Imaging Technology and the Philosophy of Causality

Philosophy and Technology 24 (2):115-136 (2011)
Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007) put forward the thesis that, at least in the health sciences, to establish the claim that C is a cause of E, one normally needs evidence of an underlying mechanism linking C and E as well as evidence that C makes a difference to E. This epistemological thesis poses a problem for most current analyses of causality which, in virtue of analysing causality in terms of just one of mechanisms or difference making, cannot account for the need for the other kind of evidence. Weber (Int Stud Philos Sci 23(2):277–295, 2009) has suggested to the contrary that Giere’s probabilistic analysis of causality survives this criticism. In this paper, we look in detail at the case of medical imaging technology, which, we argue, supports the thesis of Russo and Williamson, and we respond to Weber’s suggestion, arguing that Giere’s account does not survive the criticism
Keywords Causality  Causation  Difference making  Mechanism  Medical imaging
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DOI 10.1007/s13347-010-0010-7
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Jon Williamson (2009). Probabilistic Theories of Causality. In Helen Beebee, Peter Menzies & Christopher Hitchcock (eds.), The Oxford Handbook of Causation. Oxford University Press 185--212.
Federica Russo & Jon Williamson (2007). Interpreting Causality in the Health Sciences. International Studies in the Philosophy of Science 21 (2):157 – 170.
Jon Williamson (2007). Interpreting Causality in the Health Sciences. International Studies in the Philosophy of Science 21 (2):157-170.
James R. Kuehl (1970). Perceiving and Imaging. Philosophy and Phenomenological Research 31 (December):212-224.

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