Data–Worlds Lecture at Schaufler Lab@TU Dresden

28-30 Sept. 2026

Presenting within the Data Epistemologies context at the Data–Worlds Symposium taking place at TU Dresden 28-30 Sept., 2026. Paper: Data Sensitivity, Modeling Worlds, and World Models will take place on 30 Sept. More conference details here.

While Kant infamously wrote that intuitions without concepts are blind, in ‘white ignorance’ Charles Mills quipped back, that concept blindness blocks vision. Analogously, in machinic terms, data without a model is asemantic, and yet model ignorance prohibits the interpretability of, and sensitivity to data as relevant in the first instance. Epistemologically speaking, this analogy rehearses the ageless ‘frame’ problem long before digital computation: through what frameworks is data conceptually embedded, such that a meaningful inference can be made, perhaps one that abuts with normative convention? Considering the history of human knowledge is riddled with reticence towards data that unsettles frameworks of interpretability,  this presentation adopts a biosemiotic vantagepoint in view of human / ML interactions, examining instances of analytic abduction in the encounter between divergent cognitive Umwelten that work to recalibrate sensitivity to data otherwise.