Assessing the relationship between subjective trust, confidence measurements, and mouse trajectory characteristics in an online task
Abstract
Trust is essential for our interactions with others but also with artificial intelligence (AI) based systems. To understand whether a user trusts an AI, researchers need reliable measurement tools. However, currently discussed markers mostly rely on expensive and invasive sensors, like electroencephalograms, which may cause discomfort. The analysis of mouse trajectory has been suggested as a convenient tool for trust assessment. However, the relationship between trust, confidence and mouse trajectory is not yet fully understood. To provide more insights into this relationship, we asked participants (n = 146) to rate whether several tweets were offensive while an AI suggested its assessment. Our results reveal which aspects of the mouse trajectory are affected by the users subjective trust and confidence ratings; yet they indicate that these measures might not explain sufficiently the variance to be used on their own. This work examines a potential low-cost trust assessment in AI systems.
Keywords
Cite
@article{arxiv.2310.16632,
title = {Assessing the relationship between subjective trust, confidence measurements, and mouse trajectory characteristics in an online task},
author = {Martin Dechant and Susanne Poeller and Benedikt Hosp and Olga Lukashova-Sanz and Alexandra Sipatchin and Siegfried Wahl},
journal= {arXiv preprint arXiv:2310.16632},
year = {2023}
}
Comments
Submitted to CHI 2023 and rejected