08.10.2024, 10:15 - 11:45
– 3.06.H02
Kálmán Lecture
Particle Methods in Machine Learning and Inverse Problems
Martin Burger, Helmholtz Imaging
Prof. Nathalie Sinclair (Simon-Fraser-University, Canada)
To measure is at once a practical and a conceptual engagement with the world. At its most basic, measuring involves empirical encounters (broadly conceived) that allow one to assign various quantitative values to the phenomenon which is under study. But measurement is not only this material and semiotic rendering of the physical world, since it has tremendous philosophical implications for how we make qualitative sense of our world. In this talk, I will delve into the under-examined complexity of measurement as a process that entails situated corporeal mobilities of all kinds. I show how school mathematics very quickly narrows the measurable world into particular parameters, so that children are made to focus almost exclusively on numerically measur-ing extension (perimeter, length, area, volume, speed). This approach emphasises the act of ‘covering’ spatial objects with standardized units. What is lost in these learning exercises are the intensive, relational, and analogical aspects of measuring, which I argue are critical to the politics of dis/ability in mathematics education.