SummaryAfter presumably cleaning science of induction, Karl Popper claims to offer a purely noninductivist theory of science. In critically evaluating this theory, I focus on the allegedly noninductive character of this theory. First, I defend and expand Wesley Salmon's charge that Popper's dismissal of induction renders science useless for practical purposes. Without induction practitioners have no grounds for believing that the predicted event will actually take place. Second, despite Popper's demands to the contrary, his theory of science is shown to (...) rest on induction. In particular, the function he attributes to background knowledge in testing a scientific hypothesis requires induction. (shrink)

The problem of induction is formulated as a set of three questions, namely: ‘What is the nature of the attitude of acceptance that we adopt in relation to certain theories?’ ‘What are the rules according to which we select those theories which we accept?’ and, ‘What is the justification for the adoption of those rules?’. An original answer is proposed for each question in turn, with the help of the new concepts of sub-theory, established sub-theory, aberrant, arbitrary and degenerate theories. (...) The answer to the third question follows the lines of Reichenbach's pragmatic strategy. (shrink)

It is widely agreed that Hume's description of human inductive reasoning is inadequate. But many philosophers think that this inadequacy in no way affects the force of Hume's argument for the unjustifiability of inductive reasoning. I argue that this constellation of opinions contains a serious tension, given that Hume was not merely pointing out that induction is fallible. I then explore a recent diagnosis of where Hume's sceptical argument goes wrong, due to Elliott Sober. Sober argues that Hume committed a (...) quantifier-shift fallacy, i.e. inferred a statement of ?? form from one of ?? form. The implications of this diagnosis for the traditional problem of induction are briefly examined. (shrink)

It is widely agreed that Hume’s description of human inductive reasoning is inadequate. But many philosophers think that this inadequacy in no way affects the force of Hume’s argument for the unjustifiability of inductive reasoning. I argue that this constellation of opinions contains a serious tension, given that Hume was not merely pointing out that induction is fallible. I then explore a recent diagnosis of where Hume’s sceptical argument goes wrong, due to Elliott Sober. Sober argues that Hume committed a (...) quantifier-shift fallacy, i.e. inferred a statement of ∃∀ form from one of V∀∃ form. The implications of this diagnosis for the traditional problem of induction are briefly examined. The author suggests that, were his philosophy received, we must alter from the foundation the greatest part of the sciences. Hume 1740. (shrink)

State of the art paper on the problem of induction: how to justify the conclusion that ‘all Fs are Gs’ from the premise that ‘all observed Fs are Gs’. The most prominent theories of contemporary philosophical literature are discussed and analysed, such as: inductivism, reliabilism, perspective of laws of nature, rationalism, falsificationism, the material theory of induction and probabilistic approaches, according to Carnap, Reichenbach and Bayesianism. In the end, we discuss the new problem of induction of Goodman, raised by the (...) grue predicate. (shrink)

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions (...) can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone. (shrink)