1. The Intersection of Neuropsychology and the Metacrisis
In the expanse of neuropsychological research, few ideas resonate as profoundly with our contemporary challenges as those put forth by Ian McGilchrist [
1,
2,
3]. His exploration into the divided nature of the human brain presents an enlightening framework for understanding the intricate balance between different modes of thinking and perceiving the world. His discussion is based on the dichotomy between the left and right hemispheres of the human brain [
4,
5,
6]. He argues that each hemisphere processes information differently: the left is analytical, sequential, and focused on detail, while the right is holistic, intuitive, and concerned with the broader context. This bifurcation, according to McGilchrist, is not just a neurological fact but also a profound metaphor for the imbalances in contemporary society.
The term “metacrisis” refers to a multifaceted global crisis encompassing environmental, social, economic, and psychological dimensions. McGilchrist [
3] posits that the root of this crisis lies in the dominance of left-hemisphere thinking, which prioritizes technical rationality and narrow efficiency over the more integrative and empathetic approaches of the right hemisphere. This imbalance, he suggests, leads to a disconnection from the natural world, each other, and ultimately, from ourselves. Art and creativity are deeply intertwined with this neuropsychological perspective. They are quintessentially right-hemisphere activities that foster holistic understanding and emotional resonance. In the context of the metacrisis, art becomes not just a form of expression but a vital mode of reconnecting with the lost dimensions of experience. Creativity serves as a bridge, offering pathways out of the rigid frameworks imposed by an overly analytical mindset [
7,
8,
9].
The advent of Artificial Intelligence (AI) presents both challenges and opportunities in this landscape. On one hand, AI epitomizes the pinnacle of left-hemisphere dominance, with its emphasis on algorithms, patterns, and predictability. However, as AI evolves, there is a burgeoning interest in designing systems that can mimic right-hemisphere attributes such as intuition, empathy, and the ability to grasp the essence of complex, unstructured problems. The integration of AI into creative processes—whether in art, literature, or music—heralds a new era where technology and human insight converge. This synergy offers a glimpse into a future where AI aids in restoring balance, augmenting human creativity rather than supplanting it, and helping address the multifaceted challenges of the metacrisis.
This leads to a new phenomenon, which here shall be referred to as “AI artists” and its corresponding “AI artistry” and “AI art”.
2. The Dawn of AI Artistry: A New Horizon for Human Creativity
The landscape of art and creativity is undergoing a seismic shift, propelled by the evolution of AI. Today, we stand at the cusp of a new era where NLP (Natural Language Processing) and computer vision technologies are not just tools for enhancing art but are becoming capable of generating art independently. AI art is rising, with technologies enabling the automation of creative processes that were once solely the domain of humans. NLP and computer vision allow AI systems to understand and interpret text and images in ways that were unimaginable just a few years ago. This capability has paved the way for AI agents to not only enhance art created by humans but also to produce original works on their own. From composing music (e.g., Suno AI) to writing poetry (e.g., Gemini or GPT), painting (e.g., Midjourney or Dall-E 3), and videos (e.g., Sora), AI is stepping into roles traditionally held by human artists. This emergence of AI as ‘artists’ has sparked a debate, with some critics fearing that this signifies the beginning of the end for human creativity [
10,
11]. They argue that as AI becomes more capable of producing art, the unique value of human-made art could diminish, leading to a loss of human creativity. However, this perspective, while understandable, overlooks the broader implications and potential of AI in the art world.
The role of AI in creativity can also be read through the psychoanalytic lens of projective identification, where human anxieties about authorship and originality are displaced onto the machine. This aligns with Althusser’s [
12] notion of ideology as the ‘imaginary relation subjects hold with real modes of production’—a framework that helps explain both the utopian and dystopian narratives surrounding AI art.
