Two More Principles of Epistemic Rationality

In Chapter 6, the author focuses on two main topics: the essential role of partial or full necessitation hypotheses in scenarios that generate expectations for experience and the social dimension of epistemic rationality. He contrasts partial or full necessitation hypotheses with neo-Humean regularity hypotheses. He argues that memory is a causal notion and contrasts it with non-causal apparent memories. He contrasts the causal physical object framework with a non-causal phenomenalist framework. And he explains why there is no syntactic solution to Goodman’s New Riddle of induction. He explains why Goodman’s own solution to the puzzle is an example of a parasitic hypothesis. He discusses parasitic hypotheses more fully and explains why most conspiracy theories are parasitic. He proposes a Third and Fourth Principle of Epistemic Rationality. Finally, he credits feminist epistemologists with drawing attention to the social dimension of epistemic rationality in contrast to the usual individualist approach in Western epistemology. He ends the chapter with a deep challenge for his own theory.

Fifty shades of grue: Indeterminate categories and induction in and out of the language sciences

It is hard to define structural categories of language (e.g. noun, verb, adjective) in a way which accounts for linguistic variation. This leads Haspelmath to make the following claims: i) unlike in biology and chemistry, there are no natural kinds in language; ii) there is a fundamental distinction between descriptive and comparative linguistic categories, and; iii) generalisations based on comparisons between languages can in principle tell us nothing about specific languages. The implication is that cross-linguistic categories cannot support scientific induction. I disagree: generalisations on the basis of linguistic comparison should inform the language sciences. Haspelmath is not alone in identifying a connection between the nature of the categories we use and the kind of inferences we can make (e.g. Goodman’s ‘new riddle of induction’), but he is both overly pessimistic about categories in language and overly optimistic about categories in other sciences: biology and even chemistry work with categories which are indeterminate to some degree. Linguistic categories are clusters of co-occurring properties with variable instantiations, but this does not mean that we should dispense with them: if linguistic generalisations reliably lead to predictions about individual languages, and if we can integrate them into more sophisticated causal explanations, then there is no a priori requirement for a fundamental descriptive/comparative distinction. Instead, we should appreciate linguistic variation as a key component of our explanations rather than a problem to be dealt with.

Philosophy through Machine Learning

In a previous article (2019), I motivated and defended the idea of teaching philosophy through computer science. In this article, I will further develop this idea and discuss how machine learning can be used for pedagogical purposes because of its tight affinity with philosophical issues surrounding induction. To this end, I will discuss three areas of significant overlap: (i) good / bad data and David Hume’s so-called Problem of Induction, (ii) validation and accommodation vs. prediction in scientific theory selection and (iii) feature engineering and Nelson Goodman’s so-called New Riddle of Induction.

Goodman e o projeto de uma definição construtiva de “indução válida”

In Fact, Fiction and Forecast, Nelson Goodman claims that the problem of justifying induction is not something over and above the problem of describing valid induction. Such claim seems to open up the possibility that the new riddle of induction could be addressed empirically. Discoveries about psychological preferences for projecting certain classes of objects could function as a criterion for determining which predicates are after all projectible. In this paper, I argue that Goodman’s claim must be construed within his project for constructional definitions, which is methodologically oriented by reflective equilibrium. The description of inductive practice is committed to the articulation of the extension of the class selected by the predicate ‘valid induction’. The mutual adjustment between theoretical considerations and inductive practice involved in the proposal of a definition of ‘valid induction’ must preserve that practice as much as possible, there is no way to get rid of entrenchment. Empirical discoveries about the psychological mechanism that underlies projections may help that adjustment but they cannot substitute the role played by the entrenchment of predicates.

Goodman, Nelson (1906–98)

Nelson Goodman was an American philosopher who wrote important works in metaphysics, aesthetics and epistemology. Throughout his work runs a concern with the ways that the symbols we construct inform the facts that we find, and structure our understanding of them. Different symbol systems yield irreconcilable structures. So there is no one way things really are. There are, he concludes, many worlds if any. Moreover, worlds are made rather than found, for the categories we construct fix the criteria of identity for the individuals and kinds we recognize. Thus they determine what objects and kinds constitute a world. Goodman argues that the arts as well as the sciences make and reveal worlds. Aesthetics as he construes it is a branch of epistemology. He analyses a variety of modes of symbolization, literal and metaphorical, and shows how they contribute in the arts and elsewhere to the advancement of understanding. Goodman’s ‘new riddle of induction’ reveals that the problem of induction runs deeper than philosophers had thought. He defines the predicate ‘grue’ as ‘examined before future time t and found to be green or not so examined and blue.’ All emeralds examined to date have been both green and grue. What justifies our expecting future emeralds to be green rather than grue? Inductive validity, the new riddle shows, turns not only on the constitution of an evidence class, but also on its characterization. The question then is what favours one characterization over its rivals. The fact that ‘green’ has been used far more often than ‘grue’ in induction, Goodman contends, provides the answer – not because it increases our odds of being right, but because of its pragmatic advantages.

Generality, generalization, and induction in Poincaré’s philosophy

This article examines Henri Poincaré’s philosophical conceptions of generality in mathematics and physics, and more specifically his claim that induction in experimental physics does not consist in extending the domain of a predicate. It first considers Poincaré’s view that generalization is not a means to reach generality and that the issue of infinity is related to the theme of generality. It then shows how generality in mathematics and physics is construed by Poincaré in a very specific way and how he analyzes empirical induction in physics. It also analyzes the distinction suggested by Poincaré between generalizations used in mathematical physics and generalizations used by ‘naturalists’. In particular, it explains the distinction between mathematical generality and the so-called predicative generality. Finally, it compares Poincaré’s concern regarding empirical induction with Nelson Goodman’s ‘new riddle of induction’, arguing that ‘the new riddle of induction’ was originally formulated by Poincaré half a century earlier.

Nelson Goodman

Goodman addressed the problem of induction twice. His first approach is famous, centers on his “new riddle of induction,” and is the locus classicus of modern reflective equilibrium theory. In it the focus is on inductive inferences and rules of inductive inference. In his second approach, the focus is instead on the conclusions of inductive inferences to explanations of the available data. Here reflective equilibrium theory is more fully developed. The author in this chapter argues that Goodman’s two accounts of inductive justification in terms of reflective equilibrium share a deep commonality.

Confirmation and Induction

Scientific knowledge is based on induction, ampliative inferences from experience. The chapter gives an overview of the problem of induction and the responses that philosophers of science have developed over time, focusing on attempts to spell out rules of inductive inference, and to balance attractive theoretical principles with judgments and intuitions in particular cases. That this is not always easy is demonstrated by challenges such as the paradox of the ravens, the problem of irrelevant conjunctions, and Goodman's new riddle of induction. The chapter then focuses on explications of the degree of confirmation of a hypothesis and compares various Bayesian measures of confirmation, as well as the Bayesian and frequentist approaches to statistical inference.