Thomas Nickles

The history of science is articulated by moments of discovery. Yet, these 'moments' are not simple or isolated events in science. Just as a scientific discovery illuminates our understanding of nature or of society, and reveals new connections among phenomena, so too does the history of scientific activity and the analysis of scientific reasoning illuminate the processes which give rise to moments of discovery and the complex network of consequences which follow upon such moments. Understanding discovery has not been, until recently, a major concern of modem philosophy of science. Whether the act of discoyery was regarded as mysterious and inexplicable, or obvious and in no need of explanation, modem philosophy of science in effect bracketed the question. It concentrated instead on the logic of scientific explanation or on the issues of validation or justification of scientific theories or laws. The recent revival of interest in the context of discovery, indeed in the acts of discovery, on the part of philosophers and historians of science, represents no one particular method'ological or philosophical orientation. It proceeds as much from an empiricist and analytical approach as from a sociological or historical one; from considerations of the logic of science as much as from the alogical or extralogical contexts of scientific tho'¢tt and practice. But, in general, this new interest focuses sharply on the actual historical and contem porary cases of scientific discovery, and on an examination of the act or moment of discovery in situ.

Pure consequentialists hold that all theoretical justification derives from testing the consequences of hypotheses, while generativists maintain that reasoning (some feature of) the hypothesis from we already know is an important form of justification. The strongest form of justification (they claim) is an idealized discovery argument. In the guise of H-D methodology, consequentialism is widely supposed to have defeated generativism during the 19th century. I argue that novel prediction fails to overcome the logical weakness of consequentialism or to render generative methodology superfluous. Specifically, Bayesian consequentialism is not an alternative to generativism but reduces to an instance of it.

The last forty years have produced a dramatic reversal in leading accounts of science. Once thought necessary to (explain) scientific progress, a rigid method of science is now widely considered impossible. Study of products yields to study of processes and practices, .unity gives way to diversity, generality to particularity, logic to luck, and final justification to heuristic scaffolding. I sketch the story, from Bacon and Descartes to the present, of the decline and fall of traditional scientific method, conceived as The Central Planning Bureau for Science or as Rationality Czar. I defend a deflationary account of method and of rational judgment,. with emphasis on heuristic appraisal and cognitive economy.

Reduction was once a central topic in philosophy of science. I claim that it remains important, especially when applied to problems and problem-solutions rather than only to large theory-complexes. Without attempting a comprehensive classification, I discuss various kinds of problem reductions and similar relations, illustrating them, inter alia, in terms of the blackbody problem and early quantization problems. Kuhn's early work is suggestive here both for structuralist theory of science and for the line I prefer to take. My central claims in the paper are (1) that problem reduction is important in its own right and does not "reduce" to theory reduction and (2) that problem reduction is generally more important than theory reduction to methodology as the "control theory" of inquiry.

The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; the applicability of mathematical models to the real world and their effectiveness; the links between models and inferences; and models as a means for acquiring new knowledge. It analyzes different examples of models in physics, biology, mathematics and engineering. Written for researchers and graduate students, it provides a cross-disciplinary reference guide to the notion and the use of models and inferences in science.

Looking at Thomas Kuhn's work from a cognitive science perspective helps to articulate and to legitimize, to some degree, his rejection of traditional views of concepts, categorization, theory structure, and rule-based problem solving. Whereas my colleagues focus on the later Kuhn of the MIT years, I study the early Kuhn as an anticipation of case-based reasoning and schema theory. These recent developments in cognitive psychology and artificial intelligence may point toward a more computational version of Kuhn's ideas, but they also expose ambiguities in his work, notably in his understanding of exemplars

Contemporary Philosophy in Focus offers a series of introductory volumes to many of the dominant philosophical thinkers of the current age. Thomas Kuhn, the author of The Structure of Scientific Revolutions, is probably the best-known and most influential historian and philosopher of science of the last 25 years, and has become something of a cultural icon. His concepts of paradigm, paradigm change and incommensurability have changed the way we think about science. This volume offers an introduction to Kuhn's life and work and then considers the implications of Kuhn's work for philosophy, cognitive psychology, social studies of science and feminism. The volume is more than a retrospective on Kuhn, exploring future developments of cognitive and information services along Kuhnian lines. Outside of philosophy the volume will be of particular interest to professionals and students in cognitive science, history of science, science studies and cultural studies.

In this paper the relation between scientific problems and the constraints on their solutions is explored. First the historical constraints on the solution to the blackbody radiation problem are set out. The blackbody history is used as a guide in sketching a working taxonomy of constraints, which distinguishes various kinds of reductive and nonreductive constraints. Finally, this discussion is related to some work in erotetic logic. The hypothesis that scientific problems can be identified with structured sets of constraints is interesting; however, a full defense of the identification thesis requires the resolution of some unsolved problems.

Does the viability of the discovery program depend on showing either (1) that methods of generating new problem solutions, per se, have special probative weight (the per se thesis); or, (2) that the original conception of an idea is logically continuous with its justification (anti-divorce thesis)? Many writers have identified these as the key issues of the discovery debate. McLaughlin, Pera, and others recently have defended the discovery program by attacking the divorce thesis, while Laudan has attacked the discovery program by rejecting the per se thesis. This disagreement over the central issue has led to communication breakdown. I contend that both friends and foes of discovery mistake the central issues. Recognizing a form of divorce helps rather than hurts the discovery program. However, the per se thesis is not essential to the program (nor is the related debate over novel prediction); hence, the status of the per se thesis is a side issue. With these clarifications in hand, we can proceed to the next stage of the discovery debate--the development (or revival) of a generative conception of justification which goes beyond consequentialism to forge a strong linkage of generation (or rather, generatability) with justification

Davidson's defective defense of the consistency of (1) the causal interaction of mental and physical events, (2) the backing law thesis on causation, (3) the impossibility of lawfully explaining mental events is repaired by closer attention to the description-Relativity of explanation. Davidson wrongly allows that particular mental events are explainable when particular identities to physical events are known. The author argues that such identities are powerless to affect what features a given law can explain. Thus a great intelligence knowing all the physical laws could not explain a single mental event, As such, Even if he knew all particular identities

Although seriously defective, 17th-century ideas about discovery, justification, and positive science are not as hopeless, useless, and out of date as many philosophers assume. They appear to underlie modern scientific practice. The generationist view of justification interestingly links justification with discovery issues while employing a concept of empirical support quite foreign to the modern, consequentialist concept, which identifies empirical evidence with favorable test results (predictive/explanatory success). In the generationist sense, justification amounts to potential discovery or "discoverability". A partial defense of updated versions of these ideas is offered without disputing the importance of consequential testing. Much further work is needed!