I wish to argue that the fear of a loss in human creativity due to AI is misplaced. Human creativity is not a finite resource that can be depleted or replaced by machines. Instead, creativity is an inherent aspect of the human condition, continually evolving and manifesting in myriad forms. The introduction of AI into the realm of art does not constitute the end of human creativity but rather marks the beginning of a new chapter in which the boundaries of creativity may be expanded. The integration of AI into art should be seen as an extension of the tools at our disposal, much like the advent of photography, digital editing, and 3D printing in previous years. Each of these technological advancements was initially met with skepticism and fear, yet each has ultimately led to new forms of artistic expression and creativity. Similarly, AI has the potential to democratize art, making it more accessible to a wider range of people. With AI, individuals who may have previously felt excluded from the art world due to a lack of traditional skills or resources can now participate and express themselves in ways that were not possible before. Moreover, the collaboration between AI and humans can lead to the creation of novel forms. By combining human intuition, emotion, and subjective experience with the computational power, pattern recognition, and data processing capabilities of AI, new vistas of creative expression are opened up. This symbiosis can enhance human creativity, pushing the boundaries of what is possible and encouraging more people to engage in creative pursuits. The ‘old ways’ of doing art are thereby not being threatened, but new ones are being developed.
3. Shaping the Future of Creative Expression
In the midst of these developments, the study of Human-AI Interaction becomes more important. After all, emergent technologies have revolutionized the way we interact with machines, enabling AI to understand and generate human-like text, create compelling images, compose music, and even produce video content. As AI gets more equipped with capabilities, there is a visible shift towards multimodal AI, which is ‘conversant’ in more than text, music, or any other singular modality. The main modalities for the creative space to date are the following:
- Text (NLP): The journey began with text-based models. Over the years, from rule-based systems to machine learning and then to deep learning approaches, NLP has seen significant advancements. The development of models like GPT (Generative Pretrained Transformer) series has revolutionized text generation, enabling more coherent and contextually relevant outputs.
- Images (Computer Vision): Parallel to NLP, computer vision has made leaps with models that can now not only recognize but also generate images. The evolution from simple image classification to complex image generation techniques like GANs (Generative Adversarial Networks) has enabled AI to produce artwork that is increasingly difficult to distinguish from that created by humans.
- Music: AI’s foray into music generation began with basic MIDI sequences but has since evolved to more sophisticated models that can compose music in various styles and even mimic specific composers.
- Video: Video generation remains the most complex, combining elements of text, image, and sound. However, recent advancements are paving the way for AI to generate not just short clips but entire sequences that are coherent and visually appealing.
Recent years have seen a shift towards multimodal AI models that can operate across different media types. These models integrate the capabilities of NLP, computer vision, and other modalities, enabling them to understand and generate content that spans text, images, music, and video. This synthesis allows for a more integrated and seamless creative process, where AI can, for example, generate a piece of music based on a written description or create a video from a script. The implications of these advancements for art and creativity are profound. Artists and creatives now have at their disposal tools that can assist in generating new ideas, expanding their creative horizons, and even collaborating with AI to create novel works that were previously unimaginable. This democratizes art creation, making it more accessible to those without traditional artistic training and providing new avenues for expression and storytelling. Moreover, the ability to modify existing media with AI allows for a new level of creative editing and personalization. Artists can take existing pieces of music, artwork, or video and transform them into something uniquely their own, blending human creativity with AI’s computational power. Sometimes, this can also enable content creators that one would not have expected. This is the case, for example, with Google’s newest AI called
Notebook LM, which can create whole podcasts with a click—and it sounds very realistic.
As AI continues to evolve, the fusion of human and machine-based creativity will thusly become increasingly seamless. While there are concerns about originality and the potential for AI to overshadow human creativity, it is more constructive to view AI as a tool that can enhance and extend human creative capabilities rather than replace them. The rise of multimodal AI models signifies a shift towards a more integrated approach to art and creativity, where the boundaries between different media and modalities become increasingly blurred. This not only opens up new possibilities for creative expression but also challenges us to rethink our definitions of art, authorship, and creativity. As Jacques Rancière [
13] reminded us, the aesthetic regime of art is not merely about artistic styles but about how art is distributed and understood within a given social order. This aligns with the broader discourse on AI and creativity, where the question is not just what AI can create, but how its outputs are perceived and situated within contemporary aesthetic and political structures.
4. Conceptualizing Art and Creativity in the Age of AI
What do we mean by art? This question has puzzled philosophers, artists, and scholars for centuries. Art, in its broadest sense, is often seen as any activity or product created with intention and purpose, invoking an aesthetic experience or conveying an idea, emotion, or worldview. Theories and models about art vary widely, from Aristotle’s mimesis, representing the imitation of nature, to Kant’s notion of art as an end in itself, to Duchamp’s challenge of the art status quo with his ready-mades [
14,
15,
16]. In parallel, creativity has been a subject of intrigue and extensive study, particularly in psychology and cognitive science [
17]. Creativity is generally regarded as the ability to produce work that is both novel and appropriate in its context. Recent research in human creativity has explored various dimensions, including the cognitive processes behind creative thought, the influence of environment and culture, and the neurological underpinnings of the creative mind.
