Induction

Historical inductions, viz., the pessimistic meta-induction and the problem of unconceived alternatives, are critically analyzed via John D. Norton’s material theory of induction and subsequently rejected as non-cogent arguments. It is suggested that the material theory is amenable to a local version of the pessimistic meta-induction, e.g., in the context of some medical studies.

John D. Norton’s “Material Theory of Induction” has been one of the most intriguing recent additions to the philosophy of induction. Norton’s account appears to be a notably natural account of actual inductive practices, though his theory has attracted considerable criticisms. I detail several novel issues for his theory, but argue that supplementing the Material Theory with a theory of direct inference could address these problems. I argue that if this combination is possible, a stronger theory of inductive reasoning emerges, (...) which has a more propitious answer to the Problem of Induction. (shrink)

Newton’s Regulae philosophandi—the rules for reasoning in natural philosophy—are maxims of causal reasoning and induction. This essay reviews their significance for Newton’s method of inquiry, as well as their application to particular propositions within the Principia. Two main claims emerge. First, the rules are not only interrelated, they defend various facets of the same core idea: that nature is simple and orderly by divine decree, and that, consequently, human beings can be justified in inferring universal causes from limited phenomena, if (...) only fallibly. Second, the rules make substantive ontological assumptions on which Newton’s argument in the Principia relies. (shrink)

William Whewell’s account of induction differs dramatically from the one familiar from twentieth-century debates. I argue that Whewell’s induction can be usefully understood by comparing the difference between his views and more standard accounts to contemporary debates between semantic and syntactic views of theories: rather than understanding inductive inference as capturing a relationship between sentences or propositions, Whewell understands it as a method for constructing a model of the world. The difference between this view and the more familiar picture of (...) induction is reflected in other aspects of Whewell’s philosophy of science, particularly his treatment of consilience and the order of discovery. (shrink)

Review Essay of ‘Isaac Newton’s Scientific Method’ by William L. Harper.

Peter Lipton argues that inference to the best explanation involves the selection of a hypothesis on the basis of its loveliness. I argue that in optimal cases of IBE we may be able to eliminate all but one of the hypotheses. In such cases we have a form of eliminative induction takes place, which I call ‘Holmesian inference’. I argue that Lipton’s example in which Ignaz Semmelweis identified a cause of puerperal fever better illustrates Holmesian inference than Liptonian IBE. I (...) consider in detail the conditions under which Holmesian inference is possible and conclude by considering the epistemological relations between Holmesian inference and Liptonian IBE.Keywords: Inference to the best explanation; Peter Lipton; Abduction; Holmesian inference; Eliminative induction. (shrink)

Primarily between 1833 and 1840, William Whewell attempted to accomplish what natural philosophers and scientists since at least Galileo had failed to do: to provide a systematic and broad-ranged study of the tides and to attempt to establish a general scientific theory of tidal phenomena. I document the close interaction between Whewell’s philosophy of science and his scientific practice as a tidologist. I claim that the intertwinement between Whewell’s methodology and his tidology is more fundamental than has hitherto been documented.Keywords: (...) William Whewell; Tidology; History of HPS; Scientific methodology; Whewell papers. (shrink)

We apply the recently elaborated notions of 'pragmatic truth' and 'pragmatic probability' to the problem of the construction of a logic of inductive inference. It is argued that the system outlined here is able to overcome many of the objections usually levelled against such attempts. We claim, furthermore, that our view captures the essentially cumulative nature of science and allows us to explain why it is indeed reasonable to accept and believe in the conclusions reached by inductive inference.

An original study of the philosophical problems associated with inductive reasoning. Like most of the main questions in epistemology, the classical problem of induction arises from doubts about a mode of inference used to justify some of our most familiar and pervasive beliefs. The experience of each individual is limited and fragmentary, yet the scope of our beliefs is much wider; and it is the relation between belief and experience, in particular the belief that the future will in some respects (...) resemble the past and the unobserved the observed, which forms the subject of this book. Dr Blackburn's first aim is to state the problem of induction properly, to show that there does exist a genuine problem immune to the solutions in vogue at present, yet no tin principle insoluble. He gives an extended and original account of the concept of a reason and goes on to discuss prediction. In the end Dr Blackburn produces a rationale for belief in certain short-term predictions based on his reinterpretation of the classical principle of indifference. He claims that a justification for induction can be found along the lines he has suggested and must indeed be found there if anywhere. (shrink)

Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction and (...) Part IV outlines the shape of this problem and its solution take if transformed by the present approach. (shrink)

In this paper I will argue that the controversial process of inferring to the best explanation can be made more coherent if its formulation recognizes and includes a significant inductive component. To do so, I will examine the relationship between Harman’s, Lipton’s, and Fumerton’s positions on IBE, settling ultimately upon a conception that categorically rejects Harman’s account while appropriating potions of both Lipton’s and Fumerton’s accounts. The resulting formulation will be called inductive-IBE, and I will argue that this formulation more (...) accurately describes the inferential practices employed in scientific inquiry. The upshot of my argument, that IBE contains a significant inductive component, will be that any conclusion born from such types of inductive inference must be, at best, likely, and not a necessity. And, although previous accounts of IBE have accepted the defeasibility of IBE, I will argue that inductive-IBE is more descriptive because it tells us why this fallibility exists. That is, although the Liptonian conception of IBE acknowledges that IBE is fallible, my account specifically addresses this characteristic and, thus, is more descriptive and informative in this regard. I will use inductive-IBE to argue, contra van Fraassen, that IBE can be a legitimate form of inference that leads science to true theories and real entities. (shrink)

A complete calculus of inductive inference captures the totality of facts about inductive support within some domain of propositions as relations or theorems within the calculus. It is demonstrated that there can be no complete, non-trivial calculus of inductive inference.

We compare Karl Popper’s ideas concerning the falsifiability of a theory with similar notions from the part of statistical learning theory known as VC-theory . Popper’s notion of the dimension of a theory is contrasted with the apparently very similar VC-dimension. Having located some divergences, we discuss how best to view Popper’s work from the perspective of statistical learning theory, either as a precursor or as aiming to capture a different learning activity.

Goodman published his "riddle" in the middle of the 20th century and many philosophers have attempted to solve it. These attempts almost all shared an assumption that, I shall argue, might be wrong, namely, the assumption that when we project from cases we have examined to cases we have not, what we project are predicates. I shall argue that this assumption, shared by almost all attempts at a solution, looks wrong, because, in the first place, what we project are generalizations (...) and not predicates, and a generalization is projectible relative to a given context. In this paper I develop the idea of explainable-projectible generalizations versus unexplainable-unprojectible generalizations, relative to a specific context. My main claim is that we rationally project a generalization if and only if we rationally believe that there is something that explains the general phenomenon that the generalized statement in question asserts to obtain, and that a generalization is projectible, if and only if its putative truth can be explained, whether we know that it can be or not. (shrink)

While there is no universal logic of induction, the probability calculus succeeds as a logic of induction in many contexts through its use of several notions concerning inductive inference. They include Addition, through which low probabilities represent disbelief as opposed to ignorance; and Bayes property, which commits the calculus to a ‘refute and rescale’ dynamics for incorporating new evidence. These notions are independent and it is urged that they be employed selectively according to needs of the problem at hand. It (...) is shown that neither is adapted to inductive inference concerning some indeterministic systems. (shrink)

In _Reliable Reasoning_, Gilbert Harman and Sanjeev Kulkarni -- a philosopher and an engineer -- argue that philosophy and cognitive science can benefit from statistical learning theory, the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors -- a central topic in SLT. After discussing philosophical attempts to evade the (...) problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT. (shrink)

This volume brings together a collection of essays on the history and philosophy of probability and statistics by one of the eminent scholars in these subjects. Written over the last fifteen years, they fall into three broad categories. The first deals with the use of symmetry arguments in inductive probability, in particular, their use in deriving rules of succession. The second group deals with four outstanding individuals who made lasting contributions to probability and statistics in very different ways: Frank Ramsey, (...) R. A. Fisher, Alan Turing, and Abraham de Moivre. The last group of essays deals with the problem of 'predicting the unpredictable' - making predictions when the range of possible outcomes is unknown in advance. The essays weave together the history and philosophy of these subjects and document the fascination that they have exercised for more than three centuries. (shrink)

John Norton has proposed a position of “material induction” that denies the existence of a universal inductive inference schema behind scientific reasoning. In this vein, Norton has recently presented a “dome scenario” based on Newtonian physics that, in his understanding, is at variance with Bayesianism. The present note points out that a closer analysis of the dome scenario reveals incompatibilities with material inductivism itself.

Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction and (...) Part IV outlines the shape of this problem and its solution take if transformed by the present approach. (shrink)