David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Synthese 167 (2):363 - 389 (2009)
Various conceptual approaches to the notion of information can currently be traced in the literature in logic and formal epistemology. A main issue of disagreement is the attribution of truthfulness to informational data, the so called Veridicality Thesis (Floridi 2005). The notion of Epistemic Constructive Information (Primiero 2007) is one of those rejecting VT. The present paper develops a formal framework for ECI. It extends on the basic approach of Artemov’s logic of proofs (Artemov 1994), representing an epistemic logic based on dependent justifications, where the definition of information relies on a strict distinction from factual truth. The definition obtained by comparison with a Normal Modal Logic translates a constructive logic for “becoming informed”: its distinction from the logic of “being informed”—which internalizes truthfulness—is essential to a general evaluation of information with respect to truth. The formal disentanglement of these two logics, and the description of the modal version of the former as a weaker embedding into the latter, allows for a proper understanding of the Veridicality Thesis with respect to epistemic states defined in terms of information.
|Keywords||Philosophy of information Epistemic logic Logic of justification Modal logic|
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References found in this work BETA
Sergei Artëmov (1994). Logic of Proofs. Annals of Pure and Applied Logic 67 (1-3):29-59.
Sergei N. Artemov (2001). Explicit Provability and Constructive Semantics. Bulletin of Symbolic Logic 7 (1):1-36.
Alexandru Baltag & Lawrence S. Moss (2004). Logics for Epistemic Programs. Synthese 139 (2):165 - 224.
G. M. Bierman & V. C. V. de Paiva (2000). On an Intuitionistic Modal Logic. Studia Logica 65 (3):383-416.
James H. Fetzer (2004). Information: Does It Have to Be True? [REVIEW] Minds and Machines 14 (2):223-229.
Citations of this work BETA
Giuseppe Primiero (forthcoming). A Taxonomy of Errors for Information Systems. Minds and Machines:1-25.
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