A Ranking-theoretic Account of Deterministic Causation

Note from the organiser: The technical background for this talk will be the paper "Causation: An Alternative" (British Journal for the Philosophy of Science 57, 2006).

Abstract of "Causation: An Alternative"

The paper builds on the basically Humean general idea that A is a cause of B iff A and B both occur, A precedes B, and A raises the metaphysical or epistemic status of B given the obtaining circumstances. It argues that in pursuit of a theory of deterministic causation this 'status raising' is best explicated not in regularity or counterfactual terms, but in terms of ranking functions. On this basis, it constructs a rigorous theory of deterministic causation that successfully deals with cases of overdetermination and preemption. It finally indicates how the account's profound epistemic relativization induced by ranking theory can be undone.

July 9, 2010 / 4.00 p.m. / LMU Munich (M210)


Graphs as Models of Interventions

Note: The title of this talk is taken from the programmatic section 2.2 of Judea Pearl's paper "Causal Diagrams for Empirical Research" (Biometrika, Vol. 82, No. 4, 669-709, 1995) which will be presented and commented on as an introduction to Pearl's interventionist account of causal analysis. The paper can be downloaded as item R-218-B from Pearl's website.

July 9, 2010 / 9.15 a.m. / LMU Munich (M210)


Causation in Physics

According to a widespread view, causal notions have no legitimate role to play in mature physical theorizing. This view, which can be traced back to Russell’s famous attack on the notion of cause, has proponents even among those who, like proponents of interventionist and Bayes Net accounts of causation, believe that causal notions have an important place in the special sciences and in our folk conception of the world.  In this talk I critically examine a range of general arguments for the view and discuss a case of causal modeling in physics - linear response theory.

July 9, 2010 / 11.25 a.m. / LMU Munich (M210)

Currently Mathias Frisch is conducting research at the Seminar for Philosophy, Logic and Philosophy of Science at LMU Munich as a Humboldt Scholar.
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Causality and Observational Equivalence of Deterministic and Indeterministic Descriptions

In this talk I present results on the observational equivalence of deterministic descriptions and indeterministic descriptions. These results show that there is a choice between a deterministic and an indeterministic description. Thus the question arises: which description is preferable relative to evidence? If none of them is preferable, this would amount to underdetermination. I criticise the extant philosophical answers to this question and propose a new answer. Then I assess the implications of the results on observational equivalence on accounts of causality, focusing on the example of billiard systems. In particular, I discuss the implications for accounts of causality which require that causality has to be deterministic, and I examine whether the Causal Markov condition holds for the indeterministic descriptions.

July 9, 2010 / 2.40 p.m. / LMU Munich (M210)
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The Causal Chain Problem

This talk addresses a problem that arises when it comes to inferring deterministic causal chains from pertinent empirical data. It will be shown that to every deterministic chain there exists an empirically equivalent common cause structure. Thus, our overall conviction that deterministic chains are one of the most ubiquitous (macroscopic) causal structures is underdetermined by empirical data. It will be argued that even though the chain and its associated common cause model are empirically equivalent there exists an important asymmetry between the two models with respect to model expansions. This asymmetry might constitute a basis on which to disambiguate corresponding causal inferences on non-empirical grounds.

July 9, 2010 / 1.20 p.m. / LMU Munich (M210)
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Modelling Experimental Interventions: Results and Challenges

In this talk I discuss probabilistic models of experimental intervention, and I show that such models elucidate the intuition that observations following intervention are more informative than observations per se. Because of this success, it seems attractive to also cast other problems from the philosophy of experiment in terms of probabilistic models. However, a critical examination of the models reveals that they obscure certain aspects of experimentation, to do with the externalist character of experimental knowledge and the notion of agency involved in framing experimental findings.

July 9, 2010 / 10.05 a.m. / LMU Munich (M210)
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