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Measuring Information Deprivation: A Democratic Proposal

Yee, Adrian K. (2023) Measuring Information Deprivation: A Democratic Proposal. In: UNSPECIFIED.

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Abstract

There remains no consensus amongst social scientists as to how to quantify and understand forms of information deprivation such as misinformation. Measures of information deprivation typically employ a deficient conception of truth that should be replaced with measurement methods grounded in certain idealized norms of agreement about what kind of information ecosystem a society’s participants wish to live in. A mature science of information deprivation should include considerable democratic involvement that is sensitive to the value-ladenness of information quality and that doing so may enhance the predictive and explanatory power of models of information deprivation.


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Item Type: Conference or Workshop Item (UNSPECIFIED)
Creators:
CreatorsEmailORCID
Yee, Adrian K.adriankyle.yee@mail.utoronto.ca0000-0002-4170-9257
Keywords: social epistemology, machine learning, information sciences, misinformation, models, construct validity, political philosophy, epistemology, science and values
Subjects: General Issues > Data
Specific Sciences > Computation/Information
Specific Sciences > Computer Science
General Issues > Explanation
Specific Sciences > Artificial Intelligence > Machine Learning
General Issues > Models and Idealization
General Issues > Operationalism/Instrumentalism
General Issues > Science and Society
General Issues > Science and Policy
General Issues > Theory/Observation
General Issues > Values In Science
Depositing User: Adrian K. Yee
Date Deposited: 22 Jul 2022 22:33
Last Modified: 22 Jul 2022 22:33
Item ID: 20952
Subjects: General Issues > Data
Specific Sciences > Computation/Information
Specific Sciences > Computer Science
General Issues > Explanation
Specific Sciences > Artificial Intelligence > Machine Learning
General Issues > Models and Idealization
General Issues > Operationalism/Instrumentalism
General Issues > Science and Society
General Issues > Science and Policy
General Issues > Theory/Observation
General Issues > Values In Science
Date: 2023
URI: http://philsci-archive.pitt.edu/id/eprint/20952

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