The Causal Autonomy of the Special Sciences

In Cynthia Macdonald & Graham Macdonald (eds.), Emergence in Mind. Oxford University Press (2010)
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The systems studied in the special sciences are often said to be causally autonomous, in the sense that their higher-level properties have causal powers that are independent of those of their more basic physical properties. This view was espoused by the British emergentists, who claimed that systems achieving a certain level of organizational complexity have distinctive causal powers that emerge from their constituent elements but do not derive from them.2 More recently, non-reductive physicalists have espoused a similar view about the causal autonomy of specialscience properties. They argue that since these properties can typically have multiple physical realizations, they are not identical to physical properties, and further they possess causal powers that differ from those of their physical realizers.3 Despite the orthodoxy of this view, it is hard to find a clear exposition of its meaning or a defence of it in terms of a well-motivated account of causation. In this paper, we aim to address this gap in the literature by clarifying what is implied by the doctrine of the causal autonomy of special-science properties and by defending the doctrine using a prominent theory of causation from the philosophy of science. The theory of causation we employ is a simplified version of an “interventionist” theory advanced by James Woodward (2003, forthcoming a, b), according to which a cause makes a counterfactual difference to its effects. In terms of this theory, it is possible to show that a special-science property can make a difference to some effect while the physical property that realizes it does not. Although other philosophers have also used counterfactual analyses of causation to argue for the causal autonomy of special-science properties,4 the theory of causation we employ is able to establish this with an unprecedented level of precision..
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Explaining the Brain.Craver, Carl F.
Causation, Prediction, and Search.Spirtes, Peter; Glymour, Clark & Scheines, Richard

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