Elucidating the Continual Genesis of Artificial Creativity*

Examining artificial and human creativity: Comparing perspectives on the differences between AI and human creativity.
By Enrico Klos

In 1962, within the walls of Bell Labs in Murray Hill, New Jersey, an engineer by the name of A. Michael Noll manipulated a room sized IBM 7090 to print an abstract design on a sheet of paper. This simple arrangement of lines would later be regarded and called “Computer art” by artists, programmers and historians. Noll had been exploring the creative potential of machines hidden within machines by having them create randomized patterns. Since then, the topic of Artificial Creativity and the debate within it has continues to become more prevalent to this day.
The notion of creativity is a complex concept. In many cases creativity is defined as a characteristic that distinguishes us humans from the rest of the world. Artificial creativity has been a topic of much debate in the field of Artificial intelligence (AI), with experts like Arthur I. Miller's, Matthew Elton, Margaret Boden, and others each proposing different solutions.
As I begin this odyssey, my motivation and inspiration stems from the thought of AI encroaching and challenging my notions about the nature of creativity being a uniquely human trait. This journey aims to dive deep into the essence of what it means to be creative while assessing to which extend AI can mimic or potentially surpass human creativity capabilities.
With AI's steadily intertwining into our lives, the once clear distinctions between human and machine or “artificial” creativity have become increasingly blurred to me. This change in perspective

Unraveling Human and Artificial Creativity

Weaving the Tapestry of Human Ingenuity:

Our odyssey begins with the intricate concept of creativity, which will eventually lead us to the realm of understanding artificial creativity. In order to explore this topic further, it is essential to first establish what we mean by creativity. The definition of creativity is and has been extensively debated across various disciplines including the sciences, psychology, philosophy, and the arts. Generally, the definition of creativity includes a blend of emotional, cognitive and social processes. When asked how we would define creativity, we often first associate it with the arts, literature, and music, in which individuals “produce entities be they ideas, poems, paintings, pieces of music or whatever.”1
To better understand creativity, we must first distinguish between imagination and creativity. Imagination is the ability to form mental images or concepts, such as visualizing the journey of a character while reading a novel, or children building a makeshift fort out of pillows and blankets pretending to be knights defending their castle. The Oregon-based psychology professor Marjorie Taylor wonderfully describes this as “the capacity to mentally transcend time, place, and/or circumstance.”2 Creativity, on the other hand, builds upon imagination as a key component, but it extends beyond visualization. While these two concepts frequently or even typically go hand in hand, there are alternative methods to achieve creativity, with imagination perhaps being considered “the” primary cornerstone in this endeavor. Creativity involves drawing from existing knowledge and information, evaluating, and implementing novel ideas. Transforming imagined ideas involves taking something abstract created in the mind and creating something tangible with it that resonates with others and contributes to meaningful experiences, therefore being valuable.
Creativity requires and employs imagination, novelty, and the willingness to think outside the box. For that to happen you need to have the willingness to take risks and embrace uncertainty by expressing personal vision. Creativity can manifest itself in various forms and in numerous fields including the arts, science, technology, and business. It involves taking existing knowledge and information and recombining them in new and innovative ways, engaging in both divergent thinking (generating many different ideas) and convergent thinking (evaluating and refining ideas). Abstract thinking is an essential component to all of this. Creativity is something that is fluid and flows and should not be seen as a static and unchanging quality; rather, it requires the ability to look at things from new and unique ways.
To help illustrate what creativity is, I will use this example from the book Imagination and Creative Thinking (2022) by Amy Kind, philosophy professor at Claremont McKenna College. She introduces us to three different kinds of examples to which the notion of creativity applies:
“Inspiring Invitee.

A college is looking for an inspiring speaker to give their convocation address. Finally, the selection committee has decided to invite an individual known as Indigo who works in technology. ‘The students will learn so much from Indigo,’ the chair of the committee concludes. ‘He's so accomplished and such a creative person.’

Mathematical Musings.

