The AI & Technology Influence on Contemporary Art exhibition that opens today in London explores the impact of technology on contemporary artists, especially painters, revealing how AI has shaped and challenged their creative processes while sparking profound dialogues on its implications. In the exhibition established artists Jonathan Yeo, Von Wolfe, and Henry Hudson have embraced AI and technology to redefine the essence of a new series of works, seamlessly integrating artificial intelligence and cutting-edge technologies.
Through these groundbreaking works, they explore and navigate the complex relationship between humanity and machines, prompting a re-evaluation of art's future. They probe the boundaries of AI's capacity to expand or limit artistic expression, and examine questions of identity, development, authorship, authenticity, originality, reality.
Jonathan Yeo's exploration of the power dynamics between humanity and technology evokes a strategic chess game, where the outcome remains uncertain. Known for his radical approach to portraiture, Yeo presents a captivating series that transcends conventional identity. By employing 3D scanning technology and AI algorithms to reimagine self-portraiture, Yeo's "Paradox of Progress" blurs the boundaries between the tangible and the virtual and questions the evolution of technology.
Von Wolfe trains AI to cultivate intense psychological narratives, skillfully arranging and crafting his protagonists within it. Von Wolfe's process embodies the seamless interplay between the artist's practice as an oil painter and the forefront of technological innovation. Striking a balance between intuitive human discernment and a cutting-edge, node-based system using diffusion models, the resulting works showcase astounding precision.
For Henry Hudson, the notion of AI evokes a sense of hysteria, questioning its limits, our control over it, and whether it ultimately controls us. Hudson melds technology seamlessly into this new series “Somewhere in Time”, transcending physical and digital boundaries. His creations serve as a metaphor for the fluidity of existence in the digital age, prompting contemplation on the influence of AI on our lives.
The London exhibition is part of a broader trend that highlights the integration of AI in art such as Refik Anatol’s recent exhibition at the Serpentine and AI: More than Human at the Barbican. The latter offers an unprecedented survey of creative and scientific developments in Artificial Intelligence.
In New York’s Times Square, we witnessed Scott Eaton’s large-scale digital moving image piece “Intersections” on the skyscraper screens. An MIT graduate, creative technologist, and multimedia artist, Eaton is a perfect example of an artist who blends machine learning with other skills such as animation, sculpture and drawing. The specific piece reflects on the complexity of the digital landscape that defines our existence.
The technique is trained on a custom dataset of 50,000 images that it is then deconstructed into a single QR code, distorted, and remixed through layers of random processes. This customized AI code exemplifies the complexities of AI and its potential to be adaptable to an artist's intent. It is not just about using AI, but how we leverage it to enhance our creative and unique flair.
New media video artist Jake Elwes explores the ethical problems which exist in AI observing that computer systems “have difficulty recognising trans, queer and other marginalised identities”, in a show running through 2024 at the V&A/ Other artists such as Sougwen Chung use fancy robotics and AI to create drawings and paintings, raising questions whether the focus lies more on the medium or tool itself than the final artwork.
AI was also present in this year’s Venice Biennale. French artist Pierre Huyghe exhibition Liminal at Pinault Collection looks at AI and the relationship between the human and non-human. In Camata, a film edited in real time by artificial intelligence, a set of machines performs a bizarre ritual on a skeleton of a young man found in Chile's Atacama desert.
The trick lies in fine-tuning our own stylistic identity, avoiding generic imitation
Pierre Huyghe has since long questioned the relation between the human and the non-human, and conceives his works as speculative fictions from which emerge other modalities of the world. Fictions, to him, are “vehicles for accessing the possible or the impossible — what could be or could not be.”
In the book How to Speak Machine: Computational Thinking for the Rest of Us, John Maeda, Vice President of Design and Artificial Intelligence at Microsoft, explores the convergence of business, design, and technology. John Maeda is also an artist, so I was particularly interested in his point of view.
In his book, he engineers a rapprochement between humans and our computational creations. As he aptly puts it "Before you can get machines to do what you want, you'd better learn to speak their language” and I assert that teaching machines our language, identity, and distinctive style becomes paramount before they can execute our desires. As the capabilities of AI and language models advance, understanding their implications, potential and pitfalls becomes increasingly crucial.
This show — AI & Technology Influence on Contemporary Art — sparks introspection and dialogue: Is AI and technology a liberating force for creativity, or does it pose risks, challenging the essence of genuine ideas in art? These questions linger, inviting viewers to embark on a journey of discovery alongside these visionary artists.
Personally, I have witnessed artists who tailor the tool to their needs and unique style discover a spectrum of new ideas, broadening their range of inspiration. AI is merely a tool, a passive companion; in the hands of a mature artist who already has developed a distinctive style and identity, extraordinary things can happen.
Artists must curate their own data and consider their provenance, navigating copyright problems that come with the tool's public availability, all while maintaining moral viability, integrity and uniqueness. The trick lies in fine-tuning our own stylistic identity, avoiding generic imitation. AI must learn from the artist, and the artists must train the tool to understand the artist’s identity and style; without critical engagement and curation, we risk the tool leading us, rather than the other way around.
