Truth and Verisimilitude, Misc

This monograph is an in-depth and engaging discourse on the deeply cognitive roots of human scientific quest. The process of making scientific inferences is continuous with the day-to-day inferential activity of individuals, and is predominantly inductive in nature. Inductive inference, which is fallible, exploratory, and open-ended, is of essential relevance in our incessant efforts at making sense of a complex and uncertain world around us, and covers a vast range of cognitive activities, among which scientific exploration constitutes the pinnacle. Inductive (...) inference has a personal aspect to it, being rooted in the cognitive unconscious of individuals, which has recently been found to be of paramount importance in a wide range of complex cognitive processes. One other major aspect of the process of inference making, including the making of scientific inferences, is the role of a vast web of beliefs lodged in the human mind, as also of a huge repertoire of heuristics, that constitute an important component of ‘unconscious intelligence’. Finally, human cognitive activity is dependent in a large measure on emotions and affects, that operate mostly at an unconscious level. Of special importance in scientific inferential activity is the process of hypothesis making, which is examined in this book, along with the above aspects of inductive inference, at considerable depth. The book focuses on the inadequacy of the viewpoint of naive realism in understanding the contextual nature of scientific theories, where a cumulative progress towards an ultimate truth about Nature appears to be too simplistic a generalization. It poses a critique to the commonly perceived image of science which is seen as the last word in logic and objectivity, the latter in the double sense of being independent of individual psychological propensities and, at the same time, approaching a correct understanding of the workings of a mind-independent nature. Adopting the naturalist point of view, it examines the essential tension between the cognitive endeavours of individuals and scientific communities, immersed in belief systems and cultures, on the one hand, and the engagement with a mind-independent reality on the other. In the end, science emerges as an interpretation of nature, which is perceived by us only contextually, as successively emerging cross-sections of limited scope and extent. Successive waves of theory building in science appear as episodic and kaleidoscopic changes in perspective as certain in-built borders are crossed, rather than as a cumulative progress towards some ultimate truth. While written in an informal and conversational style, the book raises a number of deep and intriguing questions located at the interface of cognitive psychology and philosophy of science, meant for both the general lay reader and the specialist. Of particular interest is the way it explores the role of belief (aided by emotions and affects) in making the process of inductive inference possible since belief is a subtle though all-pervasive cognitive factor not adequately investigated in the current literature. (shrink)

The merging/fusion of belief/data collections in propositional logic form is a topic that has received due attention within the domains of database and AI research. A distinction can be made between two types of scenarios to which the process of merging can be applied. In the first type, the collections represent preferences, such as the voting choices of a group of people, that need to be aggregated so as to give a consistent result that in some way best represents the (...) collective judgement of the group. In the second type, the collections represent factual data that is to be aggregated with an aim of obtaining a result that maximises factual correctness. After introducing a general framework for belief merging via some prominent literature on the topic, this paper then introduces and considers a method for belief merging with the second type of scenario in mind. Its suitability is corroborated by demonstrating how it can be seen as a special case of a merging procedure that combines aggregation of probabilities and maximisation of expected truthlikeness. (shrink)

This paper builds an integrated framework of measures of information based on the Model for Information (MfI) developed by the author. Since truth is expressed using information, an analysis of truth depends on the nature of information and its limitations. These limitations include those implied by the geometry of information and those implied by the relativity of information. This paper proposes an approach to truth and truthlikeness that takes these limitations into account by incorporating measures of the quality of information. (...) Another measure of information is the amount of information. This has played a role in two important theoretical difficulties—the Bar-Hillel Carnap paradox and the “scandal of deduction”. This paper further provides an analysis of the amount of information, based on MfI, and shows how the MfI approach can resolve these difficulties. (shrink)

Theories in the philosphy of science are often described from a syntactical or semantical point of view. In this text both descriptions are generalised by interpreted theories. The corresponding interpreted reductions unify the usual attempts to describe intertheoretical reductions. Furthermore leads the chosen framework to interesting results in various versions of reductionism. Approximative Reductions are identified as a special case, as well as truthlikeness.

