User Trust in Assisted Decision-Making Using Miniaturized Near-Infrared Spectroscopy

要旨

We investigate the use of a miniaturized Near-Infrared Spectroscopy (NIRS) device in an assisted decision-making task. We consider the real-world scenario of determining whether food contains gluten, and we investigate how end-users interact with our NIRS detection device to ultimately make this judgment. In particular, we explore the effects of different nutrition labels and representations of confidence on participants’ perception and trust. Our results show that participants tend to be conservative in their judgment and are willing to trust the device in the absence of understandable label information. We further identify strategies to increase user trust in the system. Our work contributes to the growing body of knowledge on how NIRS can be mass-appropriated for everyday sensing tasks, and how to enhance the trustworthiness of assisted decision-making systems.

著者
Weiwei Jiang
The University of Melbourne, Melbourne, Australia
Zhanna Sarsenbayeva
University of Melbourne, Melbourne, Australia
Niels van Berkel
Aalborg University, Aalborg, Denmark
Chaofan Wang
The University of Melbourne, Melbourne, VIC, Australia
Difeng Yu
The University of Melbourne, Melbourne, VIC, Australia
Jing Wei
The University of Melbourne, Melbourne, Australia
Jorge Goncalves
The University of Melbourne, Melbourne, Australia
Vassilis Kostakos
University of Melbourne, Melbourne, Victoria, Australia
DOI

10.1145/3411764.3445710

論文URL

https://doi.org/10.1145/3411764.3445710

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Human-AI, Automation, Vehicles & Drones / Trust & Explainability

[A] Paper Room 15, 2021-05-13 17:00:00~2021-05-13 19:00:00 / [B] Paper Room 15, 2021-05-14 01:00:00~2021-05-14 03:00:00 / [C] Paper Room 15, 2021-05-14 09:00:00~2021-05-14 11:00:00
Paper Room 15
12 件の発表
2021-05-13 17:00:00
2021-05-13 19:00:00
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