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Towards a framework for challenging ML-based decisions

Abstract : The goal of the work presented in this paper is to provide techniques to challenge the results of an algorithmic decision system relying on machine learning. We highlight the differences between explanations and justifications and outline a framework to generate evidence to support or to dismiss challenges. We also present the results of a preliminary study to assess users' perception of the different types of challenges proposed here and their benefits to detect incorrect results.
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Contributor : Clement Henin <>
Submitted on : Monday, September 7, 2020 - 6:32:42 PM
Last modification on : Wednesday, October 14, 2020 - 4:00:47 AM
Long-term archiving on: : Wednesday, December 2, 2020 - 10:22:04 PM


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  • HAL Id : hal-02932467, version 1



Clément Henin, Daniel Le Métayer. Towards a framework for challenging ML-based decisions. DeceptECAI 2020 - 1st International Workshop on Deceptive AI @ECAI2020, Aug 2020, Santiago de Chili, Chile. pp.1-13. ⟨hal-02932467⟩



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