X-RAI: A Framework for the Transparent, Responsible, and Accurate Use of Machine Learning in the Public Sector

Per Rådberg Nagbøl, Oliver Müller

    Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

    Abstract

    This paper reports on an Action Design Research project taking place in the Danish Business Authority focusing on quality assurance and evaluation of machine learning models in production. The design artifact is a Framework (X-RAI) which stands for Transparency (X-Ray), Responsible(R), and explainable (X-AI). X-RAI consist of four sub-frameworks: the Model Impact and Clarification Framework, Evaluation Plan Framework, Evaluation Support Framework, and Retraining Execution Framework for machine learning that builds upon the theory of interpretable AI and practical experiences tested on nine different machine learning models used by the Danish Business Authority.
    OriginalsprogEngelsk
    TitelEGOV-CeDEM-ePart 2020 : Proceedings of Ongoing Research, Practitioners, Workshops, Posters, and Projects of the International Conference EGOV-CeDEM-ePart 2020
    RedaktørerShefali Virkar, Marijn Janssen, Ida Lindgren, Ulf Melin, Francesco Mureddu, Peter Parycek, Efthimios Tambouris, Gerhard Schwabe, Hans Jochen Scholl
    Antal sider267
    UdgivelsesstedSweden
    ForlagCEUR Workshop Proceedings
    Publikationsdato2020
    Sider259
    StatusUdgivet - 2020
    BegivenhedIFIP EGOV-ePart-CeDEM conference - Linköping Univeristy, Linköping, Sverige
    Varighed: 31 aug. 20202 sep. 2020
    http://dgsociety.org/egov-2020/

    Konference

    KonferenceIFIP EGOV-ePart-CeDEM conference
    LokationLinköping Univeristy
    Land/OmrådeSverige
    ByLinköping
    Periode31/08/202002/09/2020
    Internetadresse
    NavnCEUR Workshop Proceedings
    Vol/bind2797
    ISSN1613-0073

    Emneord

    • Machine Learning Evaluation
    • Government
    • Interpretability

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