Models of creativity, such as the Four C model [
18], differentiate between mini-c (personal transformative creativity), little-c (everyday problem-solving and creative expression), Pro-C (expert level creativity), and Big-C (groundbreaking work in a field). These models suggest that creativity exists on a spectrum and is a feature not just of the extraordinary but of everyday human experience. So, how do art and creativity fit together? Art is often seen as the manifestation of creativity, the vehicle through which the abstract becomes tangible. While not all creative acts result in art, and not all art necessitates groundbreaking creativity, the two are inextricably linked. Creativity is the engine behind the evolution of artistic styles, movements, and mediums.
But how do these models relate to one another, and more importantly, how does AI interfere with these ideas? AI challenges traditional notions of art and creativity by introducing a non-human agent into the creative process. This has led to debates about whether AI can truly be creative or whether it merely simulates creativity based on patterns it has learned from vast datasets. The interference of AI in art and creativity is not a straightforward usurpation. Instead, AI acts as a catalyst, challenging humans to redefine what we consider art and what we consider creativity. If creativity is the ability to produce work that is both novel and appropriate, then AI has certainly demonstrated the capacity for novelty. However, the appropriateness, often governed by social and cultural contexts, remains a distinctly human judgment. Is it then possible to create AI art? I would argue yes, but with nuances. AI can generate art, but the intentionality, emotion, and context behind the art are derived from human input and interpretation. AI-generated art is more a collaboration between human and machine, with each bringing unique strengths to the process.
This leads us to the question: “Does AI interfere with our creativity?”. It could certainly do so, but only if we allow it to. Instead of viewing AI as a replacement for human creativity, it can be seen as a tool that enhances and extends our creative capabilities. AI can handle the labor-intensive or data-driven aspects of creativity, freeing humans to focus on the conceptual, contextual, and emotional elements of art-making. Isabelle Stengers [
19] argues that thinking in terms of possibility rather than inevitability allows us to reframe AI not as a deterministic force but as a contingent phenomenon that remains open to human intervention and negotiation. This perspective shifts the debate from whether AI will replace human creativity to how AI might be integrated into creative ecosystems in ways that enrich, rather than undermine, artistic practice.
In order to have a better understanding of these interactions, let us turn to theories of art and theories of creativity, which may help to make sense of how art and creativity come to arise—be it with or without new technologies.
4.1. Theories of Art
- 1.
-
Mimesis Theory: Traditionally attributed to Aristotle, the Mimesis Theory posits that art is essentially an imitation of life. It reflects the physical and the emotional world [20,21,22]. In the context of AI, this raises questions about whether AI-generated art can truly replicate the depth of human experience or if it merely reproduces the outward appearance of objects and emotions.
- 2.
-
Expression Theory: Championed by philosophers like Tolstoy and Croce, the Expression Theory suggests that art is a means of expressing the inner feelings and emotions of the artist [23,24]. The challenge with AI in this context is determining whether AI can possess ‘inner feelings’ or if it can only mimic the emotional expressions found in human-created works.
- 3.
-
Formalism: This theory emphasizes the form and visual elements of art, such as line, shape, color, and composition, rather than its content or context. Formalism suggests that the aesthetic value of art comes from its formal properties [25,26,27]. AI-generated art can align well with this theory, as AI can create compositions with intricate patterns and structures, potentially offering new forms that were not conceived by human artists.
- 4.
-
Institutional Theory: Proposed by George Dickie [28], this contemporary theory of art suggests that something is art if it is considered as such by the art world (institutions, galleries, critics, etc.). In the era of AI, this theory is particularly pertinent as it raises the question of whether AI-generated works can be recognized and legitimized by the art community.
4.2. Theories of Creativity
- 1.
-
The Four-C Model of Creativity: As seen above, this model helps in understanding the spectrum of creativity from personal to global impacts, which can be applied to evaluate AI’s creative contributions [18].
- 2.
