The Ethical Gravity Thesis: Marrian levels and the persistence of bias in automated decision-making systems

Atoosa Kasirzadeh, C. Klein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationAIES 2021
Subtitle of host publicationProceedings of the 2021 AAI/ACM Conference on AI, Ethics, and Society
PublisherAssociation for Computing Machinery (ACM)
Pages618-626
ISBN (Electronic)9781450384735
DOIs
Publication statusPublished - 30 Jul 2021
Event4th AAAI/ACM Conference on Artificial Intelligence, Ethics and Society: AIES 2021 - Virtual, Online
Duration: 19 May 202121 May 2021
Conference number: 170685

Conference

Conference4th AAAI/ACM Conference on Artificial Intelligence, Ethics and Society
Period19/05/2121/05/21

Keywords / Materials (for Non-textual outputs)

  • algorithmic bias
  • algorithmic fairness
  • ethical artificial intelligence
  • ethical machine learning
  • ethics of artificial intelligence
  • justice
  • philosophy of artificial intelligence
  • politics of artificial intelligence

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