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A taxonomy of explanations to support Explainability-by-Design

arXiv 2206.04438 ↗First posted 9 Jun 2022cs.AI cs.CYcited by 0

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Abstract (arXiv)

As automated decision-making solutions are increasingly applied to all aspects of everyday life, capabilities to generate meaningful explanations for a variety of stakeholders (i.e., decision-makers, recipients of decisions, auditors, regulators...) become crucial. In this paper, we present a taxonomy of explanations that was developed as part of a holistic 'Explainability-by-Design' approach for the purposes of the project PLEAD. The taxonomy was built with a view to produce explanations for a wide range of requirements stemming from a variety of regulatory frameworks or policies set at the organizational level either to translate high-level compliance requirements or to meet business needs. The taxonomy comprises nine dimensions. It is used as a stand-alone classifier of explanations conceived as detective controls, in order to aid supportive automated compliance strategies. A machinereadable format of the taxonomy is provided in the form of a light ontology and the benefits of starting the Explainability-by-Design journey with such a taxonomy are demonstrated through a series of examples.

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References · 9

  1. 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,543
  2. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
  3. 2017Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Modelscited by 202
  4. 2018Explaining Explanations in AIcited by 136
  5. 2021Human-Centered Explainable AI (XAI): From Algorithms to User Experiencescited by 123
  6. 2019The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasonscited by 115
  7. 2019Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approachescited by 101
  8. 2020Human-centered Explainable AI: Towards a Reflective Sociotechnical Approachcited by 90
  9. 2019Towards a Characterization of Explainable Systemscited by 4

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