Beyond The Brushstroke: Revisiting Creativity in the Age of Artificial Intelligence

Fulbright Chronicles, Volume 4, Number 1 (2025)

Author
Nina Maria Waals

Abstract
Emerging technologies, especially artificial intelligence (AI), transform conventional understandings of artistry and creativity. This article examines how AI-generated works challenge classical notions of authorship and property, reframing the role of human intent in the creative process. Educational and industry examples reveal the collaborative dynamics that enrich artistic endeavors, suggesting that AI can expand rather than diminish creative expression. Ultimately, broader questions about originality are raised, inviting a reassessment of art’s boundaries in the digital era.

Keywords
Artificial intelligence • Creativity • Authorship • Intellectual Property • Digital Transformation

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In a quiet, dignified room of the Rijksmuseum in Amsterdam, where the air is typically thick with the reverence for classical art, an unusual exhibit prompted a subtle yet profound disquiet among its viewers. This was the unveiling of the “Next Rembrandt,” a piece not crafted by human hands but calculated by the cold logic of artificial intelligence (AI). In 2016, a collaboration of technologists, historians, and artists set forth to merge the old with the futuristic, tasking themselves with creating a new work by Rembrandt, or rather, an echo of what his genius might have conceived were he alive today.

This painting, composed not from oil but from data, was algorithmically generated by analyzing the depths of Rembrandt’s technique, distilled from his life’s works. It presented a face that never was, yet unmistakably Rembrandtesque, challenging the observers to discern where the boundary lies between the artist’s impulse and the algorithm’s output. Here lay a canvas that was both a technical marvel and a cultural query, blurring the lines between man-made and machine-generated.

This moment of reveal was not just about the achievement of a technological feat; it was a deeper meditation on the essence of human creativity. It asked us whether there’s a soul in the symmetry and shades managed by algorithms. In a society increasingly comfortable with the digital, the “Next Rembrandt” forces us to pause and ponder. If art is a mirror to the human condition, what does it reflect about us when our creations are born from binary codes? This initiative is more than an artistic endeavor; it is a philosophical exploration of our age-old quest to understand what it means to create and what it means to be human in the era of AI.

Philosophical Underpinnings: Locke’s Labor Theory and AI

To appreciate the contours of the current debate on AI in art, it helps to revisit the thoughts of John Locke, a philosopher who shared the temporal stage with Rembrandt. Locke’s discourse on property and labor offers a classic, yet ever-pertinent framework to dissect the complexities presented by AI in the creative fields today. Locke posited in his Second Treatise of Government that personal ownership of property is justified through the application of labor. He argued that nature provides us with resources in common, but when an individual mixes their labor with those resources, be it tilling the land or carving a statue, those resources transform into their property.

This transformation is rooted in the expenditure of effort, which Locke viewed as a natural extension of the person themselves. Therefore, by mixing their labor with the world, individuals make a claim to ownership not just of the fruits of their labor but of a part of the world itself. The programmers and data scientists behind the “Next Rembrandt” project ventured into a realm where Locke’s theory intertwines intriguingly with modern digital creations. They invested intellectual labor, analyzing Rembrandt’s works, understanding his style, and translating these into algorithms that could replicate his art. If Locke were to ponder this scenario, he might consider whether these digital brushstrokes, borne from human intellect and executed by machines, constitute a new form of property. These creators did not paint, but they instructed the machine on how to do so; their intellectual efforts mixed with digital resources to create something novel and valuable. Locke’s theory, thus, not only remains relevant but becomes crucial in framing our understanding of property rights in the digital age, redefining what it means to ‘mix one’s labor’ with the materials at hand, even if those materials are as ethereal as data and code.

Distinguishing Art from Illustration: The Intent Approach

As we investigate further what can distinguish art, an integral distinction evolves between art and illustration. This nuanced perspective is insightfully broadened through the reflections of Helen Darby, a legal scholar whose expertise bridges technology, copyright law, and the arts. In a recent interview conducted with her, Darby explored how traditional concepts of authorship and moral rights are being reshaped by the advent of AI in creative fields. She eloquently underscores the significance of intent in distinguishing meaningful art from mere technical illustrations.

