Michal Hladky

Bas Van Fraassen is a nifty philosopher of science. He received his PhD in Pittsburgh in 1966, under the guidance of Adolf Grünbaum, he taught at Yale University, the university of Toronto, the University of Southern California, he has been McCosh Professor of Philosophy in Princeton, and eventually joined the department of philosophy at San Francisco State University, where he has the title of Distinguished Professor of Philosophy. He first gained attention with his book An Introduction to the Philosophy of Time and Space where he tried to develop a formal theory of space and time based on the notion of causality. The book had an enormous legacy, with experts of the likes of John Earman and David Malament joining the debate. However, he achieved V.I.P. status with his classic The Scientific Image, where he defends a combination of empiricism and antirealism towards unobservable entities based on a re-definition of what the scientific enterprise is. His last achievement is the tome Scientific Representation: Paradoxes of Perspectives, where he combines his scientific empiricism with the view that theories are best thought as models or structures, rather than sets of sentences. In this interview, we talk about his philosophical influences and the birth of The Scientific Image during a journey through North-Africa, Turkey and Eastern Europe, we talk about saving the phenomena and suspending judgement over the existence of unobservable entities, living in world full of mysteries and leaving unanswerable questions unanswered, rationality and irrationality, living in a simulation, the historical interplay between theorizing and experimenting, the meaning of particle detectors for an empiricist, the unity of science and physicalism, the condemnation of Galilei by the Church, and the distinction between Appearance and Reality…

Computational modelling and simulations are often compared with experiments. It has been argued that these methods should be distinguished from experiments, that they are theoretical or that they require new epistemology. Many of these position are based on the intuition that as these methods rely on computation which can be reconstructed as series of deductive steps, the results they produce are conclusions of deductive arguments. Through a model-theoretical reconstruction of in silico experiments, I will demonstrate that the deductivist framework is not entirely adequate to capture their epistemology. Consequently, deduction is not an adequate criterion demarcating simulations from experiments.