Sense of Agency in Human-Machine Interaction

Debora Zanatto*, Mark Chattington, Jan M Noyes

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

Although being in control is an important aspect of human-machine
interaction, little is known about the combined effect of automation and mental
workload on the sense of agency. In this study, participants were asked to reproduce the time interval between a keypress and an acoustic tone presented with different time delays (1250 to 2250ms). Automation had three levels from the human being in complete control, an intermediate condition, to the machine being fully automatic. Mental workload was manipulated with a secondary memory task with two levels. Results showed a gradual loss of sense of agency with increasing automation intervention. Mental workload was found to affect only the intermediate automation condition. Further, we found an Intentional Binding effect for delays longer than 1750ms in this intermediate condition. These findings demonstrate the existence of a residual sense of agency, which has important implications for the future design of hybrid, semi-autonomous systems.
Original languageEnglish
Title of host publicationAdvances in Neuroergonomics and Cognitive Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, 2021
EditorsHasan Ayaz, Umer Asgher, Lucas Paletta
PublisherSpringer, Cham
Pages353-360
Number of pages8
Volume259
ISBN (Electronic)9783030802851
ISBN (Print)9783030802844
DOIs
Publication statusPublished - 4 Jul 2021

Publication series

NameLecture Notes in Networks and Systems
Volume259
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Bibliographical note

Funding Information:
Acknowledgments. This material was funded and delivered in partnership between the Thales Group and the University of Bristol, and with the support of the UK Engineering and Physical Sciences Research Council Grant Award EP/R004757/1 entitled ‘Thales-Bristol Partnership in Hybrid Autonomous Systems Engineering (T-B PHASE)’.

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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