To explain the phenomena in the world of our experience, to answer the question “why?” rather than only the question “what?”, is one of the foremost objectives of all rational inquiry; and especially, scientific research in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. While there is rather general agreement about this chief objective of science, there exists considerable difference of opinion as to the function (...) and the essential characteristics of scientific explanation. In the present essay, an attempt will be made to shed some light on these issues by means of an elementary survey of the basic pattern of scientific explanation and a subsequent more rigorous analysis of the concept of law and of the logical structure of explanatory arguments. (shrink)

In the opening lines of this article it is claimed that history is a discipline taking role as part of unique body of science. The concept of scientific rationality is presented as the criterion of demarcation between science and pseudoscience. From this statement as a starting point, it follows that the methodological grounds for scientific predictions are common for all scientific disciplines. Different aspects of scientific predicting are critically examined: thesis of symmetry, determinism and predictability, indeterminism and predictability, reflexivity of (...) predictions, prediction of novelty and progress, predictions in relation to the time of their uttering, the prediction sketch, truthfulness and regularity in implying prediction, and predictability of human actions. In the concluding section, the author admits of the possibility of constructing the theory of history, opposed to eschatological philosophy of history, as a predictive theory with a scientific basis and a theory whose specifications limit its misuse in practice. (shrink)

I argue that Carl Hempel’s pioneering work on scientific explanation introduced an assumption that Hempel never motivated, namely, that explanation is an aim of science. Ever since, it has remained largely unquestioned in analytic philosophy of science. By expanding the historical scope of the debate on explanation to philosophers from the first half of the twentieth century, I show that the debate should include a critical reflection on Hempel’s assumption. This reflection includes two problems: how to motivate one’s position on (...) the aims of scientific knowledge and how to decide which examples count as expressions of those aims. (shrink)

Philosophy of science was once a much more socially engaged endeavor, and can be so again. After a look back at philosophy of science in the 1930s-1950s, I turn to discuss the current potential for returning to a more engaged philosophy of science. Although philosophers of science have much to offer scientists and the public, I am skeptical that much can be gained by philosophers importing off-the-shelf discussions from philosophy of science to science and society. Such efforts will likely look (...) like efforts to do applied ethics by merely applying ethical theories to particular contexts and problems. While some insight can be gained by these kinds of endeavors, the most interesting and pressing problems for the actual practitioners and users of science are rarely addressed. Instead, I recommend that philosophers of science engage seriously and regularly with scientists and/or the users of science in order to gain an understanding of the conceptual issues on the ground. From such engagement, flaws in the traditional philosophical frameworks, and how such flaws can be remedied, become apparent. Serious engagement with the contexts of science thus provides the most fruit for philosophy of science per se and for the practitioners whom the philosophers aim to assist. And if one focuses on contexts where science has its most social relevance, these efforts can help to provide the thing that philosophy of science now lacks: a full-bodied philosophy of science in society. (shrink)

Certain characteristics make machine learning a powerful tool for processing large amounts of data, and also particularly unsuitable for explanatory purposes. There are worries that its increasing use in science may sideline the explanatory goals of research. We analyze the key characteristics of ML that might have implications for the future directions in scientific research: epistemic opacity and the ‘theory-agnostic’ modeling. These characteristics are further analyzed in a comparison of ML with the traditional statistical methods, in order to demonstrate what (...) it is specifically that makes ML methodology substantially unsuitable for reaching explanations. The analysis is given broader philosophical context by connecting it with the views on the role of prediction and explanation in science, their relationship, and the value of explanation. We proceed to show, first, that ML disrupts the relationship between prediction and explanation commonly understood as a functional relationship. Then we show that the value of explanation is not exhausted in purely predictive functions, but rather has a ubiquitously recognized value for both science and everyday life. We then invoke two hypothetical scenarios with different degrees of automatization of science, which help test our intuitions on the role of explanation in science. The main question we address is whether ML will reorient or otherwise impact our standard explanatory practice. We conclude with a prognosis that ML would diversify science into purely predictively oriented research based on ML-like techniques and, on the other hand, remaining faithful to anthropocentric research focused on the search for explanation. (shrink)

In the methodology of scientific research programs (MSRP) there are important features on the problem of prediction, especially regarding novel facts. In his approach, Imre Lakatos proposed three different levels on prediction: aim, process, and assessment. Chapter 5 pays attention to the characterization of prediction in the methodology of research programs. Thus, it takes into account several features: (1) its pragmatic characterization, (2) the logical perspective as a proposition, (3) the epistemological component, (4) its role in the appraisal of research (...) programs, and (5) its place as a value for scientific research. -/- The notion of “novel facts” is highly relevant in his conception, where several aspects are involved: the directions of novel facts, the different kinds of novelty, and the transition from six possible options of “novel facts” to four choices. Thereafter, the prediction of novel facts as the criterion of appraisal is considered. On the one hand, this requires analyzing the theoretical, empirical, and heuristic possibilities of appraisal; and, on the other, whether there is an overemphasis on the role of prediction in methodology of scientific research programs. As a consequence, there is an analysis of Lakatos’ criterion of appraisal in MSRP and economics. (shrink)

The aim of this paper is to elaborate a notion of explanation which is applicable to stochastic processes such as quantum processes. The model-theoretic approach was adopted in order to delimit appropriate classes, by defining set-theoretical predicates, of different kinds of physical transformations that quantum systems suffer, either of transitions or of transmutations, by interaction or in a spontaneous manner. To explain a singular quantum process consists in showing that it is feasible to model it as an indeterministic process of (...) certain specified kind. (shrink)

Recent discussions in the philosophy of science have devoted considerable attention to the analysis of conceptual issues relating to the methodology of explanation and prediction in the sciences. Part of this literature has been devoted to clarifying the very ideas of explanation and prediction. But the discussion has also ranged over various related topics, including the status of laws to be used for explanatory and predictive purposes, the logical interrelationships between explanatory and predictive reasonings, the differences in the strategy of (...) explanatory argumentation in different branches of science, the nature and possibility of teleological explanation, etc. The aim of the present article is to examine the issues involved in such questions from the specialized perspective afforded by one particular kind of physical systems--namely, systems, here to be characterized as discrete state systems, whose behavior has been studied extensively in the scientific literature under the general heading of Markov chains. These systems have been chosen as our focus because their behavior over time can be analyzed at once with great ease and with extraordinary precision. (shrink)

Anyone, today, with even a slight interest in the methodology of science will be aware of the heated debate which has raged in regard to the thesis of the logical symmetry between explanation and prediction, which is entailed by the hypotheticodeductive account of scientific theory. The symmetry thesis, which received its classical exposition in a well-known article by Hempel and Oppenheim [2], has been subject to a steadily growing criticism by several eminent thinkers. My intention, in this article, is to (...) argue that the current reaction to the Hempel-Oppenheim position, as exemplified by Professors Hanson, Scriven, et al., represents a retrograde movement in the philosophy of science, which, as the number of its converts grows, could undermine the progress, which has been accomplished in the broad tradition that extends from Mach and Poincaré through the Vienna Circle to the present day. Specifically, it is my contention that the aforementioned reaction is symptomatic of a contemporary trend in the direction of irrationalism which, of all branches of philosophy, the philosophy of science should seek to dispel rather than to foster. For the sake of brevity, I propose to focus my remarks wholly on the original widely read article of Hanson on this subject [1]. That I single out this particular source should not be taken to belie the admiration I hold for the masterful scholarship of its author. (shrink)