Filed under journal | Tags: · algorithm, code, computation, language, machine, philosophy, rhetoric, semantics, software studies, theory
“How can machines be rhetorical? The readers of Computational Culture need not be convinced that computation drives the digital and networked spaces in which we interact, argue and communicate: word processing programs, videogames, banking and commerce systems, social networking sites, and smartphone apps that track our data (both with and without our knowledge) are all evidence that computation in code shapes nearly every space we inhabit. Computation in code affects and effects our lives. Computational machines affect us through their programming and design, as well the discourse they can generate, via text, image, sound, and so on. By writing computer code and software, programmers and designers construct machines that make arguments and judgments and address audiences both machinic and human. In this sense, even the most mundane computational technologies can be seen as rhetorical –from the grocery store check-out scanner to the high school graphing calculator–because any computational machine shapes and constrains behavior. […]
Software studies has paved the way for many disciplines to approach software as an object of study and computer programs as written artifacts, and we may add rhetoric to our toolkit to do so. We can use rhetoric to interpret the ways that computation addresses and responds to various audiences and exigencies, makes assertions about identities, and ultimately participates in a complex ecology of forces that shape behavior and perception. This version of rhetoric is more expansive than the limited, Aristotelian definition rhetoric as the ‘available means of persuasion.’ Just as software studies recognizes that software is more than code, and that code is more than ones and zeros, contemporary rhetoric is interested in more than the content of arguments; it also concerns the relational forces that precede and exceed arguments.” (from the introduction)
With thematic texts by Steve Holmes, John Tinnell, Kevin Brock, Elizabeth Losh, Jennifer Maher, Alexander Monea, Andreas Birkbak & Hjalmar Bang Carlsen, Matthew Bellinger; articles by M. Beatrice Fazi, Erica Robles-Anderson and Patrik Svensson, Michael Lachney, William Babbitt & Ron Eglash, and review section.
Edited by Annette Vee and James J. Brown, Jr.
Published in January 2016
Filed under book | Tags: · algorithm, anticipation, biology, causality, complex systems, complexity, environment, life, machine, mathematics, mind, philosophy of science, physics, science, semantics, systems theory, technology, theory
“In this collection of twenty-two essays, Rosen takes to task the central objective of the natural sciences, calling into question the attempt to create objectivity in a subjective world. The book opens with an exploration of the interaction between biology and physics, unpacking Schrödinger´s famous text What Is Life? and revealing the shortcomings of the notion that artificial intelligence can truly replicate life.
He also refutes the thesis that mathematical models of reality can be reflected entirely in algorithms, that is, are of a purely syntactical character. He argues that it is the noncomputable, nonformalizable nature of biology that makes organisms complex, and that these systems are generic, whereas those systems described by reductionistic reasoning are simple and rare.
An intriguing enigma links all of the essays: ‘How can science explain the unpredictable?'”
Publisher Columbia University Press, 1999
Complexity in Ecological Systems series
ISBN 023110510X, 9780231105101
PDF (removed on 2019-10-30 upon request from Judith Rosen)Comment (0)
Filed under book | Tags: · artificial intelligence, cognitive science, computing, semantics, turing machine
“Classical computationalism—-the view that mental states are computational states—-has come under attack in recent years. Critics claim that in defining computation solely in abstract, syntactic terms, computationalism neglects the real-time, embodied, real-world constraints with which cognitive systems must cope. Instead of abandoning computationalism altogether, however, some researchers are reconsidering it, recognizing that real-world computers, like minds, must deal with issues of embodiment, interaction, physical implementation, and semantics.
This book lays the foundation for a successor notion of computationalism. It covers a broad intellectual range, discussing historic developments of the notions of computation and mechanism in the computationalist model, the role of Turing machines and computational practice in artificial intelligence research, different views of computation and their role in the computational theory of mind, the nature of intentionality, and the origin of language.”
Publisher MIT Press, 2002
ISBN 0262194783, 9780262194785