In math class, Marisol is called to the board to demonstrate homework problem #5. She explains how she tackled the problem and what answer she got. After complimenting her, her teacher notes, ‘Interesting! You got the same answer that I did, but I have never seen anyone take that approach before. That's a very creative way to solve the problem.’

Computer Chess.

Camisha, an excellent chess player, is practicing by competing against her favorite computer opponent. The program works by brute force, first exploring the legally available moves in line with a preexisting algorithm that narrows down the possibilities and assigns them various weights, and then choosing the optimal result. At a certain point in the game, Camisha finds herself extremely surprised by the computer's move ‘What a creative choice!’ she thinks to herself, after working out why the move was advantageous for her computer opponent. ‘I never would have thought of doing that.’”3

Each of these examples presents us with a different view on creativity. In Inspiring Invitee what is described as creative is Indigo, this is what Amy Kind calls Person-creativity. In Mathematical Musings what is described as creative is mathematical reasoning, this is what Kind calls Process-creativity done by Marisol. While in the Computer Chess exemplar, what is being described is a creative chess move made by the computer, this is what Kind calls Product-creativity. 4
Although these three forms of creativity are undoubtedly interconnected, they do not always go hand in hand. It is possible to have one type of creativity without the other. For instance, the chess computer could make a creative move without utilizing a creative method. Furthermore, to better understand the different manifestations of creativity, it is helpful to distinguish each characteristic with the various levels of impact it has. The four-C model proposed by James C. Kaufman and Dr. Ronald Beghetto helps us better distinguish between those types of creativity.5 To help illustrate this I have written examples:

Personal Creativity

This is the lowest level of creativity, where individuals use their existing knowledge and skills to create something new for themselves, this could be completely for themselves never sharing it with others. For example, an individual might create a drawing, draft a story, or experiment and create new recipes for their own enjoyment.

Professional Creativity

This level of creativity involves creating something new that is useful or valuable to others within a particular profession or industry. Professional creatives often work in fields such as design, marketing, advertising, or technology, and their innovations are intended to solve specific problems or meet the needs of their clients or customers.

Genius Creativity

This level of creativity, something truly innovative that has a significant impact on a particular field or industry. It involves developing new concepts, theories, or products that disrupt the status quo and lead to significant advancements. Examples of paradigm-shifting creatives include the invention of Light, the creation of the Internet and the first iPhone.

Eminent Creativity:

This is the highest level of creativity which involves creating something that has an enormous impact on society or even the entire world. It involves producing works of art, music, literature, or other groundbreaking accomplishments that change the way we see the world. Examples of eminent creativity include the development of the Internet, and the invention of Light bulbs.

These Four levels of creativity personal, professional and paradigm-shifting, serve as a valuable framework for understanding the way in which creativity manifests and impacts our lives. Each level serves a purpose. As we journey into the vast realm of artificial creativity, we must establish that the concept of creativity is so vast that there is no one definition that applies across all fields of study and the concept remains to be debated. Furthermore, it is influenced by a range of factors including culture, context and personal values and beliefs.
To help illustrate this I will give a few short examples. For culture, a fitting example of creativity is something like humor. Social and historical context impacts whether it will be considered funny or not. Furthermore, in a similar fashion personal values and beliefs highly influence this. Another good example of culture, context, values and beliefs influencing the concept of creativity is if we start to compare creativity within the arts to creativity within business. While in the arts creativity is seen as breaking conventions and rules, in business it is more about solutions and problem solving in a practical way.
My motivation behind exploring the concept of artificial creativities stems from the rapid advancement of artificial intelligence and its growing influence on various aspects of human life. As the topic becomes more relevant to artists, designers, educators, businesses and for society as a whole, I believe it is a good idea to gain insight into the potential and limitations of this technology so that we can see where it currently stands and what that means for us as creative creatures.

