Jimmy Fallon, host of “the tonight show,” features a recurring comedy segment called “Google Translate Songs,” where he and a celebrity guest perform popular songs whose lyrics have been run through Google Translate — one of the most widely used AI tools. The results are intentionally absurd. The Weeknd’s “Can’t Feel My Face” is transformed into “My Front is Not Felt,” and Gloria Gaynor’s empowering anthem “I Will Survive” becomes the far more mundane “I Will Be Punctual.” The segment is hilarious, and part of the joke is that artificial intelligence — despite all its power — still doesn’t quite get us. In moments like these, AI feels less like a futuristic genius and more like an eager but wildly confused intern.
Still, despite these misalignments, AI — once relegated to the realm of science fiction — has become an increasingly integrated force in contemporary life, reshaping industries from health care to finance to consumer retail. In the arts, a domain traditionally seen as the last bastion of human ingenuity and emotion, AI’s emergence as both a tool and collaborator has raised complex questions. What happens when machines not only replicate human creativity but begin to produce original works? How do artists, institutions, and audiences reconcile this technological evolution with centuries-old practices of artistic embodiment, intention, and intuition?
In recent years, AI has grown so sophisticated that it can convincingly mimic real people and places in videos — for example, leading some viewers to momentarily believe a tsunami hit Seoul, or that a celebrity said or did something they did not. These AI-generated “deepfake” videos, often circulated on social media, can flawlessly replicate a public figure’s voice, facial expressions, and mannerisms, blurring the line between reality and fabrication. Whether it’s a viral clip of Tom Cruise performing magic tricks on TikTok or a fake video of Morgan Freeman delivering a speech he never gave, the realism of these creations can be disorienting. Most of us have probably been fooled at least once — laughing, reacting, or even sharing the content before realizing it wasn’t authentic. This phenomenon reveals not only the technical prowess of AI but also the fragility of truth in the digital age.
Yet each of us uses AI every day. It has already been woven seamlessly into our lives and artistic practices — often in ways that feel intuitive, accepted, and even indispensable. Still, the growing fear of AI’s seemingly inevitable dominance, coupled with unresolved ethical questions and its sweeping cultural implications, casts a long shadow over the future of unique human expression. If you can use Midjourney to generate a visual masterpiece, why commission a painter? If a 3D printer can render a stunningly lifelike “stone” sculpture, what becomes of the sculptor? If you can hum a melody into Soundful or Boomy and receive a full orchestration, what need is there for a musician? And if you can project a holographic performance onto your living room wall, why leave your home — or pay — to see Denzel Washington breathe life into a character on stage or screen?
AI has been embraced in the visual arts as both medium and co-creator. One of the most prominent early examples is “Portrait of Edmond de Belamy” (2018), a painting generated by a generative adversarial network (GAN) developed by the Paris-based collective Obvious. The portrait, resembling a blurry Old Master-style painting, was auctioned at Christie’s for over $432,000 — far surpassing its estimate and signaling a major moment of market recognition for AI-generated art.
GANs, a class of machine learning frameworks developed by Ian Goodfellow in 2014, have become central to AI’s presence in the visual arts. These systems “learn” from vast datasets of images and produce original outputs by mimicking stylistic features. Artists like Refik Anadol, whose immersive digital installations use AI to translate massive datasets (such as brain scans or architectural archives) into visual landscapes, represent a new paradigm of the data-driven artist.
In Anadol’s “Machine Hallucination” (2019), the artist trained AI on 100 million photographs of New York City, producing a dreamlike cinematic environment that reimagines collective memory.
Importantly, artists of the African diaspora are also experimenting with AI to extend traditions of resistance, speculation, and cultural memory. Nigerian American artist Mimi Onuoha explores data absence and systemic erasure, using AI not to generate spectacle, but to interrogate what’s missing. Similarly, British Jamaican artist Rashaad Newsome incorporates machine learning into his “Being” project — a digital griot and virtual avatar that teaches critical pedagogy rooted in Black queer thought. Their work challenges dominant frameworks, insisting that AI can be a site of cultural reclamation and future-building rather than mere replication.
