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Indicative and counterfactual conditionals: a causal-modeling semantics

  • Conditionals: Truth Conditions, Probability, and Causality
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Abstract

We construct a causal-modeling semantics for both indicative and counterfactual conditionals. As regards counterfactuals, we adopt the orthodox view that a counterfactual conditional is true in a causal model M just in case its consequent is true in the submodel \(M^*\), generated by intervening in M, in which its antecedent is true. We supplement the orthodox semantics by introducing a new manipulation called extrapolation. We argue that an indicative conditional is true in a causal model M just in case its consequent is true in certain submodels \(M^*\), generated by extrapolating M, in which its antecedent is true. We show that the proposed semantics can account for some important minimal pairs nicely and naturally. We also prove a theorem showing under what conditions intervention and extrapolation will yield the same result, and thus explain how counterfactual and indicative conditionals would behave in a causal-modeling semantics.

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Notes

  1. Some propose a semantically unified treatment of indicatives and counterfactuals (Stalnaker 1975; Ellis 1978; Davis 1979; Edgington 1995; Lycan 2001; Khoo 2015), while others disagree (cf. Lewis 1973; Gibbard 1981; Bennett 2003).

  2. Our default position is in stark contrast to a very influential view, according to which indicatives do not express propositions and lack truth values (cf. Adams 1970; Gibbard 1981; Edgington 1995; Bennett 2003). For simplicity’s sake, we will not address this issue here.

  3. The following formulation is influenced by Pearl (2000) and Briggs (2012). Hiddleston (2005) has constructed a different type of causal-modeling semantics. See Lee (2017) for a recent, related discussion of Hiddleston’s semantics.

  4. For the assignment function, see Hiddleston (2005) and Briggs (2012). For a more complicated account, see Deng (2016).

  5. Part of the reason why we call this second way of manipulating a causal model ‘extrapolation’ is that this way of manipulation bears some similarity to mathematical extrapolation, which is to estimate the value of a variable based on its relationship to other variables.

  6. Galles and Pearl’s original semantics in Galles and Pearl (1998) has limited expressive power. In particular, they consider only counterfactuals of the form ‘\((A_1=a_1 \wedge \cdots \wedge A_n=a_n) > (C_1=c_1 \wedge \cdots \wedge C_m=c_m)\)’. Halpern (2000) has developed a semantics for counterfactuals that allows the consequent to be any Boolean combination of sentences of the form ‘\(C_i = c_i\)’. Briggs (2012) further extends the semantics to allow the antecedent to be any Boolean combination of sentences of the form ‘\(A_i = a_i\)’, and also to allow some nested counterfactuals of the form ‘\(A> (B > C)\)’. For simplicity’s sake, we will follow Pearl in assuming that the sentences involved in intervention (and extrapolation) consist only of conjunctions.

  7. A noticeable exception is Lee (2015, 2016).

  8. In a loose sense as specified above, this condition requires that \(A^*(C_1) = c_1\), ..., and \(A^*(C_m) = c_m\).

  9. The case is borrowed (with modifications) from Bennett (2003, p. 342). Gibbard (1981, pp. 231–32) proposes an influential case of the truth value (or at least the acceptability) of an indicative being dependent on information available to the subject’s evidence.

  10. As Williamson correctly points out, “[the value of Lewis’s semantics] is not to enable one to determine whether a counterfactual is true in a given case by applying one’s general understanding of similarity to various possible worlds, without reference to counterfactuals themselves. If one tried to do that, one would almost certainly give the wrong comparative weights to the various relevant respects of similarity. Nevertheless, the semantics gives valuable structural information about counterfactuals, in particular about their logic” (Williamson 2009, p. 9).

  11. The ‘totality’ assumption may cause some worries. We may also drop it and formulate our definition with a preorder, but it will make our definitions unnecessarily complicated. So, in this paper, we will work with a total preorder.

  12. We here assume that each deviance from the actual value assigned in the original model M has an equal weight. This can be easily modified in cases where the variables take quantitative values.

