The current pandemic has focused attention on the techniques used by epidemiologists and other non-experimental scientists to infer causal hypotheses from correlational data. I have previously argued* that we need to explain these techniques by reducing causal relationships to dependencies in systems of structural equations with probabilistically independent exogenous variables. In this talk I shall aim to use this account to cast light on (a) single-case counterfactual dependence and actual causation, (b) the content and practical relevance of generic causal claims like “smoking causes cancer”, (c) the temporal asymmetry of causation, and (d) the proper understanding of rational action under risk.
*In particular, I’ve argued this in http://weebly-file/1/8/5/5/18551740/stat_nat_csn_monist.pdf. I will also be giving a talk on it at the CUNY Logic and Metaphysics workshop on Monday 7 March 1615-1815.
The talk will be on Zoom. All are welcome to attend!
The zoom link will be distributed through the MAPS mailing list. If you are not on the MAPS mailing list and would like to receive the Zoom link for the talk, please email nyphilsci@gmail.com.
Presented by Metro Area Philosophers of Science