Scientists are constantly making observations, carrying out experiments, and analyzing empirical data. Meanwhile, scientific theories are routinely being adopted, revised, discarded, and replaced. But when are such changes to the content of science improvements on what came before? This is the question of scientific progress. One answer is that progress occurs when scientific theories ‘get closer to the truth’, i.e. increase their degree of truthlikeness. A second answer is that progress consists in increasing theories’ effectiveness for solving scientific problems. A (...) third answer is that progress occurs when the stock of scientific knowledge accumulates. A fourth and final answer is that scientific progress consists in increasing scientific understanding, i.e. the capacity to correctly explain and reliably predict relevant phenomena. This paper compares and contrasts these four accounts of scientific progress, considers some of the most prominent arguments for and against each account, and briefly explores connections to different forms of scientific realism. (shrink)

The concept of approximate truth plays a prominent role in most versions of scientific realism. However, adequately conceptualizing ?approximate truth? has proved challenging. This article argues that the goal of articulating the concept of approximate truth can be advanced by first investigating the processes by which science accords theories the status of accepted or rejected. Accordingly, this article uses a path diagram model as a visual heuristic for the purpose of showing the processes in science that are involved in determining (...) a theory's status. This ?inductive realist? model of theory status then serves as a starting point for explicating an inductive realist view of approximate truth that, it is argued, can explain instances of the success of science, but does not (1) require science's theories to be strictly true in any world or (2) require a metric for measuring how close an approximately true theory is to some strictly true theory. To show the advantages of the inductive realist approach to approximate truth, an example of a major success story of science, the successful eradication of smallpox, is reviewed and then explained. (shrink)

The degree of corroboration of a scientific hypothesis is an issue that has been repeatedly discussed in modern theory of sciences . In a preceding paper it was shown that the formulae advanced by Popper to calculate the degree of corroboration C are not very satisfactory because the probability values required in the computation of C are not available as a rule. Another equation to measure the degree of corroboration B was proposed ), whereby only the number n of unsuccessful (...) efforts to falsify a scientific hypothesis by means of adequate experiments or observations is needed to be known. Shortly after the publication of these ideas I discovered that Nicolaus Cusanus in his book "De docta ignorantia" had proposed a model of scientific "verisimilitude" which leads to a quite similar relationship between B and the number n of independent proofs or observations. The "polygonal" model of verisimilitude ) mentioned by Cusanus is presumably the first quantitative estimate proposed for this problem in philosophical literature. (shrink)

In order to develop an account of scientific rationality, two problems need to be addressed: (i) how to make sense of episodes of theory change in science where the lack of a cumulative development is found, and (ii) how to accommodate cases of scientific change where lack of consistency is involved. In this paper, we sketch a model of scientific rationality that accommodates both problems. We first provide a framework within which it is possible to make sense of scientific revolutions, (...) but which still preserves some (partial) relations between old and new theories. The existence of these relations help to explain why the break between different theories is never too radical as to make it impossible for one to interpret the process in perfectly rational terms. We then defend the view that if scientific theories are taken to be quasi-true, and if the underlying logic is paraconsistent, it's perfectly rational for scientists and mathematicians to entertain inconsistent theories without triviality. As a result, as opposed to what is demanded by traditional approaches to rationality, it's not irrational to entertain inconsistent theories. Finally, we conclude the paper by arguing that the view advanced here provides a new way of thinking about the foundations of science. In particular, it extends in important respects both coherentist and foundationalist approaches to knowledge, without the troubles that plague traditional views of scientific rationality. (shrink)

In this article, through a critical examination of K. Brad Wray's version of the argument from underconsideration against scientific realism, I articulate a modest version of scientific realism. This modest realist position, which I call ‘relative realism’, preserves the scientific realist's optimism about science's ability to get closer to the truth while, at the same time, taking on board the antirealist's premise that theory evaluation is comparative, and thus that there are no good reasons to think that science's best theories (...) are close to the truth. (shrink)

This chapter outlines improvements and developments made to aim-oriented empiricism since "From Knowledge to Wisdom" was first published in 1984. It argues that aim-oriented empiricism enables us to solve three fundamental problems in the philosophy of science: the problems of induction and verisimilitude, and the problem of what it means to say of a physical theory that it is unified.

What is the relation between method and truth? Are we justified in accepting a theory that satisfies the rules of scientific method as true? Such questions divide realism from anti-realism in the philosophy of science. Scientific realists take the methods of science to promote the realist aim of correspondence truth. Anti-realists either claim that the methods of science promote lesser epistemic goals than realist truth, or else they reject the realist conception of truth altogether. In this paper, I propose a (...) realist theory of the relation between method and truth. The theory consists of three basic elements: (a) a naturalistic treatment of epistemic normativity, (b) an instrumentalist conception of the nature of methodological rules, and (c) an abductive argument for the truth-conduciveness of the rules of scientific method. (shrink)

Accompanying the decline of empiricism in the theory of knowledge has been an increased interest in the social determinants of knowledge and an increased recognition of the fundamental place in the constitution of knowledge occupied by accepted cognitive practices. The principal aim of this paper is to show how a view of knowledge that fully recognizes the role of these practices can adequately treat a topic that is widely considered to be an insuperable obstacle to such a view. The topic (...) is that of scientific realism, of the independence with respect to cognitive practices of certain objects of knowledge. (shrink)