Picture this: a skilled artisan painstakingly replicating a renowned masterpiece, striving to mirror every brushstroke, hue, and detail. The result? Visually stunning, a perfect copy, evoking admiration from the untrained eye. But beneath this flawless facade lies a critical disparity. The forgery, despite its precision, lacks the soul of the original, the artist’s intent. Each stroke, each choice, infused with the artist’s vision and emotion, is absent in the imitation. Thus, while it might appear puzzling how visually identical images can be classified as art and illustration, this is not a new issue within the realm of AI-art; it is a concept as old as the art trade itself. Art, traditionally viewed through the prism of human creativity and intent, transcends mere aesthetic or functional values; it seeks to engage, provoke, and communicate. Illustration, while often skilled and functional, does not typically aspire to provoke thought or evoke deeper reflection in the same way.

This distinction becomes particularly pertinent when we consider works like the Next Rembrandt. This project, a fusion of data science and artistic legacy, challenges us to ask: Can a creation born from algorithms truly embody the intent traditionally reserved for human artists? The programmers and data scientists behind this AI endeavor did not merely feed data into a system; they engaged in a deeply creative act of teaching the machine the nuances of Rembrandt’s style. Their labor was not just technical but imbued with a specific intent: to resurrect Rembrandt’s artistic spirit in a new form. According to Locke, who placed great emphasis on the transformative power of labor and extending this through Darby’s insights into the importance of intent, such a project does more than create a mere digital output; it crafts a new artwork, rich with human creativity and intellectual engagement.

This exploration challenges us to reconsider our definitions of art in the digital era. When AI is directed by human intent, when it is programmed to go beyond functional outputs and to imbue its creations with meaning, depth, and context, it crosses from being a mere tool to becoming a medium for artistic expression. The intent with which these machines are programmed, to create, to emulate, to innovate, becomes pivotal in distinguishing between mere illustration and genuine art. Thus, as we contemplate the evolving intersection of technology and creativity, we find ourselves engaged in a broader dialogue about the essence of human expression. The intent approach invites us to reflect not only on the outputs of our technological tools but also on the human purposes that guide them. In this way, each piece of AI-generated art serves as a mirror, reflecting back at us not just an image but a story of intent, labor, and creativity that challenges our deepest convictions about what it means to create and appreciate art in the modern world.

The Director’s Canvas: AI and the Art of Creation

In the ongoing discourse surrounding the artistic validity of AI-generated works, skepticism often arises from the perception that these creations lack the personal touch, a soul behind the canvas, so to speak. However, to expand our understanding, consider the role of a film director, a figure universally acknowledged as an artist despite primarily working through the medium of instruction and collaboration. Quentin Tarantino, renowned for his distinctive cinematic style, provides a compelling parallel. Like a conductor of an orchestra, Tarantino doesn’t play every instrument; rather, he directs each component to harmonize into a cohesive, artistic expression. This analogy brings us closer to appreciating the role of AI in art. When a director like Tarantino assembles a film, he sets the scene, guides the actors, selects the shots, and shapes the narrative, much as the programmers of the “Next Rembrandt” guided the algorithms to paint in a certain style. Both the director and the AI programmers engage in a high form of artistry not through direct creation but through the orchestration of numerous elements towards a singular artistic vision. Yet, one might argue that Tarantino’s touch, his decisions, his style, and his vision, are palpable in every frame, something that may seem absent in a painting generated by AI.

However, this perspective may overlook the depth of human involvement in the creation of AI art. Programmers, like directors, imbue their creations with intent, style, and personal flair through the code they write and the models they build. They set the parameters within which the AI operates, much as a director controls the environment of a film set. In both cases, the art is not merely in the end product but in the vision and decision-making that lead to its creation. Recognizing this, we can see AI not just as a tool for generating art but as an extension of human creativity, reflecting the choices, style, and intentions of its human creators.

The Creative Dialogue: AI in Practice

The philosophical framework established by Locke’s labor theory and our understanding of directorial intent finds striking manifestation in contemporary educational and industrial settings. Here, the theoretical becomes tangible, as institutions and industries engage in what might be termed a “creative dialogue” with AI, each instance reinforcing our earlier observations about the nature of artistic labor and intent.

