The field of machine learning can arguably be considered as a modern-day incarnation of an endeavor which has challenged mankind since antiquity. In fact, fundamental questions pertaining to categorization, abstraction, generalization, induction, etc., have been on the agenda of mainstream philosophy, under different names and guises, since its inception. With the advent of modern digital computers and the availability of huge amount of raw data, these questions have now taken a computational flavor. In recent years there has been a revival of interest around the philosophical aspects of machine learning from both the computer scientist's and the philosopher's camps, thereby suggesting that the time is ripe to attempt establishing a dialogue between the two communities. The goal of these lectures is to provide an introduction to the philosophical underpinnings of today’s machine learning research and to provide a timely and coherent picture of the state of the art in the field. This could be an opportunity for reflection, reassessment and possibly some synthesis, with the aim of providing the field a self-portrait of where it currently stands and where it is going as a whole. I will assume no pre-existing knowledge of philosophy by the audience, thereby making the lectures self-contained and understandable by non-experts.
Marcello Pelillo is a Full Professor of Computer Science at Ca' Foscari University of Venice, Italy, where he directs the European Center for Living Technology (ECLT). He is Fellow of the IEEE and of the IAPR, and has recently been appointed IEEE Distinguished Lecturer.