Synthese

, Volume 175, Issue 2, pp 169–192 | Cite as

Actual causation: a stone soup essay

  • Clark Glymour
  • David Danks
  • Bruce Glymour
  • Frederick Eberhardt
  • Joseph Ramsey
  • Richard Scheines
  • Peter Spirtes
  • Choh Man Teng
  • Jiji Zhang
Article

Abstract

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) “neuron” and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required.

Once upon a time a hungry wanderer came into a village. He filled an iron cauldron with water, built a fire under it, and dropped a stone into the water. “I do like a tasty stone soup” he announced. Soon a villager added a cabbage to the pot, another added some salt and others added potatoes, onions, carrots, mushrooms, and so on, until there was a meal for all.

Keywords

Actual causation Bayesian networks Combinatorics Intervention Intuitions 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Clark Glymour
    • 1
  • David Danks
    • 1
  • Bruce Glymour
    • 2
  • Frederick Eberhardt
    • 3
  • Joseph Ramsey
    • 4
  • Richard Scheines
    • 4
  • Peter Spirtes
    • 4
  • Choh Man Teng
    • 5
  • Jiji Zhang
    • 6
  1. 1.Carnegie Mellon University and Florida Institute for Human and Machine CognitionPittsburghUSA
  2. 2.Kansas State UniversityManhattanUSA
  3. 3.Washington University in St. LouisSt. LouisUSA
  4. 4.Carnegie Mellon UniversityPittsburghUSA
  5. 5.Florida Institute for Human and Machine CognitionPensacolaUSA
  6. 6.Lingnan UniversityTuen MunHong Kong

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