Induction

Given plausible assumptions about the nature of evidence and undercutting defeat, many believe that the force of the evidential problem of evil depends on sceptical theism’s being false: if evil is...

This article compares and contrasts the reception of Comte’s positivism in the works of William Whewell, John Stuart Mill and Franz Brentano. It is argued that Whewell’s rejection of positivism derives from his endorsement of a constructivist account of the inductive sciences, while Mill and Brentano’s sympathies for positivism are connected to their endorsement of an empiricist account. The mandate of the article is to spell out the chief differences between these two rival accounts. In the last, conclusive section, Whewell’s (...) anti-positivist argument is briefly assessed, and rebutted. (shrink)

The environmental costs and energy constraints have become emerging issues for the future development of Machine Learning (ML) and Artificial Intelligence (AI). So far, the discussion on environmental impacts of ML/AI lacks a perspective reaching beyond quantitative measurements of the energy-related research costs. Building on the foundations laid down by Schwartz et al., 2019 in the GreenAI initiative, our argument considers two interlinked phenomena, the gratuitous generalisation capability and the future where ML/AI performs the majority of quantifiable inductive inferences. The (...) gratuitous generalisation capability refers to a discrepancy between the cognitive demands of a task to be accomplished and the performance (accuracy) of a used ML/AI model. If the latter exceeds the former because the model was optimised to achieve the best possible accuracy, it becomes inefficient and its operation harmful to the environment. The future dominated by the non-anthropic induction describes a use of ML/AI so all-pervasive that most of the inductive inferences become furnished by ML/AI generalisations. The paper argues that the present debate deserves an expansion connecting the environmental costs of research and ineffective ML/AI uses (the issue of gratuitous generalisation capability) with the (near) future marked by the all-pervasive Human-Artificial Intelligence Nexus. (shrink)

Most scientists would hold that science has not established that the cosmos is physically comprehensible – i.e. such that there is some as-yet undiscovered true physical theory of everything that is unified. This is an empirically untestable, or metaphysical thesis. It thus lies beyond the scope of science. Only when physics has formulated a testable unified theory of everything which has been amply corroborated empirically will science be in a position to declare that it has established that the cosmos is (...) physically comprehensible. But this argument presupposes a widely accepted but untenable conception of science which I shall call standard empiricism. According to standard empiricism, in science theories are accepted solely on the basis of evidence. Choice of theory may be influenced for a time by considerations of simplicity, unity, or explanatory capacity, but not in such a way that the universe itself is permanently assumed to be simple, unified or physically comprehensible. In science, no thesis about the universe can be accepted permanently as a part of scientific knowledge independently of evidence. Granted this view, it is clear that science cannot have established that the universe is physically comprehensible. Standard empiricism is, however, as I have indicated, untenable. Any fundamental physical theory, in order to be accepted as a part of theoretical scientific knowledge, must satisfy two criteria. It must be (1) sufficiently empirically successful, and (2) sufficiently unified. Given any accepted theory of physics, endlessly many empirically more successful disunified rivals can always be concocted – disunified because they assert that different dynamical laws govern the diverse phenomena to which the theory applies. These disunified rivals are not considered for a moment in physics, despite their greater empirical success. This persistent rejection of empirically more successful but disunified rival theories means, I argue, that a big, highly problematic, implicit assumption is made by science about the cosmos, to the effect, at least, that the cosmos is such that all seriously disunified theories are false. Once this point is recognized, it becomes clear, I argue, that we need a new conception of science which makes explicit, and so criticizable and improvable the big, influential, and problematic assumption that is at present implicit in physics in the persistent preference for unified theories. This conception of science, which I call aim-oriented empiricism, represents the assumption of physics in the form of a hierarchy of assumptions. As one goes up the hierarchy, the assumptions become less and less substantial, and more and more nearly such that their truth is required for science, or the pursuit of knowledge, to be possible at all. At each level, that assumption is accepted which (a) best accords with the next one up, and (b) has, associated with it the most empirically progressive research programme in physics, or holds out the greatest hope of leading to such an empirically progressive research programme. In this way a framework of relatively insubstantial, unproblematic, fixed assumptions and associated methods is created, high up in the hierarchy, within which much more substantial and problematic assumptions and associated methods, low down in the hierarchy, can be changed, and indeed improved, as scientific knowledge improves. One assumption in this hierarchy of assumptions, I argue, is that the cosmos is physically comprehensible – that is, such that some yet-to-be-discovered unified theory of everything is true. Hence the conclusion: improve our ideas about the nature of science and it becomes apparent that science has already established that the cosmos is physically comprehensible – in so far as science can ever establish anything theoretical. (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. 1Introduction 2The Deductive Structure 2.1Finite Boolean algebras of propositions 2.2Symmetries of the Boolean algebra 3Deductively Definable Logics of Induction: The Formal Expression of Completeness 3.1Strength of inductive support 3.2Explicit definition 3.3Implicit definition 4The Symmetry Theorem 4.1An illustration 4.2The general case 5Asymptotic (...) Stability 5.1Illustrations 5.2The general condition 6The No-Go Result 6.1Illustration: the principle of indifference 6.2The result 7Incompleteness 8Unsuccessful Escapes 8.1Enriching the deductive logic 8.2Enrich the inductive logic 8.3Preferred refinements and preferred languages 8.4The subjective turn 9Conclusions Appendices. (shrink)

