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A Methodology to Involve Domain Experts and Machine Learning Techniques in the Design of Human-Centered Algorithms

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Human Work Interaction Design. Designing Engaging Automation (HWID 2018)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 544))

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Abstract

Machine learning techniques are increasingly applied in Decision Support Systems. The selection processes underlying a conclusion often become black-boxed. Thus, the decision flow is not always comprehensible by developers or end users. It is unclear what the priorities are and whether all of the relevant information is used. In order to achieve human interpretability of the created algorithms, it is recommended to include domain experts in the modelling phase. Their knowledge is elicited through a combination of machine learning and social science techniques. The idea is not new, but it remains a challenge to extract and apply the experts’ experience without overburdening them. The current paper describes a methodology set to unravel, define and categorize the implicit and explicit domain knowledge in a less intense way by making use of co-creation to design human-centered algorithms, when little data is available. The methodology is applied to a case in the health domain, targeting a rheumatology triage problem. The domain knowledge is obtained through dialogue, by alternating workshops and data science exercises.

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Acknowledgement

We would like to thank Klaas Vandevyvere, MD, for his support in this research, both as project initiator and rheumatologist.

Author information

Authors and Affiliations

  1. imec-SMIT, Vrije Universiteit Brussel, Brussels, Belgium

    Tom Seymoens & An Jacobs

  2. Internet and Data Lab - imec, Universiteit Gent, Ghent, Belgium

    Femke Ongenae, Stijn Verstichel & Ann Ackaert

Authors
  1. Tom Seymoens
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  2. Femke Ongenae
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  3. An Jacobs
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  4. Stijn Verstichel
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  5. Ann Ackaert
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Corresponding author

Correspondence to Tom Seymoens .

Editor information

Editors and Affiliations

  1. University of Milan, Milan, Italy

    Barbara Rita Barricelli

  2. Aalto University, Aalto, Finland

    Virpi Roto

  3. Copenhagen Business School, Frederiksberg, Denmark

    Torkil Clemmensen

  4. Madeira Interactive Technologies Institute, Funchal, Portugal

    Pedro Campos

  5. Madeira Interactive Technologies Institute, Funchal, Portugal

    Arminda Lopes

  6. Madeira Interactive Technologies Institute, Funchal, Portugal

    Frederica Gonçalves

  7. University of West London, London, UK

    José Abdelnour-Nocera

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Seymoens, T., Ongenae, F., Jacobs, A., Verstichel, S., Ackaert, A. (2019). A Methodology to Involve Domain Experts and Machine Learning Techniques in the Design of Human-Centered Algorithms. In: Barricelli, B., et al. Human Work Interaction Design. Designing Engaging Automation. HWID 2018. IFIP Advances in Information and Communication Technology, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-030-05297-3_14

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  • DOI: https://doi.org/10.1007/978-3-030-05297-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05296-6

  • Online ISBN: 978-3-030-05297-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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