  13. Notice that for any submodels \(M_1\) and \(M_2\) in \({\mathbb {M}}^{[\varphi ]}\) and any variable X, our definition guarantees a trichotomy, i.e., exactly one of the three, \(A_1<_X A_2\), \(A_1\approx _X A_2\), and \(A_2<_X A_1\), should hold.

  14. See “Appendix 1” for a proof that \(\le \) is a total preorder on \({\mathbb {M}}^{[\varphi ]}\).

  15. Notice that a totally preordered set may not have a unique minimal element. For it can happen that C contain two (or more) minimal elements a and b, such that \(a\le b\) and \(b\le a\) both hold. But if C is a finite non-empty set, it is guaranteed that C has at least one minimal element.

  16. The setting of this example is inspired by a case of Bennett (2003, pp. 345–346). But the structures of these two cases are different.

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Acknowledgements

The authors of this paper contributed equally to it. Earlier versions of this paper had been presented at Taiwan Philosophical Association (TPA) Conference at Tunghai University, Taichung (November 2016) and the American Philosophical Association (APA) Conference (Eastern Division), Savannah (January 2018). We want to thank all the participants for comment and discussion. We are especially thankful for the invaluable comments given by our commentators Linton Wang (TPA) and Simon Goldstein (APA), and anonymous referees of this journal and others. Both authors acknowledge financial support from the Ministry of Science and Technology of Taiwan (R.O.C.) with grant numbers MOST 108-2410-H-002-017-MY2 (Duen-Min Deng) and MOST 109-2410-H-194-105 (Kok Yong Lee).

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Appendices

Appendix 1: Proof that \(\le \) is a total preorder on \({\mathbb {M}}^{[\varphi ]}\)

Recall our definition:

Definition

Let \(M=\langle U, V, F, A\rangle \) be a causal model, and \({M_{1}}=\langle U, V, F, A_{1}\rangle \) and \({M_{2}}=\langle U, V, F, A_{2}\rangle \) be submodels in \({\mathbb {M}}^{[\varphi ]}\). Define \(M_1\sqsubseteq M_2\) if and only if either of the two conditions holds:

  1. (i)

    for every \(X\in U\cup V\), \(A_1\approx _X A_2\), or

  2. (ii)

    for some \(X\in U\cup V\), \(A_1<_X A_2\), and for any \(Y\in U\cup V\) such that \(X\prec Y\), \(A_1\approx _Y A_2\).

We then define \(\le \) to be the transitive closure of \(\sqsubseteq \).

Proof

It suffices to show that \(\sqsubseteq \) is a total relation on \({\mathbb {M}}^{[\varphi ]}\). To show this, consider any submodels \(M_1=\langle U, V, F, A_1\rangle \) and \(M_2=\langle U, V, F, A_2\rangle \) in \({\mathbb {M}}^{[\varphi ]}\). If condition (i) holds, then clearly both \(M_1\sqsubseteq M_2\) and \(M_2\sqsubseteq M_1\) hold. Now, suppose condition (i) does not hold. So, for some \(X\in U\cup V\), \(A_1\not \approx _X A_2\), and hence if we define \(N=\{X\in U\cup V\mid A_1\not \approx _X A_2\}\) then N is non-empty. Now, since \(\preccurlyeq \) is a total preorder on a finite set \(U\cup V\), there is some X in N such that for any \(Y\in N\), \(Y\preccurlyeq X\). Hence, for any \(Y\in U\cup V\) such that \(X\prec Y\), we have \(Y\notin N\), i.e., \(A_1\approx _Y A_2\). But since \(X\in N\), \(A_1\not \approx _X A_2\), and so either \(A_1 <_X A_2\) or \(A_2 <_X A_1\) (by the definition of \(<_X\)). Hence, either \(M_1\sqsubseteq M_2\) or \(M_2\sqsubseteq M_1\). \(\square \)

