The AI of the Beholder: Experience of Healthcare AI Robots is Shaped by User-Centred Factors, Not Their Visual Appearance

Jinha Yoon; Patrycja Zajac; Lauren Pococke; Anisia Jicol; Christopher Clarke; Eamonn O'Neill; Karin Petrini; Christof Lutteroth; Crescent Jicol

doi:10.1109/TVCG.2025.3616748

The AI of the Beholder: Experience of Healthcare AI Robots is Shaped by User-Centred Factors, Not Their Visual Appearance

Jinha Yoon, Patrycja Zajac, Lauren Pococke, Anisia Jicol, Christopher Clarke, Eamonn O'Neill, Karin Petrini, Christof Lutteroth, Crescent Jicol

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Abstract

Healthcare artificial intelligence (HAI) robots could alleviate the current healthcare provision crisis. However, their successful deployment rests on achieving and responsibly calibrating appropriate patient trust in them. Over two user studies, we systematically investigate trust formation in and usage intentions for HAI robots. We first investigate manipulations of visual appearance in a passive observation study without healthcare-specific situational context (n=87) and then in a realistic VR scenario depicting a medical consultation with a HAI robot (n=177) that introduces such situational context (diagnosis and treatment severity). Results show that within a healthcare context, a unique combination of (i) situational (diagnosis and treatment severity), (ii) robot (perceived competence) and (iii) user characteristics (personality and attitudes) determine trust and ultimately influence usage intentions for HAI robots. Furthermore, our results emphasize the absence of HAI visual appearance effects on trust. Our findings support and inform a human centred design approach of HAI robots.

Original language	English
Pages (from-to)	9910-9920
Number of pages	11
Journal	IEEE Transactions on Visualization and Computer Graphics
Volume	31
Issue number	11
Early online date	17 Oct 2025
DOIs	https://doi.org/10.1109/TVCG.2025.3616748
Publication status	Published - 17 Oct 2025

Keywords

Artificial Intelligence (AI)
Human Computer Interaction (HCI)
Virtual Reality (VR)
anthropomorphism
diagnosis
healthcare
trust

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Computer Graphics and Computer-Aided Design

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TVCG.2025.3616748

ISMAR_AI_Healthcare_2025 (1)Accepted author manuscript, 7.41 MBLicence: CC BY

Cite this

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title = "The AI of the Beholder: Experience of Healthcare AI Robots is Shaped by User-Centred Factors, Not Their Visual Appearance",

abstract = "Healthcare artificial intelligence (HAI) robots could alleviate the current healthcare provision crisis. However, their successful deployment rests on achieving and responsibly calibrating appropriate patient trust in them. Over two user studies, we systematically investigate trust formation in and usage intentions for HAI robots. We first investigate manipulations of visual appearance in a passive observation study without healthcare-specific situational context (n=87) and then in a realistic VR scenario depicting a medical consultation with a HAI robot (n=177) that introduces such situational context (diagnosis and treatment severity). Results show that within a healthcare context, a unique combination of (i) situational (diagnosis and treatment severity), (ii) robot (perceived competence) and (iii) user characteristics (personality and attitudes) determine trust and ultimately influence usage intentions for HAI robots. Furthermore, our results emphasize the absence of HAI visual appearance effects on trust. Our findings support and inform a human centred design approach of HAI robots.",

keywords = "Artificial Intelligence (AI), Human Computer Interaction (HCI), Virtual Reality (VR), anthropomorphism, diagnosis, healthcare, trust",

author = "Jinha Yoon and Patrycja Zajac and Lauren Pococke and Anisia Jicol and Christopher Clarke and Eamonn O'Neill and Karin Petrini and Christof Lutteroth and Crescent Jicol",

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doi = "10.1109/TVCG.2025.3616748",

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T2 - Experience of Healthcare AI Robots is Shaped by User-Centred Factors, Not Their Visual Appearance

AU - Yoon, Jinha

AU - Zajac, Patrycja

AU - Pococke, Lauren

AU - Jicol, Anisia

AU - Clarke, Christopher

AU - O'Neill, Eamonn

AU - Petrini, Karin

AU - Lutteroth, Christof

AU - Jicol, Crescent

PY - 2025/10/17

Y1 - 2025/10/17

N2 - Healthcare artificial intelligence (HAI) robots could alleviate the current healthcare provision crisis. However, their successful deployment rests on achieving and responsibly calibrating appropriate patient trust in them. Over two user studies, we systematically investigate trust formation in and usage intentions for HAI robots. We first investigate manipulations of visual appearance in a passive observation study without healthcare-specific situational context (n=87) and then in a realistic VR scenario depicting a medical consultation with a HAI robot (n=177) that introduces such situational context (diagnosis and treatment severity). Results show that within a healthcare context, a unique combination of (i) situational (diagnosis and treatment severity), (ii) robot (perceived competence) and (iii) user characteristics (personality and attitudes) determine trust and ultimately influence usage intentions for HAI robots. Furthermore, our results emphasize the absence of HAI visual appearance effects on trust. Our findings support and inform a human centred design approach of HAI robots.

AB - Healthcare artificial intelligence (HAI) robots could alleviate the current healthcare provision crisis. However, their successful deployment rests on achieving and responsibly calibrating appropriate patient trust in them. Over two user studies, we systematically investigate trust formation in and usage intentions for HAI robots. We first investigate manipulations of visual appearance in a passive observation study without healthcare-specific situational context (n=87) and then in a realistic VR scenario depicting a medical consultation with a HAI robot (n=177) that introduces such situational context (diagnosis and treatment severity). Results show that within a healthcare context, a unique combination of (i) situational (diagnosis and treatment severity), (ii) robot (perceived competence) and (iii) user characteristics (personality and attitudes) determine trust and ultimately influence usage intentions for HAI robots. Furthermore, our results emphasize the absence of HAI visual appearance effects on trust. Our findings support and inform a human centred design approach of HAI robots.

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KW - Human Computer Interaction (HCI)

KW - Virtual Reality (VR)

KW - anthropomorphism

KW - diagnosis

KW - healthcare

KW - trust

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JO - IEEE Transactions on Visualization and Computer Graphics

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IS - 11

ER -

The AI of the Beholder: Experience of Healthcare AI Robots is Shaped by User-Centred Factors, Not Their Visual Appearance

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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