Crafting the Symphony of Synthetic Ingenuity

Having established the nuances of human creativity, we now venture into the realm of artificial creativity. Artificial Creativity is part of the field of artificial intelligence. Artificial creativity refers to a technology that simulates the creative process to generate new and original ideas, designs and works of art. A good example of this is the famous Portrait of Edmond de Belamy that sold for $432.500 at an auction.6 Another good example of artificial creativity is “AI dungeon” that uses GPT-3 to create interactive stories based on the player's input.7 Another good example we have previously quickly touched upon is chess engines like Stockfish 15.1.8 All of which have been deeply explored and studied for hundreds of years by humans.
The engine learns through continuously playing itself, leading to the development of unique playing styles and innovative moves that even the best players in the game would not have considered. Grandmaster Hikaru Nakamura, the five-time U.S. Chess Champion, and the reigning World Fischer Random Chess Champion, often mentions on his YouTube channel “GMHikaru” While playing against AI or while analyzing AI-played games, some moves are highly unorthodox and would never have been played by a human.9
While examining the different forms of creativity, we have discovered that creativity can manifest in several ways, such as process creativity, personal creativity, and product creativity. Chess is an example of product creativity because its focus lies with the output of valuable chess moves and strategies. However, it does not contain process creativity. This is because AI’s creative process is fundamentally different from human creativity. Unlike humans, who rely on experiences, cognitive processes, and imagination, essential for process creativity, chess AI depends on algorithms, machine learning techniques, and databases. It cannot apply knowledge beyond the information previously provided.
In contrast, we see that technology can function as a catalyst for creativity by providing a variety of tools that enable individuals to express themselves in more flexible ways. For instance, Digital art software, music composition programs, and 3D modeling tools have all revolutionized the landscape in which artists, musicians, and designers work.


This complementary relationship between technology and human creativity is explored by emeritus professor of history and philosophy of science, Arthur I. Miller's. His book The Artist in the Machine (2019) delves into the historical development of computer-generated art.10 Miller is fascinated by the potential of AI in cultivating artificial creativity. He defines creativity as "the production of new knowledge from already existing knowledge".11 Miller argues that AI can be creative in an equivalent way that humans are creative.
One of Miller's primary arguments for supporting artificial creativity is his claim that creativity is a process, and not an exclusively a human trait. Miller suggests that by understanding and modeling the cognitive processes behind human creativity, such as recognizing patterns, making connections between seemingly unrelated concepts, and generating new and original ideas, we can create AI systems capable of emulating human creativity. He also highlights that creativity is often a collaborative process. AI systems can engage in this collaboration, learning from humans and other AI systems to generate innovative ideas and creative solutions.
However, Miller mentions that it comes with challenges, especially incorporating emotion and imagination into AI systems. He remains optimistic that advancements in AI technology and a deeper understanding of human cognitive processes will eventually enable the development of artificially creative systems that can exhibit emotional and imaginative qualities, like humans.
By understanding and recreating the essence of human creativity, which encompasses all the qualities needed for true creativity. Miller believes we can unlock a whole new realm of artistic expression, one that is innovative, deeply human, and powered by artificial intelligence.

philosopher and writer Matthew Elton's concept of "enculturing" computers written in his text Artificial Creativity: Enculturing Computers (1995) aligns with Miller's way of thinking about artificial creativity. In Elton's "enculturation" process, machines are imbued with the cultural context and knowledge that humans use to generate creative ideas. By exposing AI systems to various cultural artifacts, such as literature, art, and music, these systems can acquire a deeper understanding of human culture, allowing them to simulate more human-like creative ideas.12
Elton's idea of “enculturation” supports the concept of artificial creativity in several ways. By helping machines better understand human culture, AI systems could develop richer imaginative capabilities enabling them to generate more creative ideas that connect better with human experiences and emotions. Moreover, machines could learn from human creativity by analyzing creative works made by humans and learn the patterns, styles, and techniques used within them, which could then be applied to their own creations.

