User Reception of Babylon Health’s Chatbot

Daniela Azevedo, Axel Legay, Suzanne Kieffer

2022

Abstract

Over the past decade, renewed interest in artificial intelligence systems prompted a proliferation of human-computer studies studies. These studies uncovered several factors impacting users’ appraisal and evaluation of AI systems. One key finding is that users consistently evaluated AI systems performing a given task more harshly than human experts performing the same task. This study aims to uncover another finding: by presenting a mHealth app as either AI or omitting the AI label and asking participants to perform a task, we evaluated whether users still consistently evaluate AI systems more harshly. Moreover, by picking young and well educated participants, we also open new research avenues to be further studied.

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Paper Citation


in Harvard Style

Azevedo D., Legay A. and Kieffer S. (2022). User Reception of Babylon Health’s Chatbot. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, ISBN 978-989-758-555-5, pages 134-141. DOI: 10.5220/0010803000003124


in Bibtex Style

@conference{hucapp22,
author={Daniela Azevedo and Axel Legay and Suzanne Kieffer},
title={User Reception of Babylon Health’s Chatbot},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP,},
year={2022},
pages={134-141},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010803000003124},
isbn={978-989-758-555-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP,
TI - User Reception of Babylon Health’s Chatbot
SN - 978-989-758-555-5
AU - Azevedo D.
AU - Legay A.
AU - Kieffer S.
PY - 2022
SP - 134
EP - 141
DO - 10.5220/0010803000003124