Investigative Field Essay

Keith Williams 

Jade Jemeson

October 4th 2025

In 2022, an AI-generated painting titled Theâtre D’opéra Spatial won first place at the Colorado State Fair’s digital art competition. Created using the AI image-generation platform Midjourney, which uses an algorithm to source inspiration from different artists, ultimately creating “new” artwork. Artists and critics expressed frustration, and even outrage, at the idea of a machine, devoid of human emotion or connection. The controversy revealed a growing tension between traditional notions of artistic creativity and the emerging capabilities of artificial intelligence. As machines become increasingly adept at producing images, music, poetry, and other creative content, society is forced to re-evaluate core concepts like authorships , authenticity, and creative value. 

This essay explores the philosophical, technical, legal, and cultural dimensions of this debate, arguing that while AI-generated art does indeed show remarkable computational power, it lacks human essence that gives art meaning. Art is not just about aesthetics it’s about lived experiences, culture, and emotion. As AI’s presence in creative fields grows, we must confront not only how we define creativity, but also how to ethically and legally protect human creators in a rapidly shifting artistic landscape. 

AI Art should not be hailed for its aesthetics, its mimicry without soul

For centuries, creativity has been seen as a uniquely human trait, rooted in memory, emotion, and our imaginations. Whether expressed through paint, words, or melody, art has traditionally served as a window into our human connection. As one critic put it, “Art is not just what is made–it is what is felt” (The Guardian, 2025). This rooted, emotional core gives art its authenticity and value, elevating it beyond visual appeal or technical execution. 

AI, however, does not have the capacity to feel. It cannot love, mourn, rebel, or dream. Its “creativity” is not born from experience but from computation. Models like Creative Adversarial Networks (CANs), developed by images through slight deviations from stylistic norms. These deviations may appear novel, but they lack intention. As Elgammal notes, “CANS can autonomously produce novel visual forms…but creativity is a learned deviation, not an intentional act.” AI does not know why it creates, it is just given simple commands to create art.

This lack of consciousness marks a fundamental break from traditional ideas and authorship. In human art, the creator’s identity, history, and purpose matter deeply. A painting by Frida Kahlo is inseparable from her physical suffering and political identity. A blues song gains power from the lyrics embedded in its voice. In contrast, an Ai-generated image may replicate such styles but does so without insight, emotion, or stake. Critics argue that this undermines not just the artwork’s meaning, but the very definition of art itself (McCormack et al.,2019).

Authorship and Ownership in the age of algorithms 

AI-generated art also complicates traditional ideas of authorship and ownership. Who is the artist when the machine creates an image? The user who types in the prompt, the engineer who wrote the model’s code, or the model itself? 

Current U.S. copyright law provides a clear answer. In 2023, the U.S. The Copyright Office ruled that AI-generated works are not eligible for protection unless a human has made significant contribution (Abramovitch et al., 2023). While this offers temporary safeguard for human artists, it also reveals the legal ambiguity surrounding AI-generated content. Who gets credit, and more importantly, who gets paid? 

The question becomes even more fraught when considering how AI systems are trained. Many image generation models are built on massive datasets scraped from the internet, often without the knowledge or consent of the original artists. This practice raises serious concerns about intellectual property theft, especially when AI replaces distinctive styles. As abramovitch et al warns, “Without legal reform, artists face exploitation as AI models absorb and replicate their styles without credit or compensation.” This exploitation isn’t theoretical, it’s actually happening as corporations increasingly use AI tools to bypass hiring designers or commissioning specialized work. 

This commodification of creativity poses an existential threat to working artists. When their labor is replaced by algorithms trained on their own work, artists are not just losing income, they’re losing control over their identity and legacy.

AI as a Tool v. AI as a Creator: A false equivalence? 

Some defenders of AI generated art argue that these tools are no different from past technological shifts. When photography was introduced in the 19th century, it was dismissed as mechanical and non-artistic. Yet today, photography is recognized as a powerful artistic medium. Likewise, digital painting and graphic design were once controversial but are now integral to modern visual culture. 

From this perspective, AI is simply the next tool in the artist’s kit, capable of helping creators break through creative blocks, explore new styles, and work more efficiently. As The Bulletin (2022) notes “AI may not destroy art–but change how we define it.” Indeed, many artists are already using AI collaboratively, treating it as a co-creator rather than a competitor. 

This analogy has limits however, a camera does not compose an image without a human behind the lens. An electronic stylus does not draw unless guided by a hand. These are tools, dependent on human operation, decision making, and emotion. By contrast, AI systems like midjourney or DALL-E can produce thousands of images from a few typed prompts, with no human involvement beyond the initial input. This capacity to generate  complete works independently is unprecedented. 

As McCormack et al. (2019) argue, tools require intent; AI, however, removes intent from the process entirely. This not only blurs the boundaries of authorship but also displaces the artist’s agency. It is not the tool that is changing, it is the very definition of what it means to truly make art. 

Legal Gray Areas and the Call for Recognition 

The rapid development of AI tools has outpaced legal and ethical frameworks. As it stands, much of AI-generated content operates in the legal gray zone, unregulated, uncredited, and unprotected. This great lack of clarity has allowed big tech giants, such as OpenAI or google, to profit from the creative labor of human artists without fair compensation or consent. 

Legal scholars and industry experts have begun sounding the alarm. For instance, Gangu (2018) compares the unchecked rise of AI to a natural disaster, capable of causing widespread disruption if not carefully managed. His warning applies especially to the arts, where the erosion of copyright protections and attribution standards could devastate creative industries.

