Causal exclusion and causal Bayes nets

Journal for General Philosophy of Science, 2018

The overarching theme of the book is causality -the nature of the concept and its connection to other concepts. The book's content may be thematically subdivided into four parts. After an introductory Part I (chs. 1, 2), Part II (chs. 3, 4) puts forward a theory of causation, inspired by the causal Bayesian network (BN) formalism, where causation is understood as a theoretical concept implicitly defined by the theory's axioms, in analogy with scientific concepts. Part III (ch. 5) discusses Woodward's interventionist theory of causation. Part IV (ch. 6) applies causal BN tools to modelling mechanisms and constitutional relations.

International Philosophical Quarterly, 2013

Jaegwon Kim argues that if mental properties are irreducible with respect to physical properties, then mental properties are epiphenomenal. I believe that this conditional is false and argue that mental properties, along with their physical counterparts, may causally overdetermine their effects. Kim contends, however, that embracing causal overdetermination in the mental ease should be resisted for at least three reasons: (1) it is implausible, (2) it makes mental properties causally dispensable, and (3) it violates the Causal Closure Principle. I believe, however, that each of these reasons can be defeated. Moreover, further reflection on (3), according to Kim's implicit logic, may lend support to the claim that physical properties, and not mental properties, are in danger of losing their causal relevance. I. THE CAUSAL EXCLUSION ARGUMENT T HE TARGET OF KIM'S SO-CALLED Causal Exclusion Argument is the family of positions known as non-reductive physicalism. These positions share at least three cardinal commitments: (1) mental properties are distinct from and irreducible with respect to physical properties, (2) mental properties are causally efficacious, and (3) mental properties metaphysically supervene on physical properties. I will call these commitments: distinctness, efficacy, and supervenience, respectively. With this in mind, let's take a closer look at Kim's Causal Exclusion Argument. Suppose that there is a case of mental-to-mental causation between two different mental properties, M, and M^. According to supervenience we know that M^ must have a physical supervenience base P^ that guarantees M^'s instantiation. So we have the following two premises: (1) M, causes Mj (2) M^ has some physical property P^ as its supervenience base Kim notes that we are already confronted with a tension generated from the juxtaposition of (1) and (2). He writes: (1) and (2) together give rise to a tension when we consider the question "Why is [MJ instantiated on this occasion? What is responsible for, and explains, the fact that [MJ occurs on this occasion?" For there are two seemingly exclusionary answers: (a) "because [M,] caused [M^] to instantiate on this occasion," and (b) "Because [P^], a supervenience base of [M ] is instantiated on this occasion."'

Erkenntnis, 2008

This paper presents an attempt to integrate theories of causal processes -of the kind developed by Wesley Salmon and Phil Dowe -into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are rendered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques suffice to explain cases of late preëmption and other cases that have proved problematic for causal models.

Causal exclusion arguments are taken to threaten the autonomy of the special sciences, and the causal efficacy of mental properties. A recent line of response to these arguments has appealed to "independently plausible" and "well grounded" theories of causation to rebut key premises. In this paper I consider two papers which proceed in this vein and show that they share a common feature: they both require causes to be proportional (in Yablo's sense) to their effects. I argue that this feature is a bug, and one that generalises: any attempt to rescue the autonomy of the special sciences, or the efficacy of the mental, from exclusion worries had better not look to proportionality for help.

European Journal of Philosophy, 2002

In a series of influential articles (Kim 1989b(Kim , 1992b(Kim , 1993a(Kim and 1998, Jaegwon Kim has developed a strong argument against nonreductive physicalism as a plausible solution to mental causation. The argument is commonly called the 'causal exclusion argument', and it has become, over the years, one of the most serious threats to the nonreductivist point of view.

We start this paper by arguing that causality should, in analogy with force in Newtonian physics, be understood as a theoretical concept that is not explicated by a single definition, but by the axioms of a theory. Such an understanding of causality implicitly underlies the well-known theory of causal (Bayes) nets (TCN) and has been explicitly promoted by Glymour (Br J Philos Sci 55: [779][780][781][782][783][784][785][786][787][788][789][790] 2004). In this paper we investigate the explanatory warrant and empirical content of TCN. We sketch how the assumption of directed cause-effect relations can be philosophically justified by an inference to the best explanation. We then ask whether the explanations provided by TCN are merely post-facto or have independently testable empirical content. To answer this question we develop a fine-grained axiomatization of TCN, including a distinction of different kinds of faithfulness. A number of theorems show that although the core axioms of TCN are empirically empty, extended versions of TCN have successively increasing empirical content.

Synthese Library, 2017

This monograph looks at causal nets from a philosophical point of view. The author shows that one can build a general philosophical theory of causation on the basis of the causal nets framework that can be fruitfully used to shed new light on philosophical issues. Coverage includes both a theoretical as well as application-oriented approach to the subject. The author first counters David Hume’s challenge about whether causation is something ontologically real. The idea behind this is that good metaphysical concepts should behave analogously to good theoretical concepts in scientific theories. In the process, the author offers support for the theory of causal nets as indeed being a correct theory of causation. Next, the book offers an application-oriented approach to the subject. The author shows that causal nets can investigate philosophical issues related to causation. He does this by means of two exemplary applications. The first consists of an evaluation of Jim Woodward’s interventionist theory of causation. The second offers a contribution to the new mechanist debate. Introductory chapters outline all the formal basics required. This helps make the book useful for those who are not familiar with causal nets, but interested in causation or in tools for the investigation of philosophical issues related to causation. Citation information: Gebharter, A. (2017). Causal nets, interventionism, and mechanisms: Philosophical foundations and applications. Synthese Library 381. Cham: Springer. doi:10.1007/978-3-319-49908-6

2007

This paper presents an attempt to integrate theories of causal processes - of the kind developed by Wesley Salmon and Phil Dowe - into a theory of causal models using Bayesian networks. We suggest that arcs in causal models must correspond to possible causal processes. Moreover, we suggest that when processes are ren- dered physically impossible by what occurs on distinct paths, the original model must be restricted by removing the relevant arc. These two techniques su ce to explain cases of late preëmption and other cases that have proved problematic for causal models.

In this paper we show that the application of Occam's razor to the theory of causal Bayes nets gives us a neat definition of direct causation. In particular we show that Occam's razor implies definition of direct causation, provided suitable intervention variables exist and the causal Markov condition (CMC) is satisfied. We also show how Occam's razor can account for direct causal relationships Woodward style when only stochastic intervention variables are available.