-
Systems Model of Creativity: Proposed by Mihaly Csikszentmihalyi [29,30,31], this model suggests that creativity results from the interaction between a person, a domain, and a field. It implies that creativity is not just an individual phenomenon but a cultural one, defined by the social context and the existing body of work in a domain. The inclusion of AI in this system challenges traditional dynamics and necessitates a reevaluation of how creative contributions are judged and valued.
- 3.
-
Divergent Thinking Theory: Often associated with psychologist J.P. Guilford [32], divergent thinking refers to the ability to think in multiple directions and come up with various solutions to a problem. This theory is foundational in understanding human creativity, particularly in contrast to AI, which may approach problems from different, data-driven perspectives, thereby offering new insights and solutions.
- 4.
-
The Creative Process: Graham Wallas [33] outlined a four-stage process of creativity, which includes Preparation, Incubation, Illumination, and Verification. This process provides a framework for understanding how creative ideas develop and mature over time, from initial preparation to final execution. The application of AI in this process, especially in the incubation and illumination stages, can potentially accelerate and enhance the creative workflow.
Each of these theories offers a different lens through which to view the creation and appreciation of art and the nature of creativity itself. When considering AI’s role in these domains, these theories help us to critically assess the potential and limitations of AI in contributing to human culture and creativity. They also encourage ongoing dialogue about what constitutes art and creativity in a rapidly evolving technological landscape.
5. The Rise of “AI Artists” and the Future of Creativity
Through emerging technologies, we have witnessed an unprecedented rise in “AI Artists”—sophisticated AI agents capable of producing art and engaging in creative activities traditionally reserved for humans. But what exactly are AI agents, and how do they intersect with the realms of art and creativity?
AI agents are autonomous or semi-autonomous software entities that perform tasks on behalf of users or other programs. These tasks can range from simple data retrieval and processing to more complex activities such as learning, decision-making, and, notably, creating art. As AI agents become more advanced, they can adapt to new situations, generate novel responses, and even exhibit behaviors that mimic human creativity. The introduction of AI agents in art production marks a significant shift in how we perceive and create art. OpenAI’s Sora, a groundbreaking text-to-video model, exemplifies this shift. Sora can generate high-quality videos from textual prompts, translating written descriptions into vivid, dynamic visual narratives up to a minute long. This model represents a leap in AI’s ability to understand and simulate the physical world in motion, creating compelling characters and scenes that express vibrant emotions and adhere to the user’s prompts. As these agents become more autonomous, the distinction between tools and creators begins to blur. These agents are not just enhancing human art; they are creating independently, interpreting prompts, and making ‘creative’ decisions. This autonomy paves the way for AI to do more of the things we do, including those that require creativity. I term these creative AI agents “AI Artists” because they produce media that is not only innovative but also resonates with artistic and creative standards. The implications of this are profound, as it challenges our traditional notions of artistry and creativity. It suggests that creativity may not be an exclusively human trait but rather a more universal concept, accessible to any sufficiently sophisticated cognitive entity.
The rise of AI Artists has intriguing implications for the future of art and creativity. As these agents become increasingly capable, they could democratize art creation, allowing more people to express themselves creatively without needing traditional artistic skills. This could lead to an explosion of creative content and a broader understanding of what constitutes art. However, this future also raises questions. As AI starts to perform tasks traditionally associated with human creativity, what does this mean for human artists? Will AI complement or compete with them? As should be evident by now, I argue that rather than stifling human creativity, AI Artists can enhance it by removing limitations and opening new possibilities for collaboration between humans and machines.
6. AI Artists Entering the Mainstream: Prospects and Pitfalls
These AI-powered entities, capable of generating art and creative content upon human demand, are not just a futuristic concept but a new reality. There is no stopping the inevitable entrance of AI artists in the world of art and creativity. Therefore, there is no use in holding back and not accepting it, as refusing to engage with new technologies may be futile. It is, however, imperative to acknowledge the upsides and downsides these AI artists provide us with.
AI artists offer several benefits. They democratize creativity by making art accessible to everyone, regardless of traditional artistic skills. This inclusivity fosters a more diverse and creative community. Additionally, AI artists lead to innovation and diversity, generating novel styles and ideas that human artists might not envision, thus expanding artistic boundaries. Their speed and efficiency make them valuable in industries like advertising, filmmaking, and gaming, reducing costs and accelerating project timelines. AI also allows for personalized and customized content, catering to individual tastes, which enhances user engagement across media. Moreover, AI explores new artistic frontiers by combining techniques and styles that have never been considered, pushing the limits of artistic exploration.
