Online research in philosophy

Because the label "computing and philosophy" can seem like an ad hoc attempt to tie computing to philosophy, it is important to explain why it is not, what it studies (or does) and how it differs from research in, say, "computing and history," or "computing and biology". The American Association for History and Computing is "dedicated to the reasonable and productive marriage of history and computer technology for teaching, researching and representing history through scholarship and public history" (http://theaahc.org). More pervasive, work in computing and biology enjoys the convenient name of "bioinformatics...the science of using information to understand biology..., a subset of the larger field of computational biology, the application of quantitative analytical techniques in modeling biological systems" (http://oreilly.com/catalog/bioskills/chapter/ ch01.html). The recent venture of the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers to publish the Transactions on Computational Biology and Bioinformatics (TCBB) bears witness to the reach of computing and biology and underscores its objective. TCBB intends to report "archival research results related to the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development and optimization of biological databases; and important biological results that are obtained from the use of these methods, programs, and databases" (http://tcbb.acm.org). In the case of "computing and history" and "bioinformatics," each discipline stands in a particular relationship to computers that raises questions unique to itself. But both are devoted to the development of computational tools to aid discovery..

The fundamental assumptions in Dijkstra''s influential article on computing science teaching are challenged. Dijkstra''s paper presents the radical novelties of computing, and the consequent problems that we must tackle through a formal, logic-based approach to program derivation. Dijkstra''s main premise is that the algorithmic programming paradigm is the only one, in fact, the only possible one. It is argued that there is at least one other, the network-programming paradigm, which itself is a radical novelty with respect to the implementation of problems on computers. And, as one might expect of a radical alternative, it shows much of the conventional wisdom concerning computing science, which Dijkstra variously attacks and dispenses, to be special pleading; not universals of computing at all. Finally, we explore what is known of this new paradigm in order to see what light it sheds on the fundamental problems that computing really does present to us. Not surprisingly, some become less problematic, some disappear altogether and others take their place, but, in general, it must be of benefit to modern computer technology to gain a wider perspective on the possibilities instead of seeing everything through the traditional tunnel of programming as formula derivation, and computers as the requisite, special type of symbol manipulation device.

This accessible book explores the development, history and future of Information and Communication Technology using examples from philosophy. Luciano Floridi offers both an introduction to these technologies and a philosophical analysis of the problems they pose. The book examines a wide range of areas of technology, including the digital revolution, the Web and Internet, Artificial Intelligence and CD-ROMS. We see how the relationship between philosophy and computing provokes many crucial philosophical questions. Ultimately, Philosophy and Computing outlines what the future philosophy of information will need to undertake.

http://www.diva-portal.org/mdh/theses/abstract.xsql?dbid=153.

Critiques of Knowing explores what happens to science and computing when we think of them as texts. Lynette Hunter elegantly weaves together such vast areas of thought as rhetoric, politics, AI, computing, feminism, science studies, aesthetics and epistemology. This book shows us that what we need is a radical shake-up of approaches to the arts if the critiques of science and computing are to come to any fruition.

Written by world-leading experts, this book draws together a number of important strands in contemporary approaches to the philosophical and scientific questions that emerge when dealing with the issues of computing, information, cognition and the conceptual issues that arise at their intersections. It discovers and develops the connections at the borders and in the interstices of disciplines and debates. This volume presents a range of essays that deal with the currently vigorous concerns of the philosophy of information, ontology creation and control, bioinformation and biosemiotics, computational and post-computation approaches to the philosophy of cognitive science, computational linguistics, ethics, and education. http://www.amazon.ca/Computation-Information-Cognition-Gordana-Dodig-Crnkovic/dp/1847180906.

Computers today are not only the calculation tools - they are directly (inter)acting in the physical world which itself may be conceived of as the universal computer (Zuse, Fredkin, Wolfram, Chaitin, Lloyd). In expanding its domains from abstract logical symbol manipulation to physical embedded and networked devices, computing goes beyond Church-Turing limit (Copeland, Siegelman, Burgin, Schachter). Computational processes are distributed, reactive, interactive, agent-based and concurrent. The main criterion of success of computation is not its termination, but the adequacy of its response, its speed, generality and flexibility; adaptability, and tolerance to noise, error,faults, and damage. Interactive computing is a generalization of Turing computing, and it calls for new conceptualizations (Goldin, Wegner). In the info-computationalist framework, with computation seen as information processing, natural computation appears as the most suitable paradigm of computation and information semantics requires logical pluralism.

Since the birth of computing as an academic discipline, the disciplinary identity of computing has been debated fiercely. The most heated question has concerned the scientific status of computing. Some consider computing to be a natural science and some consider it to be an experimental science. Others argue that computing is bad science, whereas some say that computing is not a science at all. This survey article presents viewpoints for and against computing as a science. Those viewpoints are analyzed against basic positions in the philosophy of science. The article aims at giving the reader an overview, background, and a historical and theoretical frame of reference for understanding and interpreting some central questions in the debates about the disciplinary identity of computer science. The article argues that much of the discussion about the scientific nature of computing is misguided due to a deep conceptual uncertainty about science in general as well as computing in particular.

Supplementary to matter and energy, information is the third essence for modeling the natural world. An emerging discipline known as cognitive informatics (CI) is developed recently that forms a profound interdisciplinary study of cognitive and information sciences, and tackles the common root problems sharing by informatics, computing, software engineering, artificial intelligence, cognitive science, neuropsychology, philosophy, linguistics, and life science. CI focuses on internal information processing mechanisms and the natural intelligence of the brain. This paper describes the historical development of informatics from the classical information theory and contemporary informatics, to CI. The domain of CI, and its interdisciplinary nature are explored. Foundations of CI, particularly the brain versus the mind, the acquired life functions versus the inherited ones, and generic relationships between information, matter, and energy are investigated. The potential engineering applications of CI and perspectives on future research are discussed. It is expected that the investigation into CI will result in fundamental findings towards the development of next generation IT and software technologies, and new architectures of computing systems.

Supplementary to matter and energy, information is the third essence for modeling the natural world. An emerging discipline known as cognitive informatics (CI) is developed recently that forms a profound interdisciplinary study of cognitive and information sciences, and tackles the common root problems sharing by informatics, computing, software engineering, artificial intelligence, cognitive science, neuropsychology, philosophy, linguistics, and life science. CI focuses on internal information processing mechanisms and the natural intelligence of the brain. This paper describes the historical development of informatics from the classical information theory and contemporary informatics, to CI. The domain of CI, and its interdisciplinary nature are explored. Foundations of CI, particularly the brain versus the mind, the acquired life functions versus the inherited ones, and generic relationships between information, matter, and energy are investigated. The potential engineering applications of CI and perspectives on future research are discussed. It is expected that the investigation into CI will result in fundamental findings towards the development of next generation IT and software technologies, and new architectures of computing systems.