Identifying the ⇜right⇝ level of explanation in a given situation

  • Valérie Beaudouin
  • , Isabelle Bloch
  • , David Bounie
  • , Stéphan Clémençon
  • , Florence d'Alché-Buc
  • , James Eagan
  • , Winston Maxwell
  • , Pavlo Mozharovskyi
  • , Jayneel Parekh

Research output: Contribution to journalConference articlepeer-review

Abstract

We present a framework for defining the “right” level of explainability based on technical, legal and economic considerations. Our approach involves three logical steps: First, define the main contextual factors, such as who is the audience of the explanation, the operational context, the level of harm that the system could cause, and the legal/regulatory framework. This step will help characterize the operational and legal needs for explanation, and the corresponding social benefits. Second, examine the technical tools available, including post-hoc approaches (input perturbation, saliency maps...) and hybrid AI approaches. Third, as function of the first two steps, choose the right levels of global and local explanation outputs, taking into the account the costs involved. We identify seven kinds of costs and emphasize that explanations are socially useful only when total social benefits exceed costs.

Original languageEnglish
Pages (from-to)63-66
Number of pages4
JournalCEUR Workshop Proceedings
Volume2659
Publication statusPublished - 1 Jan 2020
Event1st International Workshop on New Foundations for Human-Centered AI, NeHuAI 2020 - Santiago de Compostella, Spain
Duration: 4 Sept 2020 → …

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