TY - JOUR
T1 - How Much Wearable Data is Enough for the Utility and Trust of Augmented Artificial Intelligence Systems? A Scenario-Based Interview with Medical Professionals
AU - Abdelaal, Yasmin
AU - Aupetit, Michaël
AU - Baggag, Abdelkader
AU - Bashir, Mohammed
AU - Al-Thani, Dena
N1 - Publisher Copyright:
© 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
PY - 2025/6/18
Y1 - 2025/6/18
N2 - The paper explores the synergy between wearable data and augmented Artificial Intelligence (AI) through findings from two interconnected studies. The first study (study 1) focuses on medical professionals’ perceptions of wearable data and AI, and the second study (Study 2) extends it focuses on how differences in the level of granularity in the data presented affect the professionals’ understanding, interpretation, and trust in AI recommendations. This system allows medical professionals to view AI-generated recommendations for sleep and activity improvement and explanations of the underlying rationale. While each study has distinct research questions, Study 2 builds upon Study 1's foundation. Both studies employed scenario-based interviews. Thematic analysis of Study 1 identified trust as a crucial factor in the acceptance of wearable data and AI, influencing Study 2's exploration of factors affecting trust, such as explainability, data granularity, representativeness, and user interaction. Study 2 highlighted varying perspectives on information sufficiency and data sharing from the AI system linked to professionals’ roles and tasks. The work offers insights into data granularity’s impact on engagement with AI recommendations.
AB - The paper explores the synergy between wearable data and augmented Artificial Intelligence (AI) through findings from two interconnected studies. The first study (study 1) focuses on medical professionals’ perceptions of wearable data and AI, and the second study (Study 2) extends it focuses on how differences in the level of granularity in the data presented affect the professionals’ understanding, interpretation, and trust in AI recommendations. This system allows medical professionals to view AI-generated recommendations for sleep and activity improvement and explanations of the underlying rationale. While each study has distinct research questions, Study 2 builds upon Study 1's foundation. Both studies employed scenario-based interviews. Thematic analysis of Study 1 identified trust as a crucial factor in the acceptance of wearable data and AI, influencing Study 2's exploration of factors affecting trust, such as explainability, data granularity, representativeness, and user interaction. Study 2 highlighted varying perspectives on information sufficiency and data sharing from the AI system linked to professionals’ roles and tasks. The work offers insights into data granularity’s impact on engagement with AI recommendations.
KW - Artificial intelligence
KW - Augmented artificial intelligence
KW - Explainability
KW - Information sufficiency
KW - Medical professionals
KW - Wearable data
KW - Wearables
UR - https://www.scopus.com/pages/publications/85204739432
U2 - 10.1080/10447318.2024.2400388
DO - 10.1080/10447318.2024.2400388
M3 - Article
AN - SCOPUS:85204739432
SN - 1044-7318
VL - 41
SP - 7684
EP - 7710
JO - International Journal of Human-Computer Interaction
JF - International Journal of Human-Computer Interaction
IS - 12
ER -