Autorentext

James Evans is the Max Palevsky Professor of History and Civilization in Sociology and director of Knowledge Lab at the University of Chicago, where he also serves as faculty director of the program in computational social science. He holds an external professorship at the Santa Fe Institute and is the author of numerous articles in Science, Nature, and PNAS. ​Adrian Johns is the Allan Grant Maclear Professor of History at the University of Chicago. His many books include The Nature of the Book: Print and Knowledge in the Making, Piracy: The Intellectual Property Wars from Gutenberg to Gates, and, most recently, The Science of Reading: Information, Media, and Mind in Modern America, all three also published by the University of Chicago Press.

Klappentext

Perceptively explores the shifting intersections between algorithmic systems and human practices in the modern era. How have algorithmic systems and human practices developed in tandem since 1800? This volume of Osiris deftly addresses the question, dispelling along the way the traditional notion of algorithmic "code" and human "craft" as natural opposites. Instead, algorithms and humans have always acted in concert, depending on each other to advance new knowledge and produce social consequences. By shining light on alternative computational imaginaries, Beyond Craft and Code opens fresh space in which to understand algorithmic diversity, its governance, and even its conservation. The volume contains essays by experts in fields extending from early modern arithmetic to contemporary robotics. Traversing a range of cases and arguments that connect politics, historical epistemology, aesthetics, and artificial intelligence, the contributors collectively propose a novel vocabulary of concepts with which to think about how the history of science can contribute to understanding today's world. Ultimately, Beyond Craft and Code reconfigures the historiography of science and technology to suggest a new way to approach the questions posed by an algorithmic culture-not only improving our understanding of algorithmic pasts and futures but also unlocking our ability to better govern our present.