math skills
this is a guest post by tony schultz.
As a field dance-tech is in its infancy. It is ill defined and in an early process of formation. I imagine it as a cyborgian stem cell, bubbling with latent potentialities. In many ways it is a battleground in which practitioners fight to colonize and direct the field in attempts to determine what kind of cyborgs we are to become.
The cyborg project, to quote Donna Haraway, is a way of explaining “our bodies and our tools to ourselves… a powerful infidel heteroglossia.” {Cyborg Manifesto} An important part of creating this “infidel heteroglossia” is adopting (co opting) the language of science and mathematics. “Explaining our tools to our selves” means understanding our technologies and not just dancing with them.
Integrating mathematics into dance-tech pedagogy is a creative process and need not be didactic. The question of what mathematical tools a dance-technologist should have mastery of is an open one. As educators we should be comparing notes to see what fundamentals provide our students the greatest expression in their own work. Trigonometry, calculus, topology, probability theory and matrix algebra are a few tools that are useful in development. They not only relate to computer vision, graphics, image and signal processing but also to the world outside of the computer, in conceiving of dancing itself.
This issue is not simply about inserting mathematics into an arts curriculum, the action is reciprocal. Dance-tech provides new ways of knowing mathematics. Our ways of knowing are always changing and imbricated with the current mode of production. For example, Descartes reduced many problems of algebra down to the construction and measurement of geometrically constrained mechanisms (La Géométrie 1637).
Today we use computer programs to embody knowledge. In coding we build similar kinds of constrained bodies whose measurement yields knowledge. Dance opens up the body as an epistemic locus as well. In dance-tech we come into knowing using physical bodies and digital bodies. I have found it possible to communicate fairly complex mathematical concepts to my students about dancing by building and cranking media machines. Dance graphs and their entropic properties are good examples.
Lately I have been trying to share some small bits of code online that represent fundamental mathematical principles. One such element is the integrator. This is a little machine that adds numbers up. Integration need not be shrouded in the esotericism of formal mathematical proof. Instead we can come to know it by implementing it in a technical assembly and then probing that assembly. Those previously unfamiliar with calculus can come to understand it through their interaction with the machine.
Once we have integration under our belt we can invert it {differentiation} or embed it in larger assemblies that embody more complex differential relationships. The simple harmonic oscillator is a good example. This is a system in which a signal is in constant negative proportion to its second integral (or second derivative depending on how you look at it). Investigating these simple systems can give insight into into building interfaces that respond in more physically intuitive ways.
I hope that others in the field will take this as a invitation to share code with some of their basic body building strategies.
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Tony Schultz is a physical scientist. He teaches a course in Dance & Technology at Sarah Lawrence College. The course keeps a blog; «Dance Machines».
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