In this paper I offer an analysis of causation based upon a theory of mechanisms-complex systems whose internal parts interact to produce a system's external behavior. I argue that all but the fundamental laws of physics can be explained by reference to mechanisms. Mechanisms provide an epistemologically unproblematic way to explain the necessity which is often taken to distinguish laws from other generalizations. This account of necessity leads to a theory of causation according to which events are causally related when (...) there is a mechanism that connects them. I present reasons why the lack of an account of fundamental physical causation does not undermine the mechanical account. (shrink)

In this paper I present both a critical appraisal of Humphreys' probabilistic theory of causality and a sketch of an alternative view of the relationship between the notions of probability and of cause. Though I do not doubt that determinism is false, I claim that the examples used to motivate Humphreys' theory typically refer to subjective rather than objective chance. Additionally, I argue on a number of grounds that Humphreys' suggestion that linear regression models be used as a canonical form (...) for the description of causal relations is untenable. I conclude by exploring the variety of ways in which probabilistic elements can be embedded into the structure of causal mechanisms. This investigation suggests both that deterministic mechanisms can produce stochastic behavior and stochastic mechanisms can produce deterministic behavior. Note: Link is to the article in a subscription database available to users affiliated with Butler University. Appropriate login information will be required for access. Users not affiliated with Butler University should contact their local librarian for assistance in locating a copy of this article. (shrink)

A number of developmental psychologists have argued for a theory they call the theory theory - a theory of cognitive development that suggests that infants and small children make sense of their world by constructing cognitive representations that have many of the attributes of scientific theories. In this paper I argue that there are indeed close parallels between the activities of children and scientists, but that these parallels will be better understood if one recognizes that both scientists and children are (...) not so much theorists as model builders. (shrink)

In this paper I discuss Searle's claim that the computational properties of a system could never cause a system to be conscious. In the first section of the paper I argue that Searle is correct that, even if a system both behaves in a way that is characteristic of conscious agents (like ourselves) and has a computational structure similar to those agents, one cannot be certain that that system is conscious. On the other hand, I suggest that Searle's intuition that (...) it is “empirically absurd” that such a system could be conscious is unfounded. In the second section I show that Searle's attempt to show that a system's computational states could not possibly cause it to be conscious is based upon an erroneous distinction between computational and physical properties. On the basis of these two arguments, I conclude that, supposing that the behavior of conscious agents can be explained in terms of their computational properties, we have good reason to suppose that a system having computational properties similar to such agents is also conscious. (shrink)

In this paper I offer a criticism of Carnap's inductive logic which also applies to other formal methods of inductive inference. Criticisms of Carnap's views have typically centered upon the justification of his particular choice of inductive method. I argue that the real problem is not that there is an agreed upon method for which no justification can be found, but that different methods are justified in different circumstances.