Hello - I am a Senior Lecturer in philosophy at Birkbeck College, London, where I have been since 2011. I became Head of Department in October 2017. Before Birkbeck, I taught for six years at the University of Missouri-St Louis. I received my PhD from the London School of Economics, and during my last two years as a student I was a visitor at University of California-San Diego. Before switching to philosophy, I did graduate work in economics, receiving an MSc, and undergraduate work in mathematics and history.
Away from philosophy, I have among other things:
... won money at tournaments in pool, poker, and foosball/table football
... been, in my LSE days, captain of a University Challenge TV quiz team, reaching the grand final of the 1996/7 series
... kissed a mother grey whale in the wild on the lips (it was salty), at Laguna San Ignacio in Mexico
... more recently, in golf made my first ever hole-in-one and my first ever rounds under 80
My research is mainly in philosophy of science, and especially the ‘special sciences’ such as biology and economics. I have also written extensively on related themes in metaphysics, especially the notions of causation and causal explanation. These various strands connect when, for instance, analysing the use of statistical techniques to measure causation. I have also applied some of this causal training to debates around several other philosophical issues, including scientific progress, harm, innateness, and free will.
My primary interest is in how knowledge is produced in field sciences, i.e. in sciences outside the confines of the laboratory and unable to conduct shielded experiments, with a particular interest in economics. What is the relation, for instance, between the theoretical development of abstract models, and progress in terms of better predictions and explanations of messy real-world events? Broadly speaking, I argue for more emphasis on local empirical work and less on development of generalised theory.
Most recently, I have been examining the role in field sciences of prediction. When can we rest content with after-the-fact explanation, and when should we insist instead on accurate prediction? What kind of knowledge do we really have if we can't predict well?