Individuals Expend More Effort to Compete Against Robots Than Humans After Observing Competitive Human–Robot Interactions
Timmerman, Rosanne H.; Hsieh, Te Yi; Henschel, Anna; Hortensius, Ruud; Cross, Emily S.; Li, Haizhou; Ge, Shuzhi Sam; Wu, Yan; Wykowska, Agnieszka; He, Hongsheng; Liu, Xiaorui; Li, Dongyu; Perez-Osorio, Jairo
(2021)
Social Robotics, volume 13086, pp. 685 - 696
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 13086, pp. 685 - 696
13th International Conference on Social Robotics, ICSR 2021, volume 13086, pp. 685 - 696
(Part of book)
Abstract
In everyday life, we often observe and learn from interactions between other individuals—so-called third-party encounters. As robots are poised to become an increasingly familiar presence in our daily lives, third-party encounters between other people and robots might offer a valuable approach to influence people’s behaviors and attitudes towards robots. Here,
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we conducted an online experiment where participants (n = 48) watched videos of human—robot dyads interacting in a cooperative or competitive manner. Following this observation, we measured participants’ behavior and attitudes towards the human and robotic agents. First, participants played a game with the agents to measure whether their behavior was affected by their observed encounters. Second, participants’ attitudes toward the agents were measured before and after the game. We found that the third-party encounters influenced behavior during the game but not attitudes towards the observed agents. Participants showed more effort towards robots than towards humans, especially when the human and robot agents were framed as competitive in the observation phase. Our study suggests that people’s behaviors towards robots can be shaped by the mere observation of third-party encounters between robots and other people.
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Keywords: Artificial agents, Competition, Cooperation, Human—robot interaction, Social cognition, Social robotics, Third-party encounters, Theoretical Computer Science, Computer Science(all)
ISSN: 0302-9743
ISBN: 9783030905248
Publisher: Springer Science and Business Media Deutschland GmbH
Note: Funding Information: Funding. Research supported by funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement number 677270 to E.S.C.), the Leverhulme Trust (PLP-2018–152 to E.S.C), and the BIAL Foundation (to R.H.). Publisher Copyright: © 2021, Springer Nature Switzerland AG.
(Peer reviewed)