Expectational v. Instrumental Reasoning: What Statistics Contributes to Practical Reasoning

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Published: Oct 4, 2017
DOI: https://doi.org/10.13153/diam.53.0.1104
Keywords:
statistics, distributions, risk, instrumental reasoning, expectational reasoning

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Mariam Thalos
University of Tennessee, Department of Philosophy

Abstract

Utility theories—both Expected Utility (EU) and non-Expected Utility (non-EU) theories—offer numericalized representations of classical principles meant for the regulation of choice under conditions of risk—a type of formal representation that reduces the representation of risk to a single number. I shall refer to these as risk-numericalizing theories of decision. I shall argue that risk--numericalizing theories (referring both to the representations and to the underlying axioms that render numericalization possible) are not satisfactory answers to the question: “How do I take the (best) means to my ends?” In other words, they are inadequate or incomplete as instrumental theories. They are inadequate because they are poor answers to the question of what it is for an option to be instrumental towards an end. To say it another way, they do not offer a sufficiently rich account of what it is for something to be a means (an instrument) toward an end.

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How to Cite
“Expectational V. Instrumental Reasoning: What Statistics Contributes to Practical Reasoning”. 2017. Diametros, no. 53 (October): 125-49. https://doi.org/10.13153/diam.53.0.1104.
Issue
No. 53 (2017)
Section
Ethics and Uncertainty

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Author Biography

Mariam Thalos, University of Tennessee, Department of Philosophy

Mariam Thalos, Professor
Department of Philosophy
University of Tennessee, Knoxville
801 McClung Tower
Knoxville TN 37996-0480
US

E-mail: m.thalos@gmail.com

How to Cite

“Expectational V. Instrumental Reasoning: What Statistics Contributes to Practical Reasoning”. 2017. Diametros, no. 53 (October): 125-49. https://doi.org/10.13153/diam.53.0.1104.
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