Do stakeholder needs differ? - Designing stakeholder-tailored Explainable Artificial Intelligence (XAI) interfaces

Minjung Kim, Saebyeol Kim, Jinwoo Kim, Tae Jin Song, Yuyoung Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Explainable AI (XAI) is increasingly being used in the healthcare domain. In health management, clinicians and patients are critical stakeholders, requiring tailored XAI explanations based on their unique needs. Our study investigates the differences in explanation needs between clinicians and patients and designs corresponding explanation interfaces for each group. Using a scenario-based approach, we assessed stakeholder-tailored needs, analyzed differences, and designed interfaces using theoretical frameworks. The results demonstrate diverse stakeholder motivations for seeking explanations, leading to varied requirements. The designed interfaces effectively address these requirements, as validated by the preference selection and qualitative feedback from clinicians and patients. Their suggestions provide design insights and highlight the divergent needs of these stakeholder groups. This study contributes practical and theoretical implications to XAI research, emphasizing the importance of understanding diverse stakeholder needs and incorporating relevant theoretical concepts into user-centered interface design.

Original languageEnglish
Article number103160
JournalInternational Journal of Human Computer Studies
Volume181
DOIs
StatePublished - Jan 2024

Bibliographical note

Publisher Copyright:
© 2023

Keywords

  • Digital health
  • Explanation interfaces
  • Explanation needs
  • Health management
  • Human-centered XAI
  • Medical XAI

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