Tuesday, 3 April 2012
Dynamics, Data, and Noise in the Cognitive Sciences
Anthony Chemero, Department of Psychology
Franklin & Marshall College
12:05 pm, 817R Cathedral of Learning
Abstract: The standard understanding of good experimental design in the cognitive sciences calls for the minimization of error variance, a.k.a., noise. Yet certain nonlinear dynamical modeling techniques, recently imported to the cognitive sciences from statistical mechanics, upend this conception by taking the structure of noise to be the primary data. These methods are allowing psychologists to address previously elusive questions concerning central topics such as the modularity of cognitive systems and the nature of insight in problem solving. As an example of the sort of nonlinear modeling which treats noise as the primary data, I will describe work in which we were able to demonstrate experimentally a central aspect of Heidegger's phenomenological philosophy: the transition from readiness-to-hand to unreadiness-to-hand. After discussing this use of noise as data, I discuss the consequences of this kind of nonlinear modeling for the distinction between data and noise, for the varieties of explanation appropriate in the cognitive sciences, and for experimental design.