Separating facts and evaluation: motivation, account, and learnings from a novel approach to evaluating the human impacts of machine learning

AI and Society:1-14 (forthcoming)
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Abstract

In this paper, we outline a new method for evaluating the human impact of machine-learning applications. In partnership with Underwriters Laboratories Inc., we have developed a framework to evaluate the impacts of a particular use of machine learning that is based on the goals and values of the domain in which that application is deployed. By examining the use of artificial intelligence in particular domains, such as journalism, criminal justice, or law, we can develop more nuanced and practically relevant understandings of key ethical guidelines for artificial intelligence. By decoupling the extraction of the facts of the matter from the evaluation of the impact of the resulting systems, we create a framework for the process of assessing impact that has two distinctly different phases.

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Ryan Jenkins
California Polytechnic State University, San Luis Obispo

References found in this work

After virtue: a study in moral theory.Alasdair C. MacIntyre - 1984 - Notre Dame, Ind.: University of Notre Dame Press.
Law’s Empire.Ronald Dworkin - 1986 - Harvard University Press.
Value in ethics and economics.Elizabeth Anderson - 1993 - Cambridge: Harvard University Press.
Two concepts of rules.John Rawls - 1955 - Philosophical Review 64 (1):3-32.

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