Abstract The opening section outlines probabilism in the 20th century philosophy and shortly discusses the major accomplishments of Polish probabilist thinkers. A concise characterization of Bayesianism as the major recent form of probabilism follows. It builds upon the core personalist version of Bayesianism towards more objectively oriented versions thereof. The problem of a priori probability is shortly discussed. A tentative characterization of Kazimierz Ajdukiewicz’s standpoint regarding the inductive inference is cast in Bayesian terms. His objections against it presented in Pragmatic (...) Logic are presented. His 1958 paper on justification of non-deductive inference, as amply demonstrated by K. Szaniawski and I. Niiniluoto, extends his earlier Baysian position from 1928 monograph. In the closing section Ajdukiewicz’s standpoint is presented as a characteristically pragmatist and empiricist version of Bayesianism, which remains an unexplored and stimulating position. (shrink)

Any serious attempt to give an account of the cognitive aspect of science – as contrasted with e.g. its social or cultural aspects – cannot ignore the automation revolution. In the conception presented in this paper the results of computer science are taken seriously and integrated with many of the ideas concerning what constitutes scientific inquiry that have been proposed at least since the early Middle Ages. The central idea is that of reliable inquiry. Science makes explicit and elaborates on (...) the methods of acquiring beliefs in our daily life. The central question a scientific method applied to inquiry needs to face is if it is reliable in getting to the truth. On the reliabilist criteria presented here, if a method is logically warranted to get to the right answer – given data and background knowledge available – and to stick to it afterwards, then it is reliable. This is a normative theory, but the standard of reliability is adjusted to the domain of the inquiry at hand. This paper presents the central tenets of the reliabilist conception of science and briefly outlines the main results underlying it. Roughly, the aim of science is interesting truth about the world around us (scientific realism) and reliabilist epistemology affords us precise answers as to how far science can succeed in this task – given the methods, goals and background assumptions available. The philosophical task to deliver an adequate understanding of science is taken to be continuous with scientific research itself (naturalism), a major part of which is concerned with delivering causal explanations (causality) and can only be carried out with limited resources (computability). Many of the ideas integrated into the reliabilist conception of science and precisely articulated therewith have appeared earlier in both philosophy and science (history of ideas). I conclude the exposition of the ideas integrated into the reliabilist conception of science with discussions of sample case studies where the reliabilist conception of science has been applied to actual scientific research. For obvious reasons none of the grand conceptions of science from the distant past is adequate. Towards the end of this paper I give some substance to the claim that among the few contemporary conceptions of science reliabilist epistemology is the the most comprehensive account. For only it systematically elaborates the ideas of reliability and computability accompanying science from its inception. None of the past or contemporary alternatives to a thoroughly revised understanding of science offered by the reliabilist approach can embrace the recent outburst of new sciences such as computer science, Bayesian statistics and cognitive science. An outline of open problems and directions for future research concludes the paper. (shrink)

N. Cartwright's recent results on invariance under intervention and causality (2003) are reconsidered. Procedural approach to causality elicited in this paper and contrasted with Cartwright's apparently philosophical one unravels certain ramifications of her results. The procedural approach seems to license only a constrained notion of intervention and in consequence the "correctness to invariance" part of Cartwright's first theorem fails for a class of cases. The converse "invariance to correctness" part of the theorem relies heavily on modeling assumptions which prove to (...) be difficult to validate in practice and are often buttressed by independently acquired evidence. (shrink)