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FREE-ENERGY MODEL OF SENSE OF AGENCY FOR HUMAN-MACHINE INTERFACE DESIGN BASED ON COMPARATOR MODEL

Published online by Cambridge University Press:  19 June 2023

Kensaku Taniyama  and
Hideyoshi Yanagisawa
Kensaku Taniyama*
Affiliation:
The University of Tokyo
Hideyoshi Yanagisawa
Affiliation:
The University of Tokyo
*
Taniyama, Kensaku, The University of Tokyo, Japan, taniyama-kensaku688@g.ecc.u-tokyo.ac.jp

Abstract

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Sense of agency is the sense that one is causing an action. The increase in machine or system autonomy leads to an increase in the loss of sense of agency for the operation causing the loss of pleasure in the operation or sense of responsibility for the consequences of operations. Designing a sense of agency is necessary, especially in the context of machine autonomy. This calls for the control of the sense of agency, which requires the construction of a model to predict the sense of agency and establishing a design methodology to manipulate the factors of sense of agency. We propose the mathematical model that predicts the sense of agency in a human-machine system based on the comparator model and free-energy principle and what to design to enhance the sense of agency. Proposed model explains the effects of prediction error, prediction uncertainty, and observation uncertainty for body, machine, and environment feedback on the sense of agency. The model generally reveals the interaction effect between prediction error and prediction uncertainty and between prediction error and observation uncertainty. The model prediction can be widely applied as a design guide for enhancing sense of agency of human-machine interfaces.

Keywords

Design methodologySense of AgencyMathematical modelDesign for interfacesExperience design
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1945 - 1954
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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