Sander Beckers (Cornell University) on Actual Causation

Actual Causation using Nondeterministic Causal Models

Sander Beckers (Cornell University)

January 10, 14-16h, Seminarroom, 1st floor, Sydnesplassen 12-13

In recent work I introduced nondeterministic causal models as a generalization of Pearl's standard deterministic causal models. In this talk I take advantage of the increased expressivity offered by these models to offer a novel definition of actual causation (that also applies to deterministic models). Instead of motivating the definition by way of (often subjective) intuitions about examples, I proceed by developing it based entirely on the unique function that it can fulfil in communicating and learning a causal model. First I generalize the more basic notion of counterfactual dependence, second I show how this notion has a vital role to play in the logic of causal discovery, third I introduce the notion of a structural simplification of a causal model, and lastly I bring both notions together in my definition of actual causation. Although novel, the resulting definition arrives at verdicts that are almost identical to those of my 2021 definition.