Wayne McGregor's “Living Archive" Is an excellent example of how Elton's concept of "enculturation" can enhance the creative capabilities of AI systems. This collaborative experiment between Studio Wayne McGregor and Google Arts and Culture Lab to develop an AI system that could generate choreography based on Wayne's 25-year archive of contemporary dance. By analyzing thousands of hours of his videos, the AI learned from subtle nuances to intricate progressions asking the question of what choreography is? Who has to make choreography? and what is the potentials of choreography?”13
Eltons believes that AI systems could learn imagination and abstract thinking by learning across different creative domains. Exposure to various forms of art, literature, and music, AI systems can develop the ability to draw inspiration from one domain and apply it to another, thus promoting imaginative and abstract thinking. He emphasizes the importance of adaptability and flexibility for machines to develop imagination and abstract thinking. As AI systems become more advanced, they should be able to adjust their thought processes based on the context and the problem at hand, allowing them to approach problems from different angles and generate imaginative solutions.

Lastly, I would like to introduce German computer scientist Jürgen Schmidhuber. Schmidhuber's "Formal Theory of Creativity" points out the importance of curiosity and intrinsic motivation in developing creativity14. He proposes that AI systems can be designed to include an intrinsic motivation to seek novelty, leading to the generation of creative ideas. The two biggest arguments Schmidhuber has are intrinsic motivation and Autonomous learning
Schmidhuber argues that AI systems be equipped with an intrinsic motivation mechanism, encouraging them to explore and discover new patterns, ideas, and strategies. This would allow AI systems to actively seek novelty and be rewarded for creative discoveries.15
Schmidhuber's emphasizes the importance of autonomous learning in AI systems. By allowing AI systems to learn and adapt without explicit human guidance, Schmidhuber believes they can achieve higher levels of creativity and innovation.16 A fitting example of this is the “AICAN project” which demonstrates the power of AI systems in autonomously generating creative works by emphasizing the importance of self-learning and adaptation. AICAN generates original artwork by learning from a large dataset of historical art pieces and autonomously creates new pieces without explicit human guidance and therefore not following predetermined rules or algorithms.17


However, Margaret Boden views on artificial creativity differ, she argues that true creativity is a distinctly human attribute that cannot be replicated or mimicked by machines or AI. According to Boden the definition of creativity is the ability to produce ideas or artefacts that are new, surprising, and valuable or artifacts that are grounded in everyday human abilities like conceptual thinking, perception, memory, and reflective self-criticism.
Every one of us is creative, to a degree. In the book The Creative Mind: Myths and Mechanisms (1990) she analyses the concept of creativity by exploring various theories. She argues that “true” creativity requires an understanding of the problem. Artificial intelligence systems can produce new ideas, but they lack the deep understanding needed to solve the essence of the problem.18 Furthermore, they lack the ability to understand or appreciate the cultural and emotional significance of creative works that make them meaningful. This, she argues, is at the root of human creativity.19
Moreover, Boden argues that true creativity cannot adapt based on contexts, to change one's approach to a problem based on new information, and to improvise when necessary. These abilities are grounded in human experience and are difficult, if not impossible, to replicate in machines. She notes that while AI systems can produce new ideas, they lack the ability to transcend the given rules and constraints. Furthermore, they also lack intuition, flexibility, imagination, consciousness and intentionality.
An example I personally would like to use is music. A recent study published in the journal Frontiers in Digital Humanities written by Nicholas Novelli and Shannon Proksch compared human generated music to AI generated music. The study found that while AI generated music may have some novel elements, it lacked the complexity and richness of human generated music. Human generated music was more emotionally expressive and reflected the cultural and historical context in which it was created.20 Ballade No.1 in G Minor, OP. 23 is an example I would like to use as it is renowned for its emotional depth, cultural significance, and technical complexity. While AI generated music may produce novel melodies and harmonies it would be lacking the emotional depth and life experience needed to portray those emotions. it is unable to replicate the intentional choices behind the selected notes and their contextual meanings that are inherent in human-generated music. resulting in a more formulaic and mechanical sound.

