We Do Not Anthropomorphize a Robot Based Only on Its Cover: Context Matters too!

Author:

Dubois-Sage Marion1ORCID,Jacquet Baptiste12ORCID,Jamet Frank123ORCID,Baratgin Jean12ORCID

Affiliation:

1. UFR de Psychologie, Université Paris 8 (Laboratoire Cognitions Humaine et Artificielle, RNSR 200515259U), 2 Rue de la Liberté, 93526 Saint-Denis, France

2. Association P-A-R-I-S, 25 Rue Henri Barbusse, 75005 Paris, France

3. UFR d’Éducation, CY Cergy Paris Université, 33 boulevard Port, 95000 Cergy-Pontoise, France

Abstract

The increasing presence of robots in our society raises questions about how these objects are perceived by users. Individuals seem inclined to attribute human capabilities to robots, a phenomenon called anthropomorphism. Contrary to what intuition might suggest, these attributions vary according to different factors, not only robotic factors (related to the robot itself), but also situational factors (related to the interaction setting), and human factors (related to the user). The present review aims at synthesizing the results of the literature concerning the factors that influence anthropomorphism, in order to specify their impact on the perception of robots by individuals. A total of 134 experimental studies were included from 2002 to 2023. The mere appearance hypothesis and the SEEK (sociality, effectance, and elicited agent knowledge) theory are two theories attempting to explain anthropomorphism. According to the present review, which highlights the crucial role of contextual factors, the SEEK theory better explains the observations on the subject compared to the mere appearance hypothesis, although it does not explicitly explain all the factors involved (e.g., the autonomy of the robot). Moreover, the large methodological variability in the study of anthropomorphism makes the generalization of results complex. Recommendations are proposed for future studies.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference247 articles.

1. Learning by teaching with humanoid robot: A new powerful experimental tool to improve children’s learning ability;Jamet;J. Robot.,2018

2. Dubois-Sage, M., Jacquet, B., Jamet, F., and Baratgin, J. (2023, January 13–16). The mentor-child paradigm for individuals with autism spectrum disorders. Proceedings of the Workshop Social Robots Personalisation at the Crossroads between Engineering and Humanities (Concatenate) at the 18th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Stockholm, Sweden.

3. Pragmatics in the false-belief task: Let the robot ask the question!;Baratgin;Front. Psychol.,2020

4. Anthropomorphism and the social robot;Duffy;Robot. Auton. Syst.,2003

5. On seeing human: A three-factor theory of anthropomorphism;Epley;Psychol. Rev.,2007

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3