Information and Diagrammatic Reasoning: An Inferentialist Reading

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In a series of papers [4, 5, 6] on semantic information, Floridi has argued in favor of veridicality thesis (VT). According to this idea, any epistemically-oriented concept of information must have truth as one of its necessary conditions. That is, for Floridi, if a message x carries information of the kind “that is capable of yielding knowledge” (In Dretske’s words, [2, p. 45]), then x carries something that is true. Two challenges have been raised against VT. First, some philosophers have argued that VT wrongly collapses misinformation with non-informativeness [3, 9]. Secondly, it is not clear whether VT can give an adequate account of the information used in hypothetical reasoning and knowledge. In particular, think about information produced by logical and geometrical diagrams. Such representation systems are surely informative and yield knowledge even if they most of the time represent non-actualized, hypothetical scenarios. Focusing on the latter challenge, in this paper I propose an alternative definition of an epistemically-oriented concept of information. Instead of VT, based on semantic inferentialism [1, 8], I propose a definition of information in terms of what can be called the inferentiality thesis: if a message x carries epistemically-oriented information about an event p, then x reveals the inferential articulation of p. In other words, according to this inferentialist reading, information about p yields knowledge on what follows from and what implies p. Finally, I show that this inferentialist definition gives a nice account of the information used in hypothetical, diagrammatic reasoning.

References

[1] Robert Brandom. Making it Explicit: Reasoning, Representing, and Discursive Commitment. Harvard university press, 1998.

[2] Fred Dretske. Knowledge and the Flow of Information. CSLI Publications, 1981.

[3] James H Fetzer. Information: Does it have to be true? Minds and Machines, 14(2):223–229, 2004.

[4] Luciano Floridi. Outline of a theory of strongly semantic information. Minds and Machines, 14(2):197–221, 2004.

[5] Luciano Floridi. Is semantic information meaningful data? Philosophy and Phenomenological Research, 70(2):351–370, 2005.

[6] Luciano Floridi. In defence of the veridical nature of semantic information. European Journal of Analytic Philosophy, 3(1):31–41, 2007.

[7] Nancy J Nersessian and Miles MacLeod. Models and simulations. In Springer Handbook of Model-Based Science, pages 119–132. Springer, 2017.

[8] Jaroslav Peregrin. Inferentialism: why rules matter. Springer, 2014.

[9] Andrea Scarantino and Gualtiero Piccinini. Information without truth. Metaphilosophy, 41(3):313–330, 2010.

[10] Sun-Joo Shin. The Logical Status of Diagrams. Cambridge University Press, 1994.

[11] Sun-Joo Shin, Oliver Lemon, and John Mumma. Diagrams. In Edward N. Zalta, editor, The Stanford Encyclopedia of Philosophy. Metaphysics Research Lab, Stanford University, winter 2018 edition, 2018.

Nome
Bruno Mendonça (Unicamp)
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Finished
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Arbitrariness and Genericity
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