Philosopher Hubert Dreyfus, in his book What Computers Can't Do (1972), continues the argument that AI cannot replicate human creativity due to the inability of machines to possess what he calls "worldliness." Dreyfus suggests that human beings have a background of understanding that allows us to understand the context and meaning of things in the world, which is something that cannot be programmed into machines. 21
Dreyfus argues that AI is based on the assumption that the world is a closed system that can be fully represented by a set of rules and mathematical models. However, he believes that human experience and knowledge cannot be reduced to a set of rules, human creativity is rooted in physical experiences throughout life and our interaction with the world. And even the most advanced AI systems could not capture the richness and complexity of human experience. We possess a type of intuition, improvisation and capacity to transcend the rules and norms that allows us to understand things beyond what can be explicitly represented. This allows us to come up with solutions that are not simply the result of following a set of rules or procedures.


Now that we are almost reaching the end of our odyssey, I have to be honest with all of you. You might have been wondering throughout this essay, what is going on with this abstract and very cryptic title, headings, and subheadings throughout this text? All of these have been generated by AI. I asked the AI to create a creative title for the representative part of the text I used it for. The second thing I must mention is that the concept of artificial creativity still feels slightly ambiguous to me even after exploring it more Indepth. While AI systems can certainly simulate aspects of human creativity, I remain convinced that creativity in its complete concept remains a uniquely human trait. It is not just about producing innovative ideas or making creative decisions based on data analysis. True creativity involves a plethora of intertwined traits like imagination, abstraction, cultural values, complexity, intuition and combining seemingly unrelated concepts but also to truly be considered creative from my perspective.
We circle back to the definition of creativity is, in which we defined with the help of existing theory that creativity has three forms and that they are intertwined; they do not always go hand in hand. It is possible to have one type without the other. For instance, the chess computer could make a creative move without utilizing a creative method. However, it is only part of what the concept of creativity really means. Creativity is a complex trait. AI systems may excel in product-creativity and could even be considered to contain part of process creative as AI is capable of employing cognitive processes to generate creative outputs, such as machine learning, deep learning, and neural networks. These processes allow AI to be considered process creative. However, process-creativity also includes Serendipity, Analogical reasoning, and Emotional intelligence which they do not contain. Furthermore, AI can’t be considered to have personal creativity. Personal creativity is defined by the fact that the creative work expresses something personal about the creator. Therefore, personal creativity is rooted in the unique experiences, emotions, and perspectives of the individual creator.
While Elton and Schmidhuber's ideas about "enculturing" and intrinsic motivation would certainly help AI systems develop more advanced creative capabilities, it is still only simulating traits that are considered to be part of creativity. In my opinion it is very unlikely that AI will ever fully replicate human creativity, especially considering the vast amount and difficulty of traits that we have encountered throughout this journey.
Boden's theories provide an approach that perhaps aligns more with me. Specifically, her argument for transcending the given rules and constraints is an extraordinarily convincing argument for me. Additionally, the importance of personal firsthand experiences and individuality in creative expression highlights that you can’t oversimplify approaches to artificial creativity. Philosopher Dreyfus puts even more emphasis on individuality showing us that human creativity is deeply rooted in physical experiences throughout life and our interaction with the world. And I believe those parts are something that cannot be simulated or artificially mimicked. Perhaps in the future AI can come really close to mimicking human creativity, but as of right now I am not convinced.

