Kasirzadeh, Atoosa and Klein, Colin (2021) 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.
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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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| Item Type: | Published Article or Volume | |||||||||
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| Keywords: | Ethics of Artificial Intelligence Philosophy of Artificial Intelligence | |||||||||
| Subjects: | Specific Sciences > Artificial Intelligence > AI and Ethics Specific Sciences > Computer Science General Issues > Ethical Issues Specific Sciences > Artificial Intelligence > Machine Learning |
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| Depositing User: | Dr. Atoosa Kasirzadeh | |||||||||
| Date Deposited: | 22 May 2021 21:48 | |||||||||
| Last Modified: | 22 May 2021 21:48 | |||||||||
| Item ID: | 19091 | |||||||||
| Journal or Publication Title: | Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society | |||||||||
| Publisher: | ACM | |||||||||
| Subjects: | Specific Sciences > Artificial Intelligence > AI and Ethics Specific Sciences > Computer Science General Issues > Ethical Issues Specific Sciences > Artificial Intelligence > Machine Learning |
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| Date: | 2021 | |||||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/19091 |
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