An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences. In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent (...) explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility—the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized. When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993. (shrink)

The role of pictures and visual modes of presentation of data in science is a topic of increasing interest to workers in artificial intelligence, problem solving, and scientists in all fields who must deal with large quantities of complex multidimensional data. Drawing on studies of animal motion, aerodynamics, morphological transformations, the history of linkage mapping, and the analysis of deterministic chaos, I focus on the strengths and limitations of our visual system, the analysis of problems particularly suited to visualization-the analysis (...) of similarities and differences between complex objects, and problems making conjoint use of information from several complex images. (shrink)

Science once had an unshakable faith in its ability to bring the forces of nature—even human nature—under control. In this wide-ranging book Anson Rabinbach examines how developments in physics, biology, medicine, psychology, politics, and art employed the metaphor of the working body as a human motor. From nineteenth-century theories of thermodynamics and political economy to the twentieth-century ideals of Taylorism and Fordism, Rabinbach demonstrates how the utopian obsession with energy and fatigue shaped social thought across the ideological spectrum.

A complete, illustrated survey of Etienne-Jules Marey's work that investigates the far reaching effects of her inventions on stream-of-consciousness literature, psychoanalysis, Bergsonian philosophy, and the art of cubists and futurists.