AI Meets Busker Ballet
Nick’s work satisfies, almost defiantly, the demand that art be physically made directly by a human hand. His environmental and social commitments are not decoration; they are structural, preferring reuse to waste, repair to consumerism. His math-informed practice appears grounded in social responsibility.
But this raises a question for mathematics itself. Must mathematics also be physically made by a human hand to be true to be genuine?
If we demanded that mathematics be done manually, we would have to discard not only AI-assisted proofs and computer algebra systems, but also mechanical calculators — and, paradoxically, the very mechanical logic embodied in Nick’s machine-artworks. Much of modern mathematics would vanish overnight.
I do not offer a manifesto here. I offer a slogan: Do math as though computers exist. This is not surrender. It is realism that opens the door for more diversity in who can be a math explorer. For students who struggle with symbolic manipulation, the shift from abstract notation to embodied construction can be welcoming. Drawing one’s thinking through mechanism, shadow, angle, motion — this is not dilution but access.
The older paradigm tells a romantic story of the lone genius with chalk in hand. But that story is historically incorrect. Mathematics has always been distributed across abacuses and slide rules, correspondence and collaboration, and various instruments built from whatever materials were available. To mistake the tool for the essence is to misrepresent the history of the discipline.
So: Is math with AI still math?
Of course. But AI feels different.
A calculator does not propose; AI can. It can suggest decompositions, analogies, and structural parallels. This is where the anxiety begins. It is not about tools, but about authorship. When an AI proposes a pathway through a problem, who is "mathing"?
The more I meditate on Sayers machine-artworks, the more I think of Leonardo’s notebooks — not as illustrations, but as engines of thought. Leonardo’s drawings captured mathematical and physical principles. They were speculative mechanisms on paper. Nick’s constructions are speculative mechanisms in metal. Engineering here is math embodied. It is mathematics that must survive gravity, friction, torque, and tolerance.
And this is what makes the AI question sharper.
The work of Sayers lives intentionally in STEAM — where science, technology, engineering, art, and mathematics are maximally collaborative. So when AI enters the frame, the question is not whether it belongs. The question is how it integrates.
If busker ballet is mathematics performed, what happens when AI joins the performance? Does it become another instrument in the orchestra? Or does it move the structure backstage, where the visible friction disappears?
Tools like AI extend exploration. They do not abolish it. But they do change the choreography.
Questions for the artist:
- Nick, since your work is human hand guided by mathematics intelligence, how do you see AI entering that lineage?
- Is it simply another instrument in the workshop? Or does it alter what it means to perform mathematics in public?
- I am fascinated by the social impacts of recommender systems. How could I approach visualizing cosine similarity that powers the user-content matching in a physical installation?
--
Futamura, F. (2025). Writing a mathematical art manifesto. In Bridges 2025 Conference Proceedings (pp. 589–594).
.jpg)
Your post raises a lot of interesting ideas, but one point that really stood out to me was the question of authorship when AI begins proposing pathways in mathematics. That tension feels very real right now.
ReplyDeleteWhen I think about Nick Sayers’ work, it reminds me that mathematical thinking has always been supported by tools and physical systems. His machines don’t replace the thinking—they externalize it. The gears, chains, and bicycle parts become a way of making the mathematics visible and testable in the physical world. In that sense, the machine is collaborating with the human rather than replacing them.
I wonder if AI might eventually be understood in a similar way. Instead of replacing the mathematician, it may function more like an intellectual mechanism—something that helps surface patterns, possibilities, or alternative approaches that a human can then interpret, critique, and refine. The authorship may remain human, but the exploration becomes more distributed.