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Why a Right to an Explanation of Algorithmic Decision-Making Should Exist: A Trust-Based Approach

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  • Kim, Tae Wan
  • Routledge, Bryan R.

Abstract

Businesses increasingly rely on algorithms that are data-trained sets of decision rules (i.e., the output of the processes often called “machine learning”) and implement decisions with little or no human intermediation. In this article, we provide a philosophical foundation for the claim that algorithmic decision-making gives rise to a “right to explanation.” It is often said that, in the digital era, informed consent is dead. This negative view originates from a rigid understanding that presumes informed consent is a static and complete transaction. Such a view is insufficient, especially when data are used in a secondary, noncontextual, and unpredictable manner—which is the inescapable nature of advanced artificial intelligence systems. We submit that an alternative view of informed consent—as an assurance of trust for incomplete transactions—allows for an understanding of why the rationale of informed consent already entails a right to ex post explanation.

Suggested Citation

  • Kim, Tae Wan & Routledge, Bryan R., 2022. "Why a Right to an Explanation of Algorithmic Decision-Making Should Exist: A Trust-Based Approach," Business Ethics Quarterly, Cambridge University Press, vol. 32(1), pages 75-102, January.
  • Handle: RePEc:cup:buetqu:v:32:y:2022:i:1:p:75-102_4
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    Cited by:

    1. Zhou, Ying & Li, Haoran & Xiao, Zhi & Qiu, Jing, 2023. "A user-centered explainable artificial intelligence approach for financial fraud detection," Finance Research Letters, Elsevier, vol. 58(PA).

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