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Evaluating Explainability Methods Intended for Multiple Stakeholders

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2021

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Springer

Zusammenfassung

Explanation mechanisms for intelligent systems are typically designed to respond to specific user needs, yet in practice these systems tend to have a wide variety of users. This can present a challenge to organisations looking to satisfy the explanation needs of different groups using an individual system. In this paper we present an explainability framework formed of a catalogue of explanation methods, and designed to integrate with a range of projects within a telecommunications organisation. Explainability methods are split into low-level explanations and high-level explanations for increasing levels of contextual support in their explanations. We motivate this framework using the specific case-study of explaining the conclusions of field network engineering experts to non-technical planning staff and evaluate our results using feedback from two distinct user groups; domain-expert telecommunication engineers and non-expert desk agent staff. We also present and investigate two metrics designed to model the quality of explanations - Meet-In-The-Middle (MITM) and Trust-Your-Neighbours (TYN). Our analysis of these metrics offers new insights into the use of similarity knowledge for the evaluation of explanations.

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Martin, Kyle; Liret, Anne; Wiratunga, Nirmalie; Owusu, Gilbert; Kern, Mathias (2021): Evaluating Explainability Methods Intended for Multiple Stakeholders. KI - Künstliche Intelligenz: Vol. 35, No. 0. DOI: 10.1007/s13218-020-00702-6. Springer. PISSN: 1610-1987. pp. 397-411

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