Abramovitch et al. (2023) call for a legal framework that both encourages innovation and protects human creators. This includes clearer guidelines for fair use use in training data, attribution requirements, and compensation models when AI-generated content draws heavily from existing artistic styles.

Without such safeguards, the creative economy risks becoming a space where the labor of human artists is endlessly mined, commodified, and erased, while tech companies leach off of the profits. 

Cultural Resistance and Reclamation of Human Creativity. 

In response to these developments, a cultural resistance movement has emerged. People from all walks of life who oppose the use of AI in creative spaces have banded together to raise awareness about the catastrophic effects the over-saturation of AI can have. Protests, petitions, and public debates reflect a growing unease about the displacement of human creativity. At the heart of this backlash is not just a concern over job loss, but a deeper philosophical question: What should we value in art? 

As The Guardian (2025) puts it, we must “reclaim human-centered creativity” in an era increasingly dominated by algorithmic content. This is not just a rejection of technology, but a plea for understand and meaning.When the world is flooded with robotic, machine-generated art, genuine human expression becomes much more valuable. 

Art has always been more surface than aesthetics, rejecting AI entirely may not be realistic, or even desirable. Instead, the goal should be to integrate the use of AI ethically, using it to enhance human creativity rather than replace it. This means establishing firm boundaries around AI’s role in creative industries: transparency about how models are trained, compensation and credit for artists whose work is used, and clear legal definitions of authorship. Educators, lawmakers, and cultural institutions must work together to ensure that AI strengthens artistic practice rather than undermining it. 

Some artists are already using AI collaboratively, crediting the machine while still embedding their own vision into their final project. This hybrid model suggests that the future of art may not be a zero-sum battle between humanity and machine, but a complex interplay of both. 

Moving Forward: Ethical integration, Not Erasure 

The question is not whether AI will shape the future of art, it already is. Like it or not, AI is becoming the future and is playing prominent roles in creative spaces. The question is how will we respond. Will we allow artistic culture to be completely eclipsed by algorithms, or will we draw clear-cut boundaries that preserve human intention, authorship, and emotional depth? 

Moving forward, we must develop legal and ethical frameworks that: 

• Require transparency in how AI models are trained and what data is used.

• Ensure compensation and credit for artists whose works feed into AI systems

• Establish clear definitions of authorship for AI-generated content. 

• Create educational spaces where artists are empowered to engage with AI critically, not passively. 

Rather than discarding AI altogether, we should focus on integrating it responsibly. This includes encouraging collaboration between artists, expanding ethical guidelines, in creative industries, and foregrounding the irreplaceable value of human expression in an age of automation. 

Expanding Ethical Integration: Education and Artistic Values 

By fostering spaces where artists can experiment with AI while maintaining authorship, educators can help reframe AI not as a replacement but as a medium, a medium like photography or collage, which requires its own ethics, aesthetics, and techniques. Courses in art schools, design programs, and even computer science departments must begin to intersect, encouraging interdisciplinary collaboration. Artists and technologists must learn to speak each other’s languages, and collaborate effectively. 

Additionally, society at large needs to reconsider what it truly values in art. As AI-generated content floods online platforms, it becomes easier to overlook the labor and emotion behind human-created work. This overexposure can lead to numbness, where the uniqueness in art is diluted by AI. To counter this, platforms like museums, galleries, or streaming services must take active roles in uplifting human-made content. This may include labeling-AI generated works clearly, developing new ethical display standards, and supporting artist-led initiatives that encourage authenticity. 

At the same time, the public must resist the seduction of convenience. It is tempting to embrace AI-generated music, images, or writing because they are fast, cheap, and infinite. But we must remember that true authenticity creativity is not instant. It’s a perilous process that is composed of woven experiences, memories, perspectives, and cultural differences. It is precisely these qualities, imperfect and rigid, that truly makes art art. 

As we move forward into a future shaped by artificial intelligence, the goal should not be to halt technological progress. Instead, it should be to insist that progress respects the humanity at the core of great art. When wielded ethically, AI can serve as a transformative tool for expanding creative boundaries. But only if we remain committed to preserving the irreplaceable value of human imagination, creativity, emotion, and voice. 

Works Cited

• Abramovitch, S., Hervey, M., Nogeuera, J., & Toyama K. (2023). AI in Arts and Entertainment: A Double-Edged Sword. Divided We Fall. https://dividedwefall.org/ai-in-arts-and-entertainment/

• Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). Creative adversarial networks: Generating “art” by learning about styles and deviating from style norms. arXiv. https://arxiv.org/abs/1706.07068

• Gangu, P. (2018). We need to approach AI risks like we do natural disasters. Harvard Business Review. https://hbr.org/2018/02/we-need-to-approach-ai-risks-like-we-do-natural-disasters

• McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, authenticity, authorship and intention in computer-generated art. In The Philosophy of Computer Art. https://arxiv.org/pdf/1903.02166

• The Bulletin of the Atomic Scientists. (2022, October). Will AI destroy art or just change it? https://thebulletin.org/2022/10/will-ai-destroy-art-or-just-change-it

The Guardian. (2025, May 20). AI-Generated Art and Its Challenges on Traditional Ideas and Authorship. https://www.theguardian.com/commentisfree/2025/may/20/ai-art-concerns-originality-connection