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How Much Wearable Data is Enough for the Utility and Trust of Augmented Artificial Intelligence Systems? A Scenario-Based Interview with Medical Professionals.

Authors :
Abdelaal, Yasmin
Aupetit, Michaël
Baggag, Abdelkader
Bashir, Mohammed
Al-Thani, Dena
Source :
International Journal of Human-Computer Interaction. Sep2024, p1-27. 27p. 17 Illustrations.
Publication Year :
2024

Abstract

AbstractThe 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10447318
Database :
Academic Search Index
Journal :
International Journal of Human-Computer Interaction
Publication Type :
Academic Journal
Accession number :
179783279
Full Text :
https://doi.org/10.1080/10447318.2024.2400388