Author: jennkarson
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Machine Learning and Deep Green Workshop 2019
This 2019 Machine Learning workshop and invitation to work with UVM’s high performance computing center was my first hands-on introduction to machine learning. Three years before the public launch of ChatGPT, it was the beginning of a journey and practice that continues to this day. I’m grateful to have been introduced to AI before Big…
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Can AI Make Art?
Public Philosophy Week 2025 With Juniper Lovato, Jennifer Karson, and Julia Zimmerman As generative AI transforms creative industries many critical questions arise: Can AI truly create art? Does the creation of art require agency? How does AI impact artists’ creative autonomy, ownership, and fairness in the artistic landscape? We will talk about our recent research…
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AI, Nature, and Art
Where do AI, the natural world, and digital art meet? We explored this rich terrain through The Generative Tree exhibition and programming with Champlain College Professors Kristin Wolf, Ariel Burgess, and their students! The following photo essay tells the story.
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Unusual Partnerships Between Humans and Machines
Aberrant Creativity is an international, juried exhibition exploring the boundaries between our machines and ourselves. It is an opportunity for artists to challenge AI, to seduce AI into creative partnership, or lead it astray into play and joy.
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Navigating Latent Space
Here’s a look at latent space mapping and discovery with the Athena Dataset; we experienced this mathematical space as a new physical world, as new terrain and territory.
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Can technology save us from the climate crisis?
The UVM Art and AI Research Group has created a project that director Jennifer Karson says begs the question: Can technology save us from the climate crisis?
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Transfer Learning
This print illustrates the process of transfer learning, a machine learning technique when a model trained on one task is reused –usually to save time and computing energy– for another related task. A series of uncanny images reveals a machine learning model’s transition from a training dataset to a primary one.
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Tiny Datasets
The intimacy of a tiny dataset approach is in contrast with big data and its tendency to produce homogenized results; the Tiny Dataset series celebrates its local, limited, situated, chaotic, and precise results in alliance with Donna Haraway’s critique of “The God Trick.”
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When Artistic Authorship Meets Scientific Bias
“Team Picks” contrasts desirable artistic authorship and undesirable scientific bias. It confronts the destiny of any new technology – that it will eventually become an old, discarded one.
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Five Guardrails for Artists Working with Machines and A.I.
While attending the July Center for Machine Arts residency, surrounded by so many seductive artmaking technologies, I had to spend my time efficiently as we prepared for a fast-approaching exhibition. This is not an unfamiliar process for me as I routinely evaluate how machine learning serves my art practice; sometimes it does and other time…
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Summer Art + AI Outreach Programs
This week with the help of my nephew Ramsey Karson, we hosted numerous Art + AI outreach programs in the University of Vermont FabLab. The program builds from the Athena Dataset, integrates P5 programming and an introduction to our genetic algorithm. We worked with UVM Extension and Vermont 4H and the UVM Upward Bound Program.…