SSIS Postgraduate Conference, Exeter, 1 May 2015 Cause, Causatives, and Theories of Causation Julian Reiss, Durham Background ❖ ❖ ❖ ❖ Main concern: Provide a satisfactory account of causation in the sciences My own work focuses on the biomedical and social sciences Previously: detailed examination of the methods of causal inference in these sciences Here: taking a closer look at the causal language that is employed in science, taking cancer causation as a main case study Background ❖ Two things: ❖ Take scientific language at face value ❖ (Instead of starting with metaphysical intuitions and developing a theory that satisfies the given constraints) ❖ Main target: Any attempt to explicate causation by means of ‘C causes E iff “…”’ ❖ ‘Straightjacket Theories of Causation’ ❖ No matter what is on the RHS of the definition ❖ In particular (for instance) whether or not ‘cause’ appears Feature 1: Indispensability of Causatives ❖ ❖ ❖ ❖ ❖ Feature 1: Scientific language is full of causatives such as push, bond, attract, crunch, deflate ‘To buy’ = Toprolong, cause dampen, to acquire? To cause to establish Familiar from Anscombe and Cartwright ownership? To cause to have ownership? A problem: it’s not clear that you can always translate these into To cause to have ownership by ‘cause + x’ (buy) transferring money? cause to ownershiptheory: by This does constituteTo a problem forhave the straightjacket they cannot account for the large majority of causal claims in science causing someone to have . money? (‘Cause’ itself is used quite rarely!) C andMetaphysical E must be distinct events––and Feature 2: distinct not only in the sense of nonidentity but also in the sense of Anarchy nonoverlap and nonimplication. It won’t ❖ ❖ do to say that my speaking this Straightjacket Theories often necessitate the assumption of further metaphysical sentence causes my speaking this principles (e.g., counterfactual theory); e.g.: sentence, or that my speaking the ❖ Independent events whole of it causes my speaking the first half of it, or vice versa; or that my ❖ No absence causation speaking it causes my speaking it ❖ Causal order is identical to temporal order loudly, or vice versa. Feature 2: Scientific language is extremely flexible with respect to the C’s and E’s that are being causally related or indeed with respect to what is represented by a causal claim ❖ Hypothesis: there is no general metaphysical principle to which one cannot find a counterexample ❖ So ‘C φs E’, where φ is a causative, doesn’t work either ❖ A theory of causation must be a theory of causal claims Feature 3: Polysemy ❖ The third feature is that causatives are polysemous ❖ Some can be causally nonWith causatives these considerations in used mind, both it is essential to and determine causally whether the use of PREPS [potential-reduced exposure products] ❖ ❖ actually lowers carcinogen dose. What they depends on context (Hecht 2002,mean ‘Biomarkers For Investigating Tobacco and Cancer’) Therefore: a theory of causation must be a theory of causal claims in a context 🍸 Interval 🍸 ❖ The ‘Straightjacket Theory of Causation’: context iff “…”’ ‘C causes E in iff a“…”’ ❖ Indispensable causatives ❖ Metaphysical anarchy ❖ Polysemy A pluralist truth-conditional theory? What are the chances of providing truth conditions for a complex statement such as ‘[Claim using φ-causative] in context K’ iff…? ❖ I have no knock-down argument against it but doubt whether it can be done ❖ Q&A if you want to know more ❖ An Alternative: Inferentialism ❖ Main idea: ❖ Causation and inference are clearly related ❖ (Justified/accepted) Causal claims, in conjunction with other knowledge such as observations, license inferences to future and past states of affairs ❖ Observations, in conjunction with background knowledge, license inferences to causal claims ❖ Proposal: The content of causal claims consists in the inferential network of which they are a part ❖ Essentially: the content of a causal claim is given by the set of propositions from which it follows and those which follow from it Inferential systems ❖ More precisely: The content of a causal claim is given by its inferential system; that is, by the propositions from which an epistemic community is entitled to infer the causal claim, and those the community is entitled to infer from it ❖ Divides into ‘inferential base’, ‘inferential target’ and causal claim CC itself ❖ Inferential base: essentially, the evidence – RCTs, controlled experiments, statements describing experimental design, observational studies, statements describing how confounders and biases are ruled out, background knowledge etc. Evidence ❖ I can only sketch the story here ❖ Roughly, ask: under what conditions are we justified in inferring a causal claim from the evidence? ❖ Answer, roughly: when there is a study that uses a reliable method and shows the claim to hold ❖ Experimental methods often achieve reliability by design; but even they have to be checked for confounders, biases ❖ Observational methods achieve reliability to the extent that alternative accounts can be ruled out ❖ All this is highly context dependent Inferential Targets ‘Inferential EC EC EC claims ❖ Causal their own sake EC EC are rarely established for system-CC’ EC EC ❖ Rather, for the cash value: EC EC EC EC EC ❖ explanations EC EC ❖ CC attributions of blame and praise EC EC EC EC EC ❖ predictions EC EC ❖ TC TC TC TC TC TC TC propositions about effective strategies EC Context EC EC EC EC EC EC the content of a causal claim, ask: What is its ❖ To determine inferential system? Inferential base Inferential target Causal Redundancy Here is an example of how the account works Cause ❖ What is the content of a sentence such as ‘Billy’s throw caused the iPad to shatter?’ ❖ Ask: what is the inferential system of the sentence? Outcome ❖ Answer ❖ Inferential base: critical observation Backup Cause ❖ That is: observation plus critical background assumptions that are contextually justified ❖ Causal Redundancy ❖ Inferential target (e.g.): Smoking ❖ Billy is responsible; Billy’s throw explains the shattering; CompenLung ❖ BUT NOT: Had Billy not thrown, the iPad wouldn’t have sation Cancer shattered ❖ ❖ Why? We’re entitled to infer the counterfactual only in Asbestos contexts where there are no backup causes (among other things)! Conclusions ❖ By way of concluding, let me point out how the account deals with the three features about causal language in science ❖ Feature 1: Indispensability of causatives ❖ It makes no difference between sentences in which ‘cause’ appears and those in which it doesn’t ❖ For any sentence in a scientific publication we can ask, ‘What is the inferential system for this sentence?’ ❖ Neither does ‘cause’ vs causative make a principled difference, nor whether the sentence is a causal claim at all (though: the inferential networks of predictive sentences, for instance, may be a lot harder to understand) Conclusions ❖ ❖ Feature 2: Metaphysical anarchy ❖ As causation has to do with our reasoning practices and not with what the world is like, anything goes metaphysically speaking ❖ The account, as presented here, can be underwritten by a realist metaphysics (which would mean that a representationalist account would eventually have to be found) or by anti-realism (the option I favour but don’t presuppose) ❖ No general metaphysical principles are assumed Feature 3: Polysemy ❖ There is no difference-in-principle between causal and non-causal claims; to what extent a claim is causal depends on family resemblance of inferential systems ❖ And family resemblance is much more than hand-waving in this case: we know the typical kinds of proposition in inferential base and target