The examination of educational environments proves particularly crucial to our discussion, as it is within these spaces that future definitions of creativity and artistic intent are being shaped. Consider the Rhode Island School of Design’s integration of AI into its Master of Fine Arts program. In a thoughtful echo of Locke’s theory of labor mixing with resources, students engage in a fascinating dual process: they first “labor” to teach the AI their artistic preferences and stylistic inclinations, then engage in a second phase of creative labor as they refine and transform the AI’s output. This twofold application of creative intent mirrors our earlier discussion of the “Next Rembrandt” project, but in a more intimate, individual context. The students’ work becomes not merely about creating art but about developing a sophisticated understanding of their own artistic voice through its translation into algorithmic terms. Increasingly, other institutions follow similar paths. At the Berklee College of Music, for instance, students employ Google’s Magenta to co-compose pieces that merge traditional music theory with algorithmic suggestions, resulting in hybrid compositions that neither the human nor the AI could have envisioned alone. This collaborative dynamic showcases how AI can facilitate unexpected creative directions, reshaping artistic practices in real time.

This educational context is particularly significant because it represents the frontier where our theoretical framework meets practical application. As these students grapple with questions of authorship, intent, and creativity in their daily practice, they are actively shaping the future discourse around AI and art. Their experiences challenge and refine our understanding of what constitutes artistic labor in the digital age, providing a living laboratory for the philosophical questions we have explored. Moreover, their work demonstrates how the integration of AI into artistic education isn’t merely about learning new tools, but about developing a more nuanced understanding of creative intent itself, a key concept in our earlier discussion of what distinguishes art from illustration.

These real-world applications serve not merely as examples but as vital evidence supporting our theoretical framework. They demonstrate how the intersection of human intent and artificial intelligence creates not a diminishment of artistic labor, as some might fear, but rather a new form of creative engagement that Locke himself might have recognized as a legitimate form of property-generating labor. In each case, we see how the human element, the intent, the vision, the creative direction, remains paramount, while the AI serves as both medium and collaborator in the artistic process.

Nevertheless, these successes in education and industry raise a profound question: Are these AI-driven creations genuinely novel, or do they merely rearrange preexisting concepts in new forms? Such concerns about the boundaries of true innovation highlight the interplay between creativity and originality, how creative intent shapes the emergence of genuinely new ideas. If creativity is the capacity to generate fresh perspectives or transform existing elements in unexpected ways, then originality becomes the tangible evidence of that transformative spark. This tension naturally brings us to the next discussion, one that delves deeper into whether AI can originate truly new concepts. To address these concerns, we must explore the notion of originality.

The Illusion of Originality: AI and the Artistic Process

In her reflection on the Feist Publications vs. Rural Telephone Service case, Darby highlights a key lesson: substantial effort alone cannot guarantee copyright. The U.S. Supreme Court ruled that merely organizing phone numbers lacked the crucial element, originality, emphasizing the need for meaningful transformation. This principle resonates with current debates on AI-generated art: while AI often combines existing data, it can still create genuinely new works if guided by a transformative intent. Indeed, art’s history shows no creation emerges in a vacuum; Shakespeare adapted older plots, and modern filmmakers remix past influences. Likewise, AI can remix familiar elements into novel expressions, provided human authors imbue it with creative purpose. Dismissing these results as unoriginal may overlook how art evolves through reinterpretation. Instead, we might view AI as expanding the ways we conceive of originality, forging new possibilities in the continuum of artistic transformation.

Conclusion: Reframing Creativity in the Digital Age

As we conclude this exploration of AI and artistic creativity, it becomes clear that intent remains central, both for copyright considerations and for our evolving definitions of art. Rather than focusing solely on physical skill, we now recognize a deliberate artistic vision as the core of genuine creativity. In this view, AI functions not to replace the human artist but to broaden how intent is expressed, much like brushes and chisels did in earlier eras. Still, skepticism persists. Debates on what truly qualifies as art are as old as art itself. Today, these discussions often play out on digital platforms, where some see boundary-pushing works as genuine art and others dismiss them as gimmicks. Yet the subjectivity of art means it inevitably shifts with each new medium, AI included. By embracing AI as a legitimate creative tool, we expand our idea of what is possible and push the limits of human ingenuity. Just as previous generations challenged orthodox methods, we too can reconsider and reshape creativity and authorship in this new technological landscape.

Group picture at the Naval Academy Foreign Affairs Conference (NAFAC).

Biography

Nina Maria Waals is a Dutch researcher specializing in the intersection of technology and global constitutionalism. She studied at Columbia University from 2023 to 2024 as a Fulbright scholar. Currently, she is a PhD candidate at the University of Amsterdam, investigating how technological advancements influence constitutional frameworks worldwide. Her interdisciplinary background and international experience inform her unique perspective on the interplay between law, innovation, and governance, aiming to deepen our understanding of emerging technologies’ impact on democratic processes. She can be contacted at ninamaria.waals@fulbrightmail.org.