The collaboration between AI and artists has also taken form through tools like DALL·E (by OpenAI) and DeepDream (by Google), which allow artists to create visual artworks based on text prompts or neural style transfers. Rather than replacing the artist, these tools often serve to expand the boundaries of what is creatively possible, encouraging hybrid workflows and redefining the role of human intentionality.
Black diasporic performers have also begun engaging AI with cultural specificity. Artist and researcher LaJuné McMillian merges West African movement traditions and motion capture technology to create digital dance archives that resist the extractive gaze of Western technology. Their Black Movement Library invites communities to record and train AI on their own cultural gestures — reshaping machine learning from within. In the realm of music, South African producer Spoek Mathambo has experimented with AI-generated beats as a way to interrogate post-colonial hybridity in Afro-techno sounds. These artists are not simply using AI — they are repurposing it to reflect and protect cultural knowledge.
In the performing arts, AI has found diverse applications ranging from dance and music composition to theatrical performance. Choreographer Wayne McGregor collaborated with Google Arts & Culture Lab in “Living Archive” (2019), training a machine learning model on his past choreographic work. The AI generated new movement phrases that McGregor then interpreted and staged with live dancers. Here, AI functioned not as a replacement for the choreographer but as a generative partner, expanding creative possibilities through recombination and surprise.
Music, too, has seen AI systems compose symphonies, improvise jazz, and emulate iconic musicians.
OpenAI’s MuseNet and Google’s Magenta project have created original compositions in the styles of Mozart, Beyoncé, and The Beatles. AI-driven systems like AIVA (Artificial Intelligence Virtual Artist) are even being used in commercial music production, scoring short films, advertisements, and video games. In 2020, composer David Cope’s Emily Howell system, trained on his earlier work, produced compositions that critics were unable to reliably distinguish from human-composed pieces.
AI has also touched theatre and playwriting.. Beyond simply incorporating AI thematically within the content of plays — such as in “Marjorie Prime” by Jordan Harrison or “The Nether” by Jennifer Haley — or using AI-enhanced production elements like intelligent lighting systems, algorithmic soundscapes, and motorized sets, theatre is now exploring AI as a generative force in the creation of material and design itself. In 2021, the Prague-based Švanda Theatre presented “AI: When a Robot Writes a Play,” a one-act drama written entirely by GPT-2. Though the result was fragmented and at times surreal, the performance became a provocative entry in conversations about authorship, coherence, and the dramaturgical limits of machine logic. Similarly, in 2022, the Young Vic Theatre in London collaborated with technologists and playwrights to create “AI,” an experimental piece where a neural network co-wrote dialogue based on audience prompts in real time, blending improvisation, computation, and live performance to question the boundaries between human spontaneity and machine intelligence.
Meanwhile, Black playwrights and directors are beginning to interrogate AI not just as a tool, but as a subject of narrative inquiry. The National Black Theatre in Harlem, under the leadership of Sade Lythcott and Jonathan McCrory, has begun conversations about how AI intersects with Afrofuturism and spiritual technologies — asking not only what AI can do for performance, but what performance can teach AI. In experimental theatre circuits, artist-activists such as Toshi Reagon and Olufunmilayo Arewa are exploring AI’s implications through storytelling grounded in ancestral memory, technological justice, and speculative Black futures.
Despite these innovations, AI’s role in the arts remains deeply contested. While some embrace the technology as a tool of democratization and experimentation, others see it as a threat to authenticity, labor, cultural continuity, and the human creative impulse itself. Many artists and critics question whether AI-generated works can truly embody the emotional depth, historical consciousness, or lived experience that define human artistry. Phylicia Rashad, dean emerita of the College of Fine Arts (BFA ’70), underscored this concern by quoting a passage from August Wilson’s “Gem of the Ocean,” then pausing to ask the audience, “Now, can a computer do that?” Her question echoed the skepticism shared by many in the arts community. The late critic Dave Hickey similarly argued that “art is made by desire and error,” qualities that AI, by its very nature, cannot genuinely possess. At the same time, concerns about creative labor are intensifying. As AI becomes increasingly adept at replicating artistic styles, many artists have found their work taken without consent or compensation, sparking lawsuits and fueling advocacy for stronger digital copyright protections and enforcement.
