Causal Models and the Ambiguity of Counterfactuals

In Wiebe van der Hoek, Wesley H. Holliday & Wen-Fang Wang (eds.), Logic, Rationality, and Interaction 5th International Workshop, LORI 2015, Taipei, Taiwan, October 28-30, 2015. Proceedings. Springer. pp. 201-229 (2015)
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Counterfactuals are inherently ambiguous in the sense that the same counterfactual may be true under one mode of counterfactualization but false under the other. Many have regarded the ambiguity of counterfactuals as consisting in the distinction between forward-tracking and backtracking counterfactuals. This is incorrect since the ambiguity persists even in cases not involving backtracking counterfactualization. In this paper, I argue that causal modeling semantics has the resources enough for accounting for the ambiguity of counterfactuals. Specifically, we need to distinguish two types of causal manipulation, which I call “intervention” and “extrapolation” respectively. To intervene in a causal model M is to change M’s structural equations in some specific ways, while to extrapolate M is to change the value assignment of M’s variables in some specific ways. I argue that intervention and extrapolation offer a natural explanation for the ambiguity of counterfactuals.



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Kok Yong Lee
National Chung Cheng University

References found in this work

Constraints for Input/Output Logics.David Makinson & Leendert van der Torre - 2001 - Journal of Philosophical Logic 30 (2):155 - 185.
Permission from an Input/Output Perspective.David Makinson & Leendert van der Torre - 2003 - Journal of Philosophical Logic 32 (4):391 - 416.

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