Remark

Notice that it is necessary to take the transitive closure, for the relation \(\sqsubseteq \) as defined by (i) and (ii) above is not guaranteed to be transitive. This can be shown by a simple example. Consider a causal model M which contains only three variables, X, Y, and Z, with the following value assignments: \(A(X)=A(Y)=A(Z)=0\). Suppose our priority relation is given as follows:

$$\begin{aligned} X\prec Y\approx Z \end{aligned}$$

Suppose that \({\mathbb {M}}^{[\varphi ]}\) contains three submodels, \(M_1\), \(M_2\), and \(M_3\), such that

$$\begin{aligned}&A_1(X)=1, A_1(Y)=1, A_1(Z)=0 \\&A_2(X)=0, A_2(Y)=0, A_2(Z)=1 \\&A_3(X)=0, A_3(Y)=1, A_3(Z)=0 \end{aligned}$$

It is easy to check that according to our definition, the relation \(\sqsubseteq \) applies to any pair of the three submodels except \(\langle M_1, M_3\rangle \). That is to say, we have \(M_1\sqsubseteq M_2\sqsubseteq M_3\), but not \(M_1\sqsubseteq M_3\). Hence \(\sqsubseteq \) may fail to be transitive.

Appendix 2: Proof of the Theorem

Lemma 1

Let \(M=\langle U, V, F, A\rangle \) be a causal model, and \(M_{(\varphi )}=\langle U_{(\varphi )}, V_{(\varphi )}, F_{(\varphi )}, A_{(\varphi )}\rangle \) be its intervention-generated submodel. Then for any variable X, if \(X\notin {\mathcal {D}}{\mathcal {E}}(V\varphi )\), then \(A_{(\varphi )}(X)=A(X)\).

Proof

Since we assume that M is recursive, the value of each variable X can be uniquely traced back to the values of those exogenous variables in \({\mathcal {A}}{\mathcal {N}}(X)\). But if \(X\notin {\mathcal {D}}{\mathcal {E}}(V\varphi )\), then \({\mathcal {A}}{\mathcal {N}}(X)\) should contain no variable in \(V\varphi \), and hence \(A_{(\varphi )}\) should assign the same value to each variable in \(U_{(\varphi )}\cap {\mathcal {A}}{\mathcal {N}}(X)\) as A does. Hence \(A_{(\varphi )}(X)=A(X)\). \(\square \)

Lemma 2

Let \(M=\langle U, V, F, A\rangle \) be a causal model such that \({\mathbb {M}}^{[\varphi ]}\ne \emptyset \). Then there is a submodel \(M_0=\langle U, V, F, A_0\rangle \in {\mathbb {M}}^{[\varphi ]}\) such that for any \(X\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\) we have \(A_0(X) = A(X)\).

Proof

Since \({\mathbb {M}}^{[\varphi ]}\ne \emptyset \), there is some submodel \(M^*=\langle U, V, F, A^*\rangle \in {\mathbb {M}}^{[\varphi ]}\). Now, let \(M_0=\langle U, V, F, A_0\rangle \) be the submodel such that \(A_0(X)=A^*(X)\) for any \(X\in U \cap {\mathcal {A}}{\mathcal {N}}(V\varphi )\), and \(A_0(X)=A(X)\) for any \(X\in U \setminus {\mathcal {A}}{\mathcal {N}}(V\varphi )\). Now, since M is recursive, it follows that \(A_0(X)=A^*(X)\) for any \(X\in V\varphi \), and \(A_0(X) = A(X)\) for any \(X\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\). Hence \(M_0\) is a submodel in \({\mathbb {M}}^{[\varphi ]}\) with the desired property. \(\square \)

Theorem

Let \(M=\langle U, V, F, A\rangle \) be a causal model such that \({\mathbb {M}}^{[\varphi ]}\ne \emptyset \). Suppose there is a set \(S\subseteq U\cup V\) such that (i) \(S\cap {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))=\emptyset \), (ii) \(S\cup V\varphi \) is a screen to \(V\psi \), i.e., for each initial chain C that leads to a variable in \(V\psi \), we have \(C\cap (S\cup V\varphi )\ne \emptyset \), and (iii) for any \(X\in {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\) and any \(Y\in S\), we have \(X\prec Y\). Then \(\varphi >\psi \) is true in M if and only if \(\varphi \rightarrow \psi \) is true in M.

