Refocusing the Study of Induction

2003

Philosophies, 2024

When an empirical prediction E of hypothesis H is observed to be true, such observation is said to confirm, i.e., support (although not prove) the truth of the hypothesis. But why? What justifies the claim that such evidence supports the hypothesis? The widely accepted answer is that it is justified by induction. More specifically, it is commonly held that the following argument: (1) If H then E; (2) E; (3) Therefore, (probably) H—here referred to as ‘hypothetico-deductive con-firmation argument’—is inductively strong. Yet this argument looks nothing like an inductive generalisation, i.e., it doesn’t seem inductive in the term's traditional, enumerative sense. If anything, it has the form of the fallacy of affirming the consequent. This paper aims to solve this puzzle. True, in recent decades, ‘in-duction’ has been sometimes used more broadly to encompass any non-deductive, i.e., ampliative, argument. Applying Bayesian confirmation theory has famously demonstrated that hypothetico-deductive confirmation is indeed inductive in this broader, ampliative sense. Nonetheless, it will be argued here that, despite appearance, hypothetico-deductive confirmation can also be recast as a strong enumerative induction. Hence, by being enumeratively inductive, the scientific method of hypothetico-deductive confirmation is justified through this traditional, more restrictive type of induction rather than merely by ampliative induction.

Unisinos Journal of Philosophy, 2021

The problem of unconceived alternatives (or the New Induction) states that, since scientists have recurrently failed to conceive relevant theoretical alternatives for some domains of science, current scientists are probably also failing to do so. Therefore, there may be theories which still exceed the grasp of scientists' imagination, and one should not endorse a realist stance towards current science. In this paper, I raise a conceptual worry for the formulation of this problem: what does it mean to say that scientists failed to conceive a relevant theory? What aggravates the problem is that no simple notion of relevance makes the New Induction as strong as it initially seems. I consider the three more obvious interpretations of relevance: relevance as objective probability; relevance as epistemic probability assessed by current scientists; and relevance as epistemic probability assessed by past scientists. I argue that assuming any of these three notions implies difficulties for the New Induction, hence their proponents shouldn't take the notion of relevance for granted. A more precise definition of relevance is essential to understand what are the difficulties surrounding the problem of unconceived alternatives as an epistemic worry. Until now, such notion is missing.

Episteme, 2020

According to John D. Norton's Material Theory of Induction, all reasonable inductive inferences are justified in virtue of background knowledge about local uniformities in nature. These local uniformities indicate that our samples are likely to be representative of our target population in our inductions. However, a variety of critics have noted that there are many circumstances in which induction seems to be reasonable, yet such background knowledge is apparently absent. I call such an absence of circumstances 'the frontiers of science', where background scientific theories do not provide information about such local uniformities. I argue that the Material Theory of Induction can be reconciled with our intuitions in favour of these inductions. I adapt an attempted justification of induction in general, the Combinatoric Justification of Induction, into a more modest rationalisation at the less foundational level that the critics discuss. Subject to a number of conditions, we can extrapolate from large samples using our knowledge of facts about the minimum proportions of representative subsets of finite sets. I also discuss some of Norton's own criticisms of his theory and argue that he is overly pessimistic. I conclude that Norton's theory at least performs well at the frontiers of science.

Vienna Circle Institute yearbook, 2004

Journal of Management, 2007

This article argues that theory building in the social sciences, management and psychology included, should be inductive. It begins by critiquing contemporary philosophy of science, for example, Popper's falsifiability theory, his stress on deduction, and the hypothetico-deductive method. Next, the author presents some history on the concept of induction in philosophy and of inductive theory building in the hard sciences (e.g., Aristotle, Bacon, Newton)

2010

Abstract Kyle Stanford has recently claimed to offer a new challenge to scientific realism. Taking his inspiration from the familiar Pessimistic Induction (PI), Stanford proposes a New Induction (NI). Contra Anjan Chakravartty's suggestion that the NI is a 'red herring', I argue that it reveals something deep and important about science. The Problem of Unconceived Alternatives, which lies at the heart of the NI, yields a richer anti-realism than the PI.

Inductive reasoning, initially identified with enumerative induction (inferring a universal claim from an incomplete list of particular cases) is nowadays commonly understood more widely as any reasoning based on only partial support that the premises give to the conclusion. This is a tad too sweeping, for this includes any inconclusive reasoning. A more moderate and perhaps more adequate characterization requires that inductive reasoning not only includes generalizations , but also any (ideally, rational) predictions or explanations obtained in absence of suitable deductive premises. Inductive logic is meant to provide guidance in choosing the most supported from a given assembly of conjectures. In this paper we survey selected approaches to inductive logic. Paper forthcoming in: INTRODUCTION TO FORMAL PHILOSOPHY S. O. Hansson, V. Hendrick, and K. Esther Michelsen (eds), Springer, 2018.

2006

Scientists apply Bacon's investigative induction by first cataloguing experimental discrepancies among apparent natures of things. Induction begins by multiplying discrepancies, thus creating a puzzle with multiple clues. Solved puzzles thus give us power to produce those unusual, discrepant effects. Bacon's experimental method, however, is not empiricist. Grasping things empirically, like receiving impressions on a wax tablet, presupposes that our senses cannot deceive us whenever we are deceived: we err in our interpretations. Empiricism thus leaves no objective discrepancies to resolve, as deception resides in our interpretation. Scientific induction, for all its success, becomes invisible to modern empiricist methodologists.

2003