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Mindless Attractor: A False-Positive Resistant Intervention for Drawing Attention Using Auditory Perturbation

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Hiromu YakuraAuthors Info & Claims

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Article No.: 99, Pages 1 - 15

https://doi.org/10.1145/3411764.3445339

Published: 07 May 2021 Publication History

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Abstract

Explicitly alerting users is not always an optimal intervention, especially when they are not motivated to obey. For example, in video-based learning, learners who are distracted from the video would not follow an alert asking them to pay attention. Inspired by the concept of Mindless Computing, we propose a novel intervention approach, Mindless Attractor, that leverages the nature of human speech communication to help learners refocus their attention without relying on their motivation. Specifically, it perturbs the voice in the video to direct their attention without consuming their conscious awareness. Our experiments not only confirmed the validity of the proposed approach but also emphasized its advantages in combination with a machine learning-based sensing module. Namely, it would not frustrate users even though the intervention is activated by false-positive detection of their attentive state. Our intervention approach can be a reliable way to induce behavioral change in human–AI symbiosis.

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Mindless Attractor: A False-Positive Resistant Intervention for Drawing Attention Using Auditory Perturbation

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cover image ACM Conferences

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

May 2021

10862 pages

ISBN:9781450380966

DOI:10.1145/3411764

General Chairs:
Yoshifumi Kitamura
Tohoku University, Japan
,
Aaron Quigley
University of New South Wales, Australia
,
Program Chairs:
Katherine Isbister
University of California Santa Cruz, USA
,
Takeo Igarashi
The University of Tokyo, Japan
,
Publications Chairs:
Pernille Bjørn
University of Copenhagen, Denmark
,
Steven Drucker
Microsoft Research, USA

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Published: 07 May 2021

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https://dl.acm.org/doi/10.1145/3676489
Arakawa RYakura HGoel M(2024)PrISM-Observer: Intervention Agent to Help Users Perform Everyday Procedures Sensed using a SmartwatchProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676350(1-16)Online publication date: 13-Oct-2024
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