We model scientific theories as Bayesian networks. Nodes carry credences and function as abstract representations of propositions within the structure. Directed links carry conditional probabilities and represent connections between those propositions. Updating is Bayesian across the network as a whole. The impact of evidence at one point within a scientific theory can have a very different impact on the network than does evidence of the same strength at a different point. A Bayesian model allows us to envisage and analyze the (...) differential impact of evidence and credence change at different points within a single network and across different theoretical structures. (shrink)

Most social policies cannot be defended without making inductive inferences. For example, consider certain arguments for racial profiling and affirmative action, respectively. They begin with statistics about crime or socioeconomic indicators. Next, there is an inductive step in which the statistic is projected from the past to the future. Finally, there is a normative step in which a policy is proposed as a response in the service of some goal—for example, to reduce crime or to correct socioeconomic imbalances. In comparison (...) to the normative step, the inductive step of a policy defense may seem trivial. We argue that this is not so. Satisfying the demands of the inductive step is difficult, and doing so has important but underappreciated implications for the normative step. In this paper, we provide an account of induction in social contexts and explore its implications for policy. Our account helps to explain which normative principles we ought to accept, and as a result it can explain why it is acceptable to make inferences involving race in some contexts (e.g., in defense of affirmative action) but not in others (e.g., in defense of racial profiling). (shrink)

Plausible probabilistic accounts of evidential support entail that every true proposition is evidence for itself. This paper defends this surprising principle against a series of recent objections from Jessica Brown. Specifically, the paper argues that: (i) explanationist accounts of evidential support convergently entail that every true proposition is self-evident, and (ii) it is often felicitous to cite a true proposition as evidence for itself, just not under that description. The paper also develops an objection involving the apparent impossibility of believing (...) P on the evidential basis of P itself, but gives a reason not to be too worried about this objection. Establishing that every true proposition is self-evident saves probabilistic accounts of evidential support from absurdity, paves the way for a non-sceptical infallibilist theory of knowledge and has distinctive practical consequences. (shrink)

Molinists hold that there are contingently true counterfactuals about what agents would do if put in specific circumstances, that God knows these prior to creation, and that God uses this knowledge in choosing how to create. In this essay we critique Molinism, arguing that if these theses were true, agents would not be free. Consider Eve’s sinning upon being tempted by a serpent. We argue that if Molinism is true, then there is some set of facts that fully explains both (...) Eve’s action and everything else Eve does that influences that action; and that if this is the case, Eve does not act freely. The first premise of this argument follows from the explanatory relations the Molinist is committed to, and the second premise follows from libertarian intuitions about free will. (shrink)

The subject of this essay is the classical problem of induction, which is sometimes attributed to David Hume and called “the Humean Problem of Induction.” Here, I examine a certain sort of Neo-Aristotelian solution to the problem, which appeals to the concept of natural kinds in its response to the inductive skeptic. This position is most notably represented by Howard Sankey and Marc Lange. The purpose of this paper is partly destructive and partly constructive. I raise two questions. The first (...) is: Are the natural kind solutions to the problem successful? The first thesis of this paper is that they are not, and I will show how and why they fail. And the second question I raise here is: Is there nonetheless some alternative Neo-Aristotelian solution to the problem which is successful and can overcome the shortcomings endemic to the Sankey-Lange account? The second thesis is that there is, and I’ll attempt to sketch one. My stance here may be summarized by saying that, while I agree with Sankey and Lange that the problem of induction can be adequately resolved, and while I am on the whole sympathetic with the Aristotelian spirit of their account, I am, for all that, dissatisfied with the letter of them. Nothing short of a more thoroughgoing Aristotelianism about the epistemology of induction will do. (shrink)

How the mind works have always been one of the most important and fascinating puzzles. For a long time, countless scholars have devoted themselves to this research, but there has no decisive progress been made yet. We believe that the fundamental reason for this situation is that the research paradigm learned from the study of objective sciences such as physics is not applicable to the study of the mind. In this paper, we suggest that the proper way to study the (...) mind is to think of it as a computational system that can program itself. In this self-programming system, there are two key components: storage structure and bootstrap program. In this paper, we only focus on analyzing the principle of the storage structure. Although this paper does not give a full mechanism of the self-programming system, the mere study of the storage structure can generate some important findings. Specifically, by using the storage structure, the problem of induction can be solved; And the mechanism of deduction and causality can easily be explained. Some of our findings sharply contrast with the existing theories. For example, we argue that the validity of induction is attributed to the intention of self-programming systems, not because it can be justified as mainstream inductivists try to prove. (shrink)