Professional guilds in the performing arts, such as the Writers Guild of America (WGA), have also taken positions on AI. In 2023, the WGA negotiated contract language stipulating that AI cannot be credited as a writer, nor replace human writers in the development of film and television content. This was a landmark moment in labor’s response to AI and signaled broader anxieties about displacement and devaluation of creative work.
Furthermore, AI’s aesthetic tendencies — rooted in algorithmic patterns, averages, and training sets — raise concerns about cultural homogenization. As media scholar Kate Crawford warns in “Atlas of AI” (2021), these systems often reinforce dominant norms embedded in their training data, leading to “aesthetic convergence” and erasure of minority or radical voices.
At a deeper level, AI’s integration into the arts forces a reconsideration of the very nature of creativity. Is creativity solely the domain of conscious beings, or can it emerge from systems that merely simulate cognition? Can machines truly have need, desire, intention, understanding, and wisdom — or are we just confusing their smooth responses with real intelligence and creative action?
Some argue that AI does not create, but rather calculates; it recombines existing materials without understanding or meaning. Yet others see in AI a new form of creativity — one that can usher in a new creative era in human expression full of surprise, innovation, and even the subversion of expectations precisely because it lacks the limitations of human perception and preconceptions.
The fine and performing arts have long grappled with the tension between craft and concept, originality and imitation. From Duchamp’s readymades to postmodern pastiche, the boundaries of authorship have always been fluid. AI is simply the latest medium to stretch these limits, compelling us to ask not only what art is, but why we make it — and what it’s worth to us all.
Looking ahead, AI is likely to remain both muse and rival in the arts. A 2023 study from the World Economic Forum predicts that AI will augment, not replace, most artistic professions — giving rise to new hybrid roles and creative industries. Programs such as Adobe’s Firefly, which embed AI within traditional creative software, point toward a future of seamless human-AI collaboration.
But such a future demands robust ethical frameworks. Artists, educators, and institutions must lead in developing policies around transparency, consent, and credit — the latter of which often determines the sustainability of any artistic livelihood. If AI is to be a part of our creative ecosystems, its use must be intentional, equitable, regulated, and critically engaged. Artists must be at the forefront of shaping how AI is used — not only as users, but as theorists, designers, and ethicists. The arts offer a singular lens through which to examine the social, emotional, and existential dimensions of technology. In this sense, AI’s infiltration into the arts is not merely a technical development — it is a profoundly human challenge.
I was reminded of this during a recent visit to the island of Burano, off the coast of Venice, Italy, where I met women preserving the vanishing tradition of handmade lacemaking. They spoke with quiet sorrow about how the intricate craft that once sustained generations of women is likely to disappear, as younger women choose skills more aligned with today’s economic realities. I was shown a stunning lace tablecloth — reportedly made by seven women over the course of two months — on sale for a discounted price of $14,000. It was exquisite. But even as I admired its beauty, I could not justify the cost for either home dining or my budget. That moment illuminated the difficulty of sustaining labor-intensive human artistry in a world increasingly driven by speed, efficiency, and automation.
In the end, whether AI is ultimately seen as a collaborator, competitor, or colonizer will depend on how artists, institutions, and societies choose to engage with it. The arts may not need to “resist” AI so much as reimagine what artistry means in a world where machines can mimic — but not quite become — us; where they can demonstrate knowledge and intelligence but still fall short of common-sense wisdom. Even if AI doesn’t improve one iota, it is here to stay. As we stand on this creative threshold, the real challenge, then, is not whether AI can make art, but whether we can professionally make art with AI in ways that still honor the depth, diversity, uniqueness, and dignity of the human spirit.
Article ID: 2366