Workshop on Causal Explanations
Participation in presence or via Zoom
Participation to the conference is free, but, due to the new rules regarding the Covid pandemic, it is mandatory to register. The conference registration is open: Registration apply
The access to the Department of Humanities is allowed only with the Green Pass or a negative covid test in the last 48 hours and the self-certification available in the download area. Face masks must always be worn.
It is also possible to partecipate in the event via Zoom: Zoom registration.
The Zoom link will be sent to the registered participants one hour before the conference begins.
The notion of causation, and its relation with the notion of explanation, have been deeply investigated in the area of contemporary philosophy of science, but the lively confrontation with current scientific theories in several domains continues to raise stimulating questions, both in science and philosophy. This international workshop, featuring some among the most distinguished scholars on this topic, focuses on the investigation on the nature and scope of causal explanations, with a special attention to the plurality of philosophical accounts that have been proposed in contemporary philosophy of science and epistemology concerning causation and its links with related notions such as explanation, probability, reduction.
F. Laudisa, Introduction
M. Kistler, Why distinguish causal and non-causal explanation?
J. Berkovitz, On eclecticism in causal explanations
C. Hoefer, Humean Chance & Causation
Université Paris 1-Panthéon Sorbonne, UFR de philosophie, & Institut d'histoire et de philosophie des sciences et des techniques
Why distinguish causal and non-causal explanation?
Both Lewis’ theory of causation among events in terms of counterfactual dependence and Woodward’s theory of causation among variables in terms of manipulability assimilate scientific explanation with causal explanation, just as the traditional deductive-nomological account of explanation. However, not all explanations are causal. Many non-causal dependence relations can be used for explanation. In the first part of the talk, I illustrate this with non-causal association laws between physical variables. In a second part, I argue that the distinction between causal and non-causal explanation has two interesting consequences.
(1) Kim’s argument against the causal efficacy of mental events depends on the premise that all explanations are causal; once the distinction between causal and non-causal explanation is introduced, Kim’s “principle of causal-explanatory exclusion”, which is crucial for his argument, doesn’t seem plausible any more.
(2) Sartorio has argued that causal influence does not come in degrees, on the basis of the premises that a) moral responsibility is judged on the basis of causal influence, and that b) there are two ways of “being more of a cause” (coming closer to being a sufficient condition for the effect, and coming closer to being a necessary condition for the effect), which are sometimes not comparable. In reply, I argue that that the fact that dependence relations of these two sorts are not always commensurable, does not show that causal influence doesn’t come in degrees. Rather, we should conclude that moral responsibility can be grounded both on causal and non-causal forms of dependence, so that there is no unique way of measuring moral responsibility.
Department of Philosophy & Institute for the History and Philosophy of Science and Technology, University of Toronto
On eclecticism in causal explanations
Traditionally, philosophical accounts have strived for a reductive framework for explicating causal explanation, where all explanations are supposed to be of one kind, e.g. constituted by counterfactual dependence, process of conserved quantities, or some kinds of mechanisms. These kinds of accounts are typically limited in scope and suffer from various counterexamples. I argue that this reductive approach is out of sync with scientific practice and everyday understanding of causal explanation and fails to take an appropriate account of the specific know-how that underlines causal explanation. I then propose an alternative approach, which seems to better support our understanding and practice of causal explanations, where causal explanations are eclectic in nature.
ICREA Research Professor University of Barcelona & Director of the Barcelona Institute for Analytic Philosophy
Humean Chance & Causation
Causality and objective probability are often linked, and the links may go in either direction. For example, some philosophers have tried to characterize objectively chancy setups as incomplete, partial causes of the various possible outcomes the setup may yield. Other philosophers have proposed probabilistic theories of causation, defining a cause c for an effect e as a factor whose presence raises the objective probability of e. I do not subscribe to any reductive or quasi-reductive link between causation and objective chance. Nonetheless, it is clear that there is some link between causation and probability. I propose that the strongest general principle that links causation and probability is a Cause-Probability Principle (CPP), which says (roughly) that when an agent learns that a cause c for an effect e has been introduced or put into action, then her subjective probability for the occurrence of e (if she has one!) should be at least as high as it was beforehand. (That is, should go up in general, and in any event not go down.) This principle is (I claim) the strongest general link that we can make between causation and probability.