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タカハシ ヒデユキ
Hideyuki Takahashi
高橋 英之 所属 追手門学院大学 理工学部 情報工学科 職種 准教授 |
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| 言語種別 | 英語 |
| 発行・発表の年月 | 2023/07/28 |
| 形態種別 | 論文 |
| 査読 | 査読あり |
| 標題 | Anthropomorphism-based causal and responsibility attributions to robots |
| 執筆形態 | 共著・編著（代表編著を除く） |
| 掲載誌名 | Scientific Reports |
| 掲載区分 | 国外 |
| 出版社・発行元 | Springer Science and Business Media LLC |
| 巻・号・頁 | 13(1),pp.12234-12234 |
| 著者・共著者 | Yuji Kawai,Tomohito Miyake,Jihoon Park,Jiro Shimaya,Hideyuki Takahashi,Minoru Asada |
| 概要 | Abstract
People tend to expect mental capabilities in a robot based on anthropomorphism and often attribute the cause and responsibility for a failure in human-robot interactions to the robot. This study investigated the relationship between mind perception, a psychological scale of anthropomorphism, and attribution of the cause and responsibility in human-robot interactions. Participants played a repeated noncooperative game with a human, robot, or computer agent, where their monetary rewards depended on the outcome. They completed questionnaires on mind perception regarding the agent and whether the participant’s own or the agent’s decisions resulted in the unexpectedly small reward. We extracted two factors of Experience (capacity to sense and feel) and Agency (capacity to plan and act) from the mind perception scores. Then, correlation and structural equation modeling (SEM) approaches were used to analyze the data. The findings showed that mind perception influenced attribution processes differently for each agent type. In the human condition, decreased Agency score during the game led to greater causal attribution to the human agent, consequently also increasing the degree of responsibility attribution to the human agent. In the robot condition, the post-game Agency score decreased the degree of causal attribution to the robot, and the post-game Experience score increased the degree of responsibility to the robot. These relationships were not observed in the computer condition. The study highlights the importance of considering mind perception in designing appropriate causal and responsibility attribution in human-robot interactions and developing socially acceptable robots. |
| DOI | 10.1038/s41598-023-39435-5 |
| ISSN | /2045-2322 |
| PMID | 37507519 |
| PermalinkURL | https://www.nature.com/articles/s41598-023-39435-5.pdf |
| researchmap用URL | https://www.nature.com/articles/s41598-023-39435-5 |