Dance Moms Trained a Generation to Perform for Algorithms
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Dance Moms Trained a Generation to Perform for Algorithms
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概要
Competition dance trained young girls to hold their bodies in anticipation of judgment—to perform flawlessly, make difficulty look effortless, and measure themselves in real time against a crowd.
TikTok rewarded all of that. This was not a coincidence.
In this episode, I'm writing about Maya Man's StarQuest, a lecture-performance I saw at LA Dance Project—a work built from 111 AI-generated eight-second clips, each manually restaged from screenshots of Dance Moms episodes, generated using Google's Veo model, and shuffled endlessly by a custom app that never plays them in the same order twice.
The piece traces a throughline from competition dance to the algorithmic logic of social media—and then turns the camera on the artist herself. When Man tried to generate a mixed-race dancer to represent her own body, the model couldn't do it. Through that failure, she found her real role in the work: not dancer, but coach. The same relationship she'd been examining in Abby Lee Miller. The same one running the internet.
I also get into Ted Chiang's argument about AI consciousness and suffering, what it means to command something that performs on your behalf, and whether the act of prompting an AI model is, in some small way, a rehearsal of the same demanding absolutism the work sets out to critique. Also, exploding video game avatars.
If this kind of cultural criticism is your thing, I write about it every week at Killscreen—experimental games, interactive art, and the questions interactive media is quietly raising about how we live.
- (00:00) - AI Consciousness Doubts
- (00:36) - Suffering and Moral Agency
- (01:22) - Seeing Star Quest Live
- (02:48) - Dance Moms to Data Bodies
- (03:54) - Building the AI Clip Machine
- (04:54) - Coaching the Uncanny Performers
- (06:18) - What We Owe Our Creations
Hosted by Jamin Warren. Music by Nick Sylvester.
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