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Developing a Catalogue of Explainability Methods to Support Expert and Non-expert Users

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Artificial Intelligence XXXVI (SGAI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11927))

Abstract

Organisations face growing legal requirements and ethical responsibilities to ensure that decisions made by their intelligent systems are explainable. However, provisioning of an explanation is often application dependent, causing an extended design phase and delayed deployment. In this paper we present an explainability framework formed of a catalogue of explanation methods, allowing integration to a range of projects within a telecommunications organisation. These methods are split into low-level explanations, high-level explanations and co-created explanations. We motivate and evaluate this framework using the specific case-study of explaining the conclusions of field engineering experts to non-technical planning staff. Feedback from an iterative co-creation process and a qualitative evaluation is indicative that this is a valuable development tool for use in future company projects.

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Author information

Authors and Affiliations

  1. Robert Gordon University, Aberdeen, Scotland

    Kyle Martin & Nirmalie Wiratunga

  2. BT France, Paris, France

    Anne Liret

  3. British Telecommunications, London, UK

    Gilbert Owusu & Mathias Kern

Authors
  1. Kyle Martin
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  2. Anne Liret
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  3. Nirmalie Wiratunga
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  4. Gilbert Owusu
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  5. Mathias Kern
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Corresponding author

Correspondence to Kyle Martin .

Editor information

Editors and Affiliations

  1. University of Portsmouth, Portsmouth, UK

    Max Bramer

  2. Middlesex University, London, UK

    Miltos Petridis

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Martin, K., Liret, A., Wiratunga, N., Owusu, G., Kern, M. (2019). Developing a Catalogue of Explainability Methods to Support Expert and Non-expert Users. In: Bramer, M., Petridis, M. (eds) Artificial Intelligence XXXVI. SGAI 2019. Lecture Notes in Computer Science(), vol 11927. Springer, Cham. https://doi.org/10.1007/978-3-030-34885-4_24

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  • DOI: https://doi.org/10.1007/978-3-030-34885-4_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34884-7

  • Online ISBN: 978-3-030-34885-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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