Proof

Since \({\mathbb {M}}^{[\varphi ]}\ne \emptyset \), by Lemma 2 there is an \(M_0=\langle U, V, F, A_0\rangle \in {\mathbb {M}}^{[\varphi ]}\) such that for any \(X\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\) we have \(A_0(X) = A(X)\). Now, we claim that every minimal submodel in \({\mathbb {M}}^{[\varphi ]}\) agrees with \(M_0\) on the truth value of \(\psi \). For suppose the claim is false, then there is a minimal submodel \(M^*=\langle U, V, F, A^*\rangle \in {\mathbb {M}}^{[\varphi ]}\) and some variable \(X\in V\psi \) such that \(A^*(X) \ne A_0(X)\). Now, since \(S\cup V\varphi \) is a screen to X, any two submodels of M that agree on the values of all variables in \(S\cup V\varphi \) should also agree on the value of X. But \(A^*(X) \ne A_0(X)\), it follows that for some \(Y\in S\cup V\varphi \), we have \(A^*(Y) \ne A_0(Y)\). Clearly, for any \(Z\in V\varphi \), we have \(A_0(Z) = A^*(Z) = A_{(\varphi )}(Z)\), because \(\varphi \) is true in \(M_0\) and in \(M^*\) and in \(M_{(\varphi )}\). So, \(Y\notin V\varphi \), and hence \(Y\in S\). But \(S\cap {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))=\emptyset \), so \(Y\in S\) implies \(Y\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\), and hence we have \(A_0(Y) = A(Y)\). So, we have \(A_0 <_Y A^*\). Now, since for any \(Z\in {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\) and \(Y\in S\), we have \(Z\prec Y\), it follows that for any Z such that \(Y\preccurlyeq Z\), we have \(Z\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\), and hence \(A_0(Z) = A(Z)\). This implies that for any Z such that \(Y\preccurlyeq Z\), \(A_0 \lessapprox _Y A^*\), and consequently, we have \(M_0 < M^*\), which contradicts the assumption that \(M^*\) is a minimal submodel.

According to (CC), \(\varphi > \psi \) is true in M iff \(\psi \) is true in \(M_{(\varphi )}\). Now, we claim that \(\psi \) is true in \(M_{(\varphi )}\) iff \(\psi \) is true in \(M_0\). To show this, first observe that for any \(X\in S\), we have \(X\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\), and hence \(A_0(X) = A(X)\). But since \({\mathcal {D}}{\mathcal {E}}(V\varphi )\subseteq {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\), it follows that \(X\notin {\mathcal {D}}{\mathcal {E}}({\mathcal {A}}{\mathcal {N}}(V\varphi ))\) implies \(X\notin {\mathcal {D}}{\mathcal {E}}(V\varphi )\), and hence by Lemma 1, we have \(A_{(\varphi )}(X) = A(X)\). So, \(M_{(\varphi )}\) and \(M_0\) agree on the values of all variables in S. Now, since \(S\cup V\varphi \) is a screen to \(V\psi \), any two submodels of M that agree on the values of all variables in \(S\cup V\varphi \) should also agree on the value of any variable in \(V\psi \). But certainly, \(M_{(\varphi )}\) and \(M_0\) agree on the values of all variables in \(V\varphi \) (since \(\varphi \) is true in both), and we have shown that they also agree on the values of all variables in S. Consequently, \(M_{(\varphi )}\) and \(M_0\) should also agree on the truth value of \(\psi \). Since we have shown that every minimal submodel in \({\mathbb {M}}^{[\varphi ]}\) agrees with \(M_0\) on the truth value of \(\psi \), and according to (IC), \(\varphi \rightarrow \psi \) is true in M iff \(\psi \) is true in every minimal submodel in \({\mathbb {M}}^{[\varphi ]}\), it follows that \(\varphi \rightarrow \psi \) is true in M iff \(\psi \) is true in \(M_0\). Hence, we can conclude that \(\varphi > \psi \) is true in M iff \(\varphi \rightarrow \psi \) is true in M. \(\square \)

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Deng, DM., Lee, K.Y. Indicative and counterfactual conditionals: a causal-modeling semantics. Synthese 199, 3993–4014 (2021). https://doi.org/10.1007/s11229-020-02966-9

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