A crucial aspect of scientific realism is what do we mean by true. In Luk’s theory and model of scientific study, a theory can be believed to be “true” but a model is only accurate. Therefore, what do we mean by a “true” theory in scientific realism? Here, we focus on exploring the notion of truth by some thought experiments and we come up with the idea that truth is related to what we mean by the same. This has repercussion (...) to the repeatability of the experiments and the predictive power of scientific knowledge. Apart from sameness, we also found that truth is related to the granularity of the observation, the limit of detection, the distinguishability of the objects in theory, the simultaneous measurements of objects/processes, the consistencies of the theory and the one-to-one correspondence between terms/events and objects/processes, respectively. While there is no guarantee that we can arrive at the final “true” theory, we have a process/procedure with more and more experiments together with our own ingenuity, to direct us towards such a “true” theory. For quantum mechanics, since a particle is also regarded as a wave, quantum mechanics cannot be considered as a true theory based on the correspondence theory of truth. Failing this, truth may be defined by the coherence theory of truth which is similar to the coherence of beliefs. However, quantum mechanics may not be believed to be a true theory based on the coherence theory of truth because wave properties and particle properties may contradict. Further research is needed to address this problem if we want to regard quantum mechanics as a “true” theory. (shrink)

Unconscious logical inference seems to rely on the syntactic structures of mental representations (Quilty-Dunn & Mandelbaum 2018). Other transitions, such as transitions using iconic representations and associative transitions, are harder to assimilate to syntax-based theories. Here we tackle these difficulties head on in the interest of a fuller taxonomy of mental transitions. Along the way we discuss how icons can be compositional without having constituent structure, and expand and defend the “symmetry condition” on Associationism (the idea that associative links and (...) transitions are perfectly symmetric). In the end, we show how a BIT (“bare inferential transition”) theory can cohabitate with these other non-inferential mental transitions. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing on two recent proposals (...) which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

Bayesian confirmation theory is a leading theory to decide the confirmation/refutation of a hypothesis based on probability calculus. While it may be much discussed in philosophy of science, is it actually practiced in terms of hypothesis testing by scientists? Since the assignment of some of the probabilities in the theory is open to debate and the risk of making the wrong decision is unknown, many scientists do not use the theory in hypothesis testing. Instead, they use alternative statistical tests that (...) can measure the risk or the reliability in decision making, circumventing some of the theoretical problems in practice. Therefore, the theory is not very popular in hypothesis testing among scientists at present. However, there are some proponents of Bayesian hypothesis testing, and software packages are made available to accelerate utilization by scientists. Time will tell whether Bayesian confirmation theory can become both a leading theory and a widely practiced method. In addition, this theory can be used to model the belief of scientists when testing hypotheses. (shrink)

Epistemological naturalists reject the demand for a priori justification of empirical knowledge; no such thing is possible. Observation reports, being the foundation of empirical knowledge, are neither justified by other sentences, nor certain; but they may be agreed upon as starting points for inductive reasoning and they function as implicit definitions of predicates used. Making inductive generalisations from observations is a basic habit among humans. We do that without justification, but we have strong intuitions that some inductive generalisations will fail, (...) while for some other we have better hopes. Why? This is the induction problem according to Goodman. He suggested that some predicates are projectible when becoming entrenched in language. This is a step forward, but not entirely correct. Inductions result in universally generalised conditionals and these contain two predicates, one in the antecedent, one in the consequent. Counterexamples to preliminary inductive generalisations can be dismissed by refining the criteria of application for these predicates. This process can be repeated until the criteria for application of the predicate in the antecedent includes the criteria for the predicate in the consequent, in which case no further counterexample is possible. If that is the case we have arrived at a law. Such laws are implicit definitions of theoretical predicates. An accidental generalisation has not this feature, its predicates are unrelated. Laws are said to be necessary, which may be interpreted as ‘“Laws” are necessarily true’. ‘Necessarily true’ is thus a semantic predicate, not a modal operator. In addition, laws, being definitions, are necessarily true in the sense of being necessary assumptions for further use of the predicates implicitly defined by such laws. Induction, when used in science, is thus our way of inventing useful scientific predicates; it is a heuristic, not an inference principle. (shrink)

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, although his theory has attracted considerable criticism. 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.

This paper studies the use of hypotheses schemes in generating inductive predictions. After discussing Carnap-Hintikka inductive logic, hypotheses schemes are defined and illustrated with two partitions. One partition results in the Carnapian continuum of inductive methods, the other results in predictions typical for hasty generalization. Following these examples I argue that choosing a partition comes down to making inductive assumptions on patterns in the data, and that by choosing appropriately any inductive assumption can be made. Further considerations on partitions make (...) clear that they do not suggest any solution to the problem of induction. Hypotheses schemes provide the tools for making inductive assumptions, but they also reveal the need for such assumptions. (shrink)

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)