The philosophy of information (PI) is a new area of research with its own field of investigation and methodology. This article, based on the Herbert A. Simon Lecture of Computing and Philosophy I gave at Carnegie Mellon University in 2001, analyses the eighteen principal open problems in PI. Section 1 introduces the analysis by outlining Herbert Simon's approach to PI. Section 2 discusses some methodological considerations about what counts as a good philosophical problem. The discussion centers on Hilbert's famous analysis (...) of the central problems in mathematics. The rest of the article is devoted to the eighteen problems. These are organized into five sections: problems in the analysis of the concept of information, in semantics, in the study of intelligence, in the relation between information and nature, and in the investigation of values. (shrink)

This paper outlines a quantitative theory of strongly semantic information (TSSI) based on truth-values rather than probability distributions. The main hypothesis supported in the paper is that the classic quantitative theory of weakly semantic information (TWSI), based on probability distributions, assumes that truth-values supervene on factual semantic information, yet this principle is too weak and generates a well-known semantic paradox, whereas TSSI, according to which factual semantic information encapsulates truth, can avoid the paradox and is more in line with the (...) standard conception of what generally counts as semantic information. After a brief introduction, section two outlines the semantic paradox implied by TWSI, analysing it in terms of an initial conflict between two requisites of a quantitative theory of semantic information. In section three, three criteria of semantic information equivalence are used to provide a taxonomy of quantitative approaches to semantic information and introduce TSSI. In section four, some further desiderata that should be fulfilled by a quantitative TSSI are explained. From section five to section seven, TSSI is developed on the basis of a calculus of truth-values and semantic discrepancy with respect to a given situation. In section eight, it is shown how TSSI succeeds in solving the paradox. Section nine summarises the main results of the paper and indicates some future developments. (shrink)

The prelims comprise: Introduction Semantic Information The Mathematical Theory of Communication Some Philosophical Approaches to Semantic Information Conclusion Acknowledgments Some Web Resources.

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske‐Grice approach: meaningful and well‐formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth‐values do not supervene on (...) semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo‐information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo‐information. As a consequence, SDI is revised to include a necessary truth‐condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition. (shrink)

Computing is changing the traditional field of Philosophy of Science in a very profound way. First as a methodological tool, computing makes possible ``experimental Philosophy'' which is able to provide practical tests for different philosophical ideas. At the same time the ideal object of investigation of the Philosophy of Science is changing. For a long period of time the ideal science was Physics (e.g., Popper, Carnap, Kuhn, and Chalmers). Now the focus is shifting to the field of Computing/Informatics. There are (...) many good reasons for this paradigm shift, one of those being a long standing need of a new meeting between the sciences and humanities, for which the new discipline of Computing/Informatics gives innumerable possibilities. Contrary to Physics, Computing/Informatics is very much human-centered. It brings a potential for a new Renaissance, where Science and Humanities, Arts and Engineering can reach a new synthesis, so very much needed in our intellectually split culture. This paper investigates contemporary trends and the relation between the Philosophy of Science and the Philosophy of Computing and Information, which is equivalent to the present relation between Philosophy of Science and Philosophy of Physics. (shrink)

Surprisingly, modified versions of the confirmation theory (Carnap and Hempel) and truth approximation theory (Popper) turn out to be smoothly sythesizable. The glue between the two appears to be the instrumentalist methodology, rather than that of the falsificationalist. The instrumentalist methodology, used in the separate, comparative evaluation of theories in terms of their successes and problems (hence, even if already falsified), provides in theory and practice the straight road to short-term empirical progress in science ( à la Laudan). It is (...) also argued that such progress is also functional for all kinds of truth approximation: observational, referential, and theoretical. This sheds new light on the long-term dynamics of science and hence on the relation between the main epistemological positions, viz., instrumentalism (Toulmin, Laudan), constructive empiricism (Van Fraassen), referential realism (Hacking, Cartwright), and theory realism of a non-essentialist nature (constructive realism à la Popper). Readership: Open minded philosophers and scientists. The book explains and justifies the scientist's intuition that the debate among philosophers about instrumentalism and realism has almost no practical consequences. (shrink)

INTRODUCTION When Karl Popper published in' his definition of closer-to-the- truth this was an important intellectual event, but not a shocking one. ...

Tom Stonier writes from the perspective of a theoretical biologist looking at the evolution of information systems as a basis for studying the phenomena of information, intelligence and meaning. Through his exploration of the 'meaning of meaning', and by looking at how neurons create a brain which understands information inputs and then operates on the information received, he is able to propose a theory of how the brain works and to explore how this theory may be used in the development (...) of information science. (shrink)