Note: click here for the recording of this talk
Speaker: Jan-Willem Romeijn (University of Groningen)
Date and Time: Thursday, November 16th 2023, 16:30-18:00
Venue: ILLC seminar room F1.15 in Science Park 107 and online
Title: Reverse-engineering the model
Abstract. Data-driven or “machine learning” prediction methods generate predictions from data without explicitly stating their modeling assumptions. In fact there are substantial obstacles to bringing those assumptions out in the traditional format, because machine learning methods mostly do not rely on explicit representations of their target systems. In my talk I combine recent machine learning research and insights from inductive logic and the philosophy of statistics to provide a road-map for reverse-engineering the models inherent to any prediction method. Next I will determine whether and in what ways these implicit models represent their target, drawing on ideas about randomness and nonlinear dynamics. My preliminary conclusion is that the reverse-engineered models represent only superficially, and that they make visible how our traditional conception of models is ill-suited for a science of complex systems, echoing Breiman’s seminal paper on the two cultures of statistics.