Katrina Elliott

Does smoke cause fire or does fire cause smoke? James Woodward’s “Flagpoles anyone? Causal and explanatory asymmetries” argues that various statistical independence relations not only help us to uncover the directions of causal and explanatory relations in our world, but also are the worldly basis of causal and explanatory directions. We raise questions about Woodward’s envisioned epistemology, but our primary focus is on his metaphysics. We argue that any alleged connection between statistical (in)dependence and causal/explanatory direction is contingent, at best. The directions of causal/explanatory relations in our world seem not to depend on the statistical (in)dependence relations in our world (conceived of either as frequency patterns or as relations among chances). Thus, we doubt that statistical (in)dependence relations are the worldly basis of causal and explanatory directions.

Not all probability ascriptions that appear in scientific theories describe chances. There is a question about whether probability ascriptions in non-fundamental sciences, such as those found in evolutionary biology and statistical mechanics, describe chances in deterministic worlds and about whether there could be any chances in deterministic worlds. Recent debate over whether chance is compatible with determinism has unearthed two strategies for arguing about whether a probability ascription describes chance—that is, to speak metaphorically, two different strategies for figuring out where the chances are: find the chances by focusing on chance’s explanatory role or find the chances by focusing on chance’s predictive role. These two strategies tend to yield conflicting results about where the chances are, and debate over which strategy is appropriate tends to end in stalemate. After discussing these two strategies, I consider a new view of chance’s explanatory role. I argue that one theoretical advantage of this new view is that allows us to make progress on the question of where the chances are by providing a principled way of determining which probability ascriptions describe chances. From the vantage of this new view, the correct application of both strategies involves figuring out where the chances are by figuring out where the probabilistic scientific explanations are and what those explanations are like.

A synchronic probability is the probability at a time that an outcome occurs at that very time. Common sense invokes synchronic probabilities with values between 0 and 1, as do scientific theories such as classical statistical mechanics. Recently, philosophers have argued about whether any synchronic probabilities are best interpreted as objective chances. I add to this debate an underappreciated reason we might have to believe in synchronic chance; it might turn out that the best interpretation of our common sense and scientific theories is one in which the macrophysical properties of physical systems are partly determined by synchronic chance distributions over microphysical properties of those systems. Additionally, I argue against the common charge that synchronic probability fails to satisfy various platitudes about chance—most notably Lewis’s Principal Principle.

According to David Lewis’s Principal Principle, our beliefs about the objective chances of outcomes determine our rational credences in those outcomes. Lewis influentially argues that any adequate metaphysics of objective chance must explain why the Principal Principle holds. Since no theory of chance is widely agreed to have met this burden, I suggest we change tack. On the view I develop, a central aspect of the Principal Principle holds not because of what objective chances are but rather because of the explanatory role that objective chances play for the rational agents who believe in them.