Artificial intelligence is no longer just a technical breakthrough—it’s a civilizational moment, and artists are asking crucial questions about its implications.
On the heels of our video HOW TO SEE LIKE A MACHINE, we continue to delve into the ways in which artists continue to confront and use AI as the technology rapidly advances. In this video, HOW TO SEE THE HUMAN IN THE MACHINE, we are again joined by some of the foremost thinkers and creators in the field. In this wide-ranging conversation, the “godmother of AI” Fei-Fei Li, who leads Stanford University’s Human-Centered AI Institute, Be...
Questions asked in this interview
1
7:57The actual value is an interplay between things versus a picture that you put on the wall, right?
I do believe we're in a civilizational moment because AI and the surrounding technology is causing such a profound shift in the way we can live our lives that not only it's a technological inflection point, it's going to cause an inflection point in our social structure. As a scientist, I do feel a deep and profound sense of responsibility because I'm one of the people in our generation that brought this science into the world.
My contribution in AI started with realizing the importance of data. We are constantly producing data. We're constantly producing new behaviors, new ideas, new activities. But the more profound question is just because individuals are producing data, whether they're creators or just going about everyday life, doesn't mean we can always just take it all the time for free and without the considerations.
There are science questions and there are art questions and then there's also design questions, right? I would say that design and art questions are more about the actual impact of AI in the world, right? They're about imagining possible futures and trying to understand the consequences that they can have on the world.
We started working with AI about 10 years ago. My background is in computer music and when I learned about AI in the audio domain, it felt like an opportunity to create sounds that had never existed before and also new ways of performance. So, I'm really interested in these really important historical moments that kind of open up a possibility for all kinds of artists to explore and kind of run with it and create new forms of art with.
We're working right now with the artists Holly Herndon and Matt Dryhurst who are incredible collaborators and at the forefront of art and technology. The last few years of AI have been almost like 500 years of change as machine learning models have developed in scope and have been thinking and learning and training and producing new kinds of sensory experiences and information.
And Holly and Matt are coming up with new and unorthodox ways of perturbing and disturbing those systems. We were really building things from the ground up which required questions like what's your data set?
AI models are actually just us in aggregate. So an AI model output is both the product of everybody and nobody in particular. Try writing IP law around that. That's what's new about this, right? You train a model properly, everyone's in there and the result you get is the responsibility of nobody. Producing training data should be a deliberate act. It's a new medium of art in a sense.
I had always wanted to make a kind of one-to-one voice model and it felt like the only right answer would be to use my own voice. And so I sang from a series of TIMIT scripts which is basically a series of texts that cover all of the phonemes of the English language. The computer will understand how your voice sounds. While most people would want to protect their voice, we thought it would be more interesting to do the opposite, to actually make Holly's voice public domain and give people the tools to use it as they wanted.
I trained an AI on my own voice and now she can sing anything in multiple languages. Her name is Holly Plus.
In constructing a different protocol for how training might take place, you're kind of pointing to a different world.
In 2024, Holly and Matt created a work called Play from Memory for an online exhibition at MoMA. They were inspired by a 1920s form of music pedagogy for children that used what they called imitation games to teach children how to play music, but also how to improvise. And what you see is a series of fantastical images of instruments, for example, that never existed, and sounds as well that are otherworldly. And these are all generated through machine learning models that Holly and Matt fine-tuned, trained, and constructed to be able to almost speculate about what this kind of musical pedagogy could produce. They were fascinated by the similarities between how people thought children could be trained to play music and how we think about training machines.
Every step of the way they have confronted the challenges and issues of AI and consent. And this is why they are really interested in participatory forms of music like choral music, even medieval hymns and call-and-response. They've done arena concerts where they have these huge crowds that they ask to opt in into a kind of training set and it becomes a beautiful call-and-response. The sound is gorgeous.
And then Holly and Matt will use those sounds, recorded sounds, to then create new generative AI artworks. And in the sense that training sets usually are taken from images and sounds and pieces of information that are just out there in the internet, Holly and Matt are curating and crafting and asking people to participate in creating their own training set.
4 more exchanges in this transcript
Sign in free to read the rest of this interview. No card required.
Li, F. (2026, February 2). How Artists Are Rewriting AI’s Future | Fei-Fei Li, Holly Herndon and Mat Dryhurst [Interview transcript]. The Museum of Modern Art. CEOInterviews.AI. https://ceointerviews.ai/interview/680841/
MLA
Fei-fei Li. "How Artists Are Rewriting AI’s Future | Fei-Fei Li, Holly Herndon and Mat Dryhurst." The Museum of Modern Art, 2 Feb. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/680841/.
BibTeX
@misc{li2026_680841,
author = {Fei-fei Li},
title = {How Artists Are Rewriting AI’s Future | Fei-Fei Li, Holly Herndon and Mat Dryhurst},
howpublished = {Interview transcript, The Museum of Modern Art. CEOInterviews.AI},
year = {2026},
month = {feb},
url = {https://ceointerviews.ai/interview/680841/},
note = {Speaker-attributed transcript with timestamps}
}
