain. We often use computer analogies to describe how the mind works, and computers are the reason why we have been able to advance our understanding of how the brain works. It’s a beautiful dance if you ask me.
Take a look at my ArtInUX colleague Viola Miebach’s article where she discusses if robots are here to replace us, the differences between automation and AI, and their impact on labour and inclusion.
Another way that creativity researchers work is to assume that the difference between creative and non-creative thinkers lies in their database of knowledge. Here is where it gets interesting. Creative thinkers build up their expertise by accumulating a vast amount of material; we have been building AI’s expertise by feeding it enormous sets of databases. They are also skilled at sifting through this material and using it to solve problems, just like AI scrutinizes all its inputs. We are never not thinking, just like AI is never not running.
In the scientific paper published by ScienceDirect, “On the development of evolutionary artificial artists”, scientist Penousal Machado introduced these five features that an Artificial Intelligence must possess to become an artist:
But what about the current bias we are embedding in the design of AI?
More than three-quarters of all new digital innovation and patents are produced by just 200 firms, the majority from the US and China. Take a look at my ArtInUX colleague Kristine Kalanina’s article to learn more about the paradigm of (un)ethical futures.
This means that developers mainly design AI tools for Western companies. In fact, these developers are overwhelmingly white men, who also account for the vast majority of authors on AI topics.
We all have a bias embedded in our human experience and it is a part of life. However, there are different degrees of bias — from the tendency to have preferences towards the familiar to the most potent behaviors of racism.
MIT Media Lab researcher, Joy Buolamwini, discovered that most facial-recognition software doesn’t accurately identify darker-skinned faces and the faces of women. In her movie “Coded bias” she investigates the widespread of bias in existing algorithms. As it turns out, AI is not neutral, and women are leading the charge to ensure our civil rights are protected.
Artificial intelligence is not only used as technical support but also to design new art forms. Generative algorithms have opened a new window for AI applications. Machine learning has traditionally been concerned with classifying/learning the behavior of a certain process without trying to mimic it, or more precisely, without generating a similar behavior. Machines are developing the capacity to create rather than just learn. And here’s where it gets interesting — what if we can teach machines to be creative?
Artificial intelligence works of art are a new artistic form of integration of contemporary art and technology; however, most recent artistic works of artificial intelligence have appeared in the art market to cater to Western audiences' curiosity.
How can we leverage AI to enrich cultural expression?
Creativity contributes to building open, inclusive, and pluralistic societies. Both heritage and creativity lay the foundations for vibrant, innovative, and prosperous knowledge societies.
According to UNESCO, cultural expression refers to: the manifold ways in which the cultures of groups and societies find expression. These expressions are passed on within and among groups and societies. Cultural diversity is made manifest not only through the varied ways in which the cultural heritage of humanity is expressed, augmented, and transmitted through the variety of cultural expressions but also through diverse modes of artistic creation, production, dissemination, distribution, and enjoyment, whatever the means and technologies used.
We all play a vital role in elevating the message of equality and racial justice, and in this article, I would like to highlight the exceptional work of Aishatu Gwadabe. She is a member of Black Women in AI that aims to educate, engage, embrace and empower black women in artificial intelligence. As a peace innovation technologist, she creates sustainable platforms for dialogue and conflict transformation. She examines digital ecosystems from a social justice and transdisciplinary postcolonial perspective bridging together emergent technologies, peacebuilding art, and design thinking.
Her practice is centered on a radical artistic methodology inspired by Africanfuturism 2.0, postcolonial philosophy, and artificial intelligence. Aishatu is a collaborator at the AI+Art platform, which is a collective of artists, social, and artificial intelligence scientists run by AI Impact Alliance. I had the honor to discuss some of her most recent artworks and better understand her intent when using AI as an artistic tool.
Aishatu’s willingness to explore uncharted territories of human-machine collaboration led her towards exploring the potential of artificial intelligence and machine learning to expand her creativity. She is developing a new language for making sense out of AI and technology through art.
In her own words: “The artworks examine identity, personhood, and my African cultural influences as well as intersections between design and technology focusing on opportunities to foster equity, combat domination and depict desirable counter-futures.”
What is Africanfuturism 2.0? She defines it as a way of constructing new worlds and realities that anticipate possible futures, coinciding with the present, and at times, reclaiming the past through a BIPOC lens.
“It is a move towards a pluriversal perspective of not only recovering the histories of counter-futures, but also critiquing Eurocentric narratives about cultural others, past, present, and future and, challenging their presumed authority to be the sole interpreters of BIPOC lives and futures.”
“My most recent work explores technogenesis of Black identity reflecting counter histories, hacking and appropriating the influence of artificial intelligence, enhancement and augmentation, posthuman possibility and the speculative sphere. They are creative experiments that explore machine learning techniques through illustrations, photographs, and paintings. I am particularly interested in advancing how we can imagine, design, and deploy technologies for a world that is more just, equitable, and secure for all.”
There is no doubt that art can be a force for social change, and its role has been long taken for granted. Her captivating art creates a bridge for those who may feel distant from these powerful messages. As we move forward with integrating machines into our very own thinking, we must prioritize building and protecting open, inclusive, and pluralistic societies and elevate the voices of artists like Aishatu Gwadabe.
