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Explaining automated decision-making: a multinational study of the GDPR right to meaningful information

Author

Listed:
  • Jacob Dexe

    (RISE Research Institutes of Sweden
    KTH Royal Institute of Technology)

  • Ulrik Franke

    (RISE Research Institutes of Sweden
    KTH Royal Institute of Technology)

  • Kasia Söderlund

    (Lund University)

  • Niels Berkel

    (Aalborg University)

  • Rikke Hagensby Jensen

    (Aalborg University)

  • Nea Lepinkäinen

    (University of Turku)

  • Juho Vaiste

    (University of Turku)

Abstract

The General Data Protection Regulation (GDPR) establishes a right for individuals to get access to information about automated decision-making based on their personal data. However, the application of this right comes with caveats. This paper investigates how European insurance companies have navigated these obstacles. By recruiting volunteering insurance customers, requests for information about how insurance premiums are set were sent to 26 insurance companies in Denmark, Finland, The Netherlands, Poland and Sweden. Findings illustrate the practice of responding to GDPR information requests and the paper identifies possible explanations for shortcomings and omissions in the responses. The paper also adds to existing research by showing how the wordings in the different language versions of the GDPR could lead to different interpretations. Finally, the paper discusses what can reasonably be expected from explanations in consumer oriented information.

Suggested Citation

  • Jacob Dexe & Ulrik Franke & Kasia Söderlund & Niels Berkel & Rikke Hagensby Jensen & Nea Lepinkäinen & Juho Vaiste, 2022. "Explaining automated decision-making: a multinational study of the GDPR right to meaningful information," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(3), pages 669-697, July.
    • Handle: RePEc:pal:gpprii:v:47:y:2022:i:3:d:10.1057_s41288-022-00271-9
    DOI: 10.1057/s41288-022-00271-9
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    References listed on IDEAS

    as
    1. Arun Rai, 2020. "Explainable AI: from black box to glass box," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 137-141, January.
    2. Jeremy Scott, 2004. "Ethics, Governance, Trust, Transparency and Customer Relations," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 29(1), pages 45-51, January.
    3. Jacob Dexe & Ulrik Franke & Alexander Rad, 2021. "Transparency and insurance professionals: a study of Swedish insurance practice attitudes and future development," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 46(4), pages 547-572, October.
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