Not by contingency: Some arguments about the fundamentals of human causal learning

Abstract

The power PC theory postulates a normative procedure for making causal inferences from contingency information, and offers this as a descriptive model of human causal judgement. The inferential procedure requires a set of assumptions, which includes the assumption that the cause being judged is distributed independently of the set of other possible causes of the same outcome. It is argued that this assumption either never holds or can never be known to hold. It is also argued that conformity of judgements to the prescriptions of the model requires a sophisticated appreciation of methodological factors and acquired domain-specific knowledge of causes, and that the theory is disconfirmed by a finding that an objective contingency that equally supports two causal inferences results in only one of them actually being made. An alternative proposal based on the hypothesis that causal understanding originates with experiences of forces exerted while acting on objects is briefly sketched.

Keywords:

• Causal learning
• Causal inference
• Force perception
• Haptic perception

Notes

¹A reviewer pointed out that the requirement of prior causal knowledge need not, in itself, be damaging to the power PC theory so long as the prior knowledge is different from the causal claims it is used to establish. This is correct: given the assumptions of the theory, the inferential procedure can be used to build on existing causal knowledge. The point is that it cannot be used to acquire new causal beliefs without existing causal knowledge of the kind described.

²It would be going too far to claim that the mechanoreceptor system provides infallible knowledge of mechanics in actions on objects: nothing could be that good. But, in the absence of neurological deficits, it is hard to imagine how failings could occur, unless the actor was so distracted as not to notice the information being supplied by the mechanoreceptor system. Skin pressure sensors are extraordinarily sensitive and only the lightest imaginable touch would elude them. Thus, while not infallible, the mechanoreceptor system is a great deal more trustworthy than inferences about relations between actions and secondary consequences, and beliefs about the nature of willed action, as the research by Wegner and colleagues discussed earlier in the paper appears to show. If degree of trustworthiness is what matters for the ontogenesis of causal knowledge, the mechanoreceptor system is the clear winner.

³An understanding in terms of mechanisms does not necessarily mean a thorough and complete understanding. In fact there is evidence that the mechanism beliefs that people have are often simple, incomplete, and prone to error (Rozenblit & Keil, 2002). It is possible that notions of mechanism can be modelled with causal Bayes nets (e.g., Pearl, 2000). But, while causal Bayes nets aspire to being normative accounts of elucidating the structure of causal systems, which means placing components in relation to each other according to the causal connections between them, such analyses have little to say about the concept of causality that underpins mechanism-based understanding. It also remains unclear whether they would work as descriptive accounts of human reasoning about causal structures (Steyvers, Tenenbaum, Wagenmakers, & Blum 2003; White, 2006c).