The Ethical Gravity Thesis: Marrian Levels and the Persistence of Bias in Automated Decision-making Systems

Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES '21) (2021)
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Abstract

Computers are used to make decisions in an increasing number of domains. There is widespread agreement that some of these uses are ethically problematic. Far less clear is where ethical problems arise, and what might be done about them. This paper expands and defends the Ethical Gravity Thesis: ethical problems that arise at higher levels of analysis of an automated decision-making system are inherited by lower levels of analysis. Particular instantiations of systems can add new problems, but not ameliorate more general ones. We defend this thesis by adapting Marr’s famous 1982 framework for understanding information-processing systems. We show how this framework allows one to situate ethical problems at the appropriate level of abstraction, which in turn can be used to target appropriate interventions.

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Author Profiles

Atoosa Kasirzadeh
University of Toronto, St. George Campus (PhD)
Colin Klein
Australian National University

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References found in this work

Vision.David Marr - 1982 - W. H. Freeman.
Explaining the Brain.Carl F. Craver - 2007 - Oxford, GB: Oxford University Press.
Physical Computation: A Mechanistic Account.Gualtiero Piccinini - 2015 - Oxford, GB: Oxford University Press UK.

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