However, AI artists also present several dangers. One concern is the potential loss of the human touch, which imbues art with emotion and personal experience, risking a devaluation of deeply personal artistic expression. Ethical and copyright concerns arise, as questions about originality and ownership of AI-generated art remain unresolved, along with the risk of plagiarism or misuse of copyrighted material. Plagiarizing is, in essence, the misuse of power structures based on authority and knowledge, and so Foucault’s [
34] concept of biopolitics can underscore how power structures influence not just governance but also creative expression. AI’s growing role in art production calls for scrutiny of how algorithmic structures mediate creativity, determining which artistic voices are amplified or marginalized in digital spaces. The economic impact on human artists is another challenge, as AI may disrupt the traditional art market, making it harder for human artists to compete. There’s also the threat of homogenization in art if AI relies on similar datasets, leading to a reduction in artistic variety. In media and politics, AI-generated content could be used for misinformation and propaganda, posing serious societal risks. Finally, AI may lack the cultural context needed to fully understand certain art forms, leading to work that is shallow and devoid of deeper meaning.
7. An Anthropological Perspective on Creativity, Power and Universality in the Age of AI
Creativity has always emerged within structured environments and was thereby shaped not only by individual expression but also by broader cultural, cognitive, and technological contexts. Whether in prehistoric cave paintings, classical sculpture, or digital art, artistic creation is embedded in the ways humans interact with their surroundings, organize knowledge, and generate meaning [
35]. AI-generated art, sometimes seen as a radical break from human creativity (as discussed above), can instead be understood as part of a long continuum of evolving artistic tools and cognitive patterns. By looking at both the structured nature of creativity and its potentially universal foundations, we can better understand the place of the new technology in the broader human artistic landscape [
36].
Michel Foucault [
34] explored how knowledge and practices (including artistic practices) developed within specific frameworks of structured organization. While his work is applied to political theory, his concept of
epistemes, which are the underlying systems that shape what is considered possible within a given time period, offers an intriguing way to understand AI-generated creativity. Art does not arise in a vacuum but is shaped by the available techniques, materials, and conceptual paradigms of its era. Today, AI models like DALL-E, Sora, ChatGPT and many more are not merely autonomous creators but tools embedded in a particular technological and cultural moment. This is true even for AI agents that are more automatic, but still employed by humans for specific reasons. Their outputs reflect the accumulated artistic knowledge of the datasets they are trained on, meaning that AI creativity is not “artificial” in the sense of being separate from human creativity but is rather a continuation of artistic traditions within new computational frameworks. At the same time, creativity is not purely historically contingent. It also emerges from deep-seated cognitive universals shared across human cultures. Scott Atran [
37] showed that humans instinctively structure knowledge in ways that transcend specific historical or cultural settings. He described how different societies categorize and conceptualize the natural world using similar mental structures, even if their specific myths, sciences, or artistic forms may vary. When applied to creativity, this suggests that certain fundamental patterns of artistic expression, like metaphor, rhythm, and narrative, are deeply ingrained in human cognition. AI-generated art is therefore not just an algorithmic manipulation of data but an interaction with these deep-seated cognitive tendencies. AI models trained on vast human datasets do not ‘invent’ new modes of perception from scratch. Rather, they recombine and refine patterns already present in human artistic traditions. This aligns with research showing that AI-generated music, poetry, and visual art tend to resonate with human audiences when they mirror existing aesthetic structures,
i.e., symmetry, harmony, or recognizable emotional cues [
38,
39,
40]. This raises important questions: Is AI discovering something fundamental about creativity, or is it simply reflecting back what humans already know? Rather than seeing AI as an independent creative force, we might better understand it as an
amplifier of human cognitive tendencies. Just as earlier artistic tools, ranging from the paintbrush to the camera, expanded what artists could create while still being grounded in human perception, AI represents a new phase in the evolution of creative assistance. However, unlike previous tools, AI does not merely extend the artist’s physical capabilities. It interacts with creative thought itself, offering new ways of structuring artistic expression based on the same cognitive foundations that have always shaped art.