* All the titles, headers and sub headers have been generated by openAI’s CHATGPT. I asked the AI to generate creative title while giving it the text it was supposed to represent.
1. Elton, Matthew. "Artificial creativity: Enculturing computers." Leonardo 28, no. 3 (1995). p208
2. Taylor, Marjorie, ed. The Oxford handbook of the development of imagination. Oxford University Press, (2013).
3. Kind, Amy. imagination and Creative Thinking. Cambridge University Press, (2022). P20.
4. Kind, Amy. imagination and Creative Thinking. Cambridge University Press, (2022). p20-21.
5. Kaufman, James C., and Ronald A. Beghetto. "Beyond big and little: The Four-C model of creativity." Review of general psychology 13, no. 1 (2009): 1-12.
6. Arts-collective Obvious, Portrait of Edmond de Belamy, (2018), Paris. (https://time.com/5435683/artificial-intelligence-painting-christies)
7. Walton, Nick. “AI Dungeon” (2019), is a text-based adventure game that that you can play on a website online or on your mobile phone. It uses GPT-3 to generate interactive stories based on the player's input.
8. Romstad, Tord. “Stockfish” (2018), (https://stockfishchess.org), Stockfish is an AI engine that uses deep neural networks and reinforcement learning to learn and play chess.
9. Nakamura, Hikaru. “GMHikaru” (2018), (https://www.youtube.com/c/GMHikaru/videos,) To show the staggering difference between humans and Chess AI I will use the number one chess player and world champion since 2013 Magnus Carlsen who at his peak had a rating of 2882 Elo,ii which is the highest rating in recorded human history. As of April 8th, 2023, the Highest rated Chess AI is named Stockfish with a rating of 3535 Elo, a staggering difference in comparison.
10. Miller, Arthur I. “The artist in the machine: The world of AI-powered creativity.” Mit Press, (2019).
11. Pepi, Mike. “Critical Winter.” Art in America 108 (4), (2020). p26–29
12. Elton, Matthew. "Artificial creativity: Enculturing computers." Leonardo 28, no. 3 (1995): p207-208.
13. McGregor, Wayne. "Living Archive” (2019), (https://aiartists.org/wayne-mcgregor)
14. Schmidhuber, Jürgen. "A formal theory of creativity to model the creation of art." Computers and creativity (2012): 323-337.
15. Schmidhuber, Jürgen. "A formal theory of creativity to model the creation of art." Computers and creativity (2012): 323-337.

16. Schmidhuber, Jürgen. "A formal theory of creativity to model the creation of art." Computers and creativity (2012): 323-337.
17. Elgammal, Ahmed. "AICAN,” (2018), Rutgers University Art & AI Lab, (https://theconversation.com/meet-aican-a-machine-that-operates-as-an-autonomous-artist-104381)
18. Margaret Boden - The Creative Mind: Myths and Mechanisms. (1990). p23
19. Margaret Boden - The Creative Mind: Myths and Mechanisms. (1990). P35
20. Novelli, Nicholas & Proksch, Shannon. Am I (Deep) Blue? Music-Making AI and Emotional Awareness, (2022) (https://www.frontiersin.org/articles/10.3389/fnbot.2022.897110/full)
21. Hubert Dreyfus, What Computers Can’t Do (1972). p211

1. Margaret Boden - Creativity In a nutshell (2004)
2. Margaret Boden - The Creative Mind: Myths and Mechanisms. (1990).
3. Linda Candy - Creativity and cognition, Leonardo MIT Press (2002)
4. Hubert Dreyfus, What Computers Can’t Do (1972)
5. Ahmed Elgammal, Rudgers University - Artist, Artificial Intelligence and Machine-based Creativity in playform (2020)
6. Kaufman, James C., and Ronald A. Beghetto. "Beyond big and little: The four-c model of creativity." Review of general psychology 13, no. 1 (2009)
7. Matthew Elthon - Artificial Creativity: Encultering Computers, Leonardo MIT Press (1995)
8. Liana Gabora - Psychology of Creativity (2013)
9. Amy Kind - imagination and Creative Thinking (2022)
10. Arthur I. Miller - A.I. The Artist in the Machine: The World of AI-Powered Creativity, The MIT Press. (2019)
11. Mike Pepe - Art in America, critical winter (2020)
12. Jürgen Schmidhuber - A Formal Theory of Creativity to Model the Creation of Art. In Computational Creativity: The Philosophy and Engineering of Autonomously Creative Systems (2012)
13. Marjorie Taylor - The Oxford Handbook of the Development of Imagination (2013)
14. Chin Chin Yap - Robocomposing (2023)
15. Novelli, Nicholas & Proksch, Shannon. Am I (Deep) Blue? Music-Making AI and Emotional Awareness

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