Syntactical Informational Structural Realism
- 165 Downloads
Luciano Floridi’s informational structural realism (ISR) takes a constructionist attitude towards the problems of epistemology and metaphysics, but the question of the nature of the semantical component of his view remains vexing. In this paper, I propose to dispense with the semantical component of ISR completely. I outline a Syntactical version of ISR (SISR for short). The unified entropy-based framework of information has been adopted as the groundwork of SISR. To establish its realist component, SISR should be able to dissolve the latching problem. We have to be able to account for the informational structures–reality relationship in the absence of the standard semantical resources. The paper offers a pragmatic solution to the latching problem. I also take pains to account for the naturalistic plausibility of this solution by grounding it in the recent computational neuroscience of the predictive coding and the free energy principle.
KeywordsInformational structural realism Free energy principle The unified entropy-based framework of information Predictive processing Syntactical informational structural realism
- Carnap, R. (1937). The logical syntax of language. Edited by A. Smeaton (trans.). London: Kegan Paul Trench, Trubner & Co.Google Scholar
- Clark, A. (2016a). Surfing uncertainty. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780190217013.001.0001.CrossRefGoogle Scholar
- Floridi, L. (2004). Outline of a theory of strongly semantic information. Minds and Machines, 14(2), 197–221. https://doi.org/10.1023/b:mind.0000021684.50925.c9.CrossRefGoogle Scholar
- Floridi, L. (2005). Is semantic information meaningful data? Philosophy and Phenomenological Research, 70(2), 351–370. https://doi.org/10.1111/j.1933-1592.2005.tb00531.x.CrossRefGoogle Scholar
- Floridi, L. (2014). Perception and testimony as data providers. Logique et Analyse, 57(226), 3421–3438.Google Scholar
- French, S. (2014). The structure of the world: Metaphysics and representation. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199684847.001.0001.CrossRefGoogle Scholar
- Frith, C. D. (2007). Making up the mind : How the brain creates our mental world. Malden: Blackwell Pub.Google Scholar
- Hohwy, J. (2013). The predictive mind. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199682737.001.0001.CrossRefGoogle Scholar
- Morris, C. (1938). Foundations of the theory of signs. Chicago, Ill: University of Chicago Press.Google Scholar
- Suppe, F. (1998). Understanding scientific theories: An assessment of developments, 1969–1998. In Philosophy of Science Biennial Meetings of the Philosophy of Science Association. Part II: Symposia Papers (Vol. 67, pp. 102–115). http://www.jstor.org/stable/188661.
- Suppes, P. (1962). Models of data. In Logic, methodology, and philosophy of science: Proceedings of 1960 International Congress (pp. 252–261). Stanford U: Stanford University Press.Google Scholar
- Suppes, P. (1967). What is a scientific theory?” In S. Morgenbesser (Ed.), Philosophy of science today (pp. 55–67). New York: Basic Books. https://www.google.com/_/chrome/newtab?espv=2&ie=UTF-8.
- Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind : Cognitive science and human experience. Cambridge: MIT Press.Google Scholar
- Worrall, J. (1989). Structural realism: The best of both worlds? Dialectica, 43(1–2), 99–124. https://doi.org/10.1111/j.1746-8361.1989.tb00933.x.CrossRefGoogle Scholar