This perspective moves the debate beyond concerns about whether AI threatens human creativity. Instead, it suggests that AI is most productively viewed as a collaborator, not a replacement. If creativity is fundamentally structured by cognitive universals, then AI is participating in (and not overriding) the same processes that have always driven artistic evolution. The challenge, then, is not whether AI will replace artists but how artists and thinkers will engage with AI to push the boundaries of creative possibility.
8. Conclusions: Human Creativity Will Persist
While AI can assist in the artistic process, the essence of art—a reflection of human thought, emotion, and experience—remains firmly anchored in human hands. No matter how advanced technology becomes, it cannot replace the unique personal insights and cultural narratives that only humans bring to art. Art is more than a collection of forms or patterns; it is a profound means of communication between the artist and the audience, a connection rooted in shared emotions and collective understanding. Even if AI can ‘create’ art, it is only art if, by the power of human imagination and attribution of meaning, people will perceive it as creative and artful. Otherwise, it will be nothing more than a machine output from a certain task. Human creativity is the driving force behind every piece of art. It is not just about innovation or aesthetics, but about conveying messages and emotions that resonate on personal and societal levels. The ascription of meaning and thus the ability to see beyond the surface and interpret art’s deeper messages is something uniquely human. While AI can generate content, it cannot replicate the intrinsic human touch that transforms these creations into art that truly communicates. The emotional depth, cultural awareness, and critical thinking that humans bring to art allow for the creation of works that provoke thought, evoke emotion, and inspire action. These are traits that AI, no matter how advanced, cannot incorporate.
In this age of AI, thus is the claim, human creativity is not diminished but augmented. AI tools provide new ways to experiment with forms, techniques, and styles, pushing artists into innovative territories they may not have otherwise explored. Yet, the soul of art, which are the original ideas, emotions, and stories that give art its meaning, remain exclusively human. The real challenge lies in using AI as a tool to complement, rather than replace, the depth and richness that come from human creativity. AI can offer new perspectives and solutions, but it cannot create the kind of personal, meaningful connections that arise from the human experience. Moreover, art has always been, at its core, a form of communication. It’s a dialogue between creator and observer, where the value of the message depends on shared human experiences. While AI can generate forms that may seem artistic, the story behind the work (the narrative that connects it to human emotion and thought) can only be crafted by human insight. The power of art to inspire, provoke, and challenge perceptions stems from this deep connection between artist and audience, a bond that machines are unable to take over.
The emerging phenomenon of AI artists ties directly into the broader conversation about the metacrisis and the divided nature of the human brain, as proposed by neuropsychologists like Ian McGilchrist [
3]. At the heart of the metacrisis is the imbalance between the left hemisphere’s dominance—focused on technical rationality, algorithms, and efficiency—and the right hemisphere’s integrative, empathetic, and holistic approach. AI, representing the pinnacle of left-brain dominance with its emphasis on logic and pattern recognition, poses both challenges and opportunities in art. However, as the previous discussion points out, AI does not replace the human soul of creativity, which thrives on emotion, intuition, and subjective experience, which are traits rooted in the right hemisphere. AI, when integrated thoughtfully, could serve as a tool to recalibrate this imbalance. By pushing the boundaries of creativity while still relying on human insight, AI can augment human creativity rather than diminish it, helping us navigate the metacrisis. Just as the brain must function as a unified whole, the integration of AI into the creative process offers an opportunity to restore harmony between analytical precision and holistic artistic expression, ultimately leading to a more balanced, enriched creative landscape.
As we move forward into this new era of AI-assisted art, it is significant to recognize that while the tools of creation may change, the essence of art remains the same. Human creativity continues to evolve and adapt, thriving even as technology reshapes the world around us. The marriage of AI and human ingenuity offers exciting possibilities, but at the heart of it all is the unchanging truth: the soul of art requires a human touch. In a landscape where AI may enhance our abilities, it is human creativity that defines the meaning and impact of art, ensuring that it remains a deeply personal and reflective endeavor. We have done so from the times of cave paintings and ancient theaters, all the way up to digital art, creative pictures from our phones, and 3D printed sculptures. And we will continue to do so after the adoption of Artificial Intelligence. There is no reason to fear, but every reason to embrace and utilize the dawn of AI artists.
Ethics Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Funding
This research received no external funding.
Declaration of Competing Interest
Apart from being an artist himself, the author has no conflicts to declare.
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