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New measurement of psychological safety for humanoid

Authors:

Satoshi Shigemi,

Tatsuo AraiAuthors Info & Claims

HRI '12: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction

Pages 49 - 56

https://doi.org/10.1145/2157689.2157698

Published: 05 March 2012 Publication History

Abstract

In this article, we aim to discover the important factors for determining the psychological safety of humanoids and to develop a new psychological scale to measure the degree of safety quantitatively. To discover the factors that determine the psychological safety of humanoids from an ordinary person's perspective, we studied 919 Japanese, who observed movies of 11 humanoids and then freely described their impressions about what the safety of each humanoid was for them. Five psychologists categorized all of the obtained descriptions into several categories and then used the categories to compose a new psychological scale. Then, 2,624 different Japanese evaluated the same 11 humanoids using the new scale. Factor analysis on the obtained quantitative data revealed six factors of psychological safety: Performance, Humanness, Acceptance, Harmlessness, Toughness, and Agency. Additional analysis revealed that Performance, Acceptance, Harmlessness, and Toughness were the most important factors for determining the psychological safety of general humanoids. The usability of the new scale is discussed.

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Cited By

Wang YWang GGe WDuan JChen ZWen L(2024)Perceived Safety Assessment of Interactive Motions in Human–Soft Robot InteractionBiomimetics10.3390/biomimetics90100589:1(58)Online publication date: 21-Jan-2024
https://doi.org/10.3390/biomimetics9010058
Abe NHu YBenallegue MYamanobe NVenture GYoshida E(2024)Human Understanding and Perception of Unanticipated Robot Action in the Context of Physical InteractionACM Transactions on Human-Robot Interaction10.1145/364345813:1(1-26)Online publication date: 27-Jan-2024
https://dl.acm.org/doi/10.1145/3643458
Gu YSheng YDuan YZhang J(2024)How Do Different HMIs of Autonomous Driving Monitoring Systems Influence the Perceived Safety of Robotaxis Passengers? a Field StudyHCI International 2024 – Late Breaking Papers10.1007/978-3-031-76824-8_5(51-60)Online publication date: 11-Dec-2024
https://doi.org/10.1007/978-3-031-76824-8_5
Show More Cited By

Index Terms

New measurement of psychological safety for humanoid
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

HRI '12: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction

March 2012

518 pages

ISBN:9781450310635

DOI:10.1145/2157689

General Chairs:
Holly Yanco
University of Massachusetts Lowell, USA
,
Aaron Steinfeld
Carnegie Mellon University, USA
,
Program Chairs:
Vanessa Evers
University of Amsterdam, The Netherlands
,
Odest Chadwicke Jenkins
Brown University, USA

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 March 2012

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HRI'12

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HRI'12: International Conference on Human-Robot Interaction

March 5 - 8, 2012

Massachusetts, Boston, USA

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Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Cited By

Wang YWang GGe WDuan JChen ZWen L(2024)Perceived Safety Assessment of Interactive Motions in Human–Soft Robot InteractionBiomimetics10.3390/biomimetics90100589:1(58)Online publication date: 21-Jan-2024
https://doi.org/10.3390/biomimetics9010058
Abe NHu YBenallegue MYamanobe NVenture GYoshida E(2024)Human Understanding and Perception of Unanticipated Robot Action in the Context of Physical InteractionACM Transactions on Human-Robot Interaction10.1145/364345813:1(1-26)Online publication date: 27-Jan-2024
https://dl.acm.org/doi/10.1145/3643458
Gu YSheng YDuan YZhang J(2024)How Do Different HMIs of Autonomous Driving Monitoring Systems Influence the Perceived Safety of Robotaxis Passengers? a Field StudyHCI International 2024 – Late Breaking Papers10.1007/978-3-031-76824-8_5(51-60)Online publication date: 11-Dec-2024
https://doi.org/10.1007/978-3-031-76824-8_5
Akalin NKiselev AKristoffersson ALoutfi A(2023)A Taxonomy of Factors Influencing Perceived Safety in Human–Robot InteractionInternational Journal of Social Robotics10.1007/s12369-023-01027-815:12(1993-2004)Online publication date: 9-Jul-2023
https://doi.org/10.1007/s12369-023-01027-8
Vianello LPenco LGomes WYou YAnzalone SMaurice PThomas VIvaldi S(2021)Human-Humanoid Interaction and Cooperation: a ReviewCurrent Robotics Reports10.1007/s43154-021-00068-z2:4(441-454)Online publication date: 14-Dec-2021
https://doi.org/10.1007/s43154-021-00068-z
Kaplan ASanders THancock P(2021)Likert or Not? How Using Likert Rather Than Biposlar Ratings Reveal Individual Difference Scores Using the Godspeed ScalesInternational Journal of Social Robotics10.1007/s12369-020-00740-yOnline publication date: 25-Jan-2021
https://doi.org/10.1007/s12369-020-00740-y
Hu YBenallegue MVenture GYoshida E(2020)Interact With Me: An Exploratory Study on Interaction Factors for Active Physical Human-Robot InteractionIEEE Robotics and Automation Letters10.1109/LRA.2020.30174755:4(6764-6771)Online publication date: Oct-2020
https://doi.org/10.1109/LRA.2020.3017475
Venture GKulić D(2019)Robot Expressive MotionsACM Transactions on Human-Robot Interaction10.1145/33442868:4(1-17)Online publication date: 15-Nov-2019
https://dl.acm.org/doi/10.1145/3344286
Schulz TTorresen JHerstad J(2019)Animation Techniques in Human-Robot Interaction User StudiesACM Transactions on Human-Robot Interaction10.1145/33173258:2(1-22)Online publication date: 3-Jun-2019
https://dl.acm.org/doi/10.1145/3317325
Izui TVenture G(2019)Correlation Analysis for Predictive Models of Robot User’s Impression: A Study on Visual Medium and Mechanical NoiseInternational Journal of Social Robotics10.1007/s12369-019-00601-3Online publication date: 13-Nov-2019
https://doi.org/10.1007/s12369-019-00601-3
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