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Differences in Social Expectations About Robot Signals and Human Signals

机器人 社交暗示 心理学 认知心理学 阿凡达 人机交互 社交机器人 任务(项目管理) 背景(考古学) 社会心理学 社会决策 人机交互 社会关系 计算机科学 人工智能 移动机器人 工程类 机器人控制 古生物学 系统工程 生物
作者
Lorenzo Parenti,Marwen Belkaid,Agnieszka Wykowska
出处
期刊:Cognitive Science [Wiley]
卷期号:47 (12)
标识
DOI:10.1111/cogs.13393
摘要

Abstract In our daily lives, we are continually involved in decision‐making situations, many of which take place in the context of social interaction. Despite the ubiquity of such situations, there remains a gap in our understanding of how decision‐making unfolds in social contexts, and how communicative signals, such as social cues and feedback, impact the choices we make. Interestingly, there is a new social context to which humans are recently increasingly more frequently exposed—social interaction with not only other humans but also artificial agents, such as robots or avatars. Given these new technological developments, it is of great interest to address the question of whether—and in what way—social signals exhibited by non‐human agents influence decision‐making. The present study aimed to examine whether robot non‐verbal communicative behavior has an effect on human decision‐making. To this end, we implemented a two‐alternative‐choice task where participants were to guess which of two presented cups was covering a ball. This game was an adaptation of a “Shell Game.” A robot avatar acted as a game partner producing social cues and feedback. We manipulated robot's cues (pointing toward one of the cups) before the participant's decision and the robot's feedback (“thumb up” or no feedback) after the decision. We found that participants were slower (compared to other conditions) when cues were mostly invalid and the robot reacted positively to wins. We argue that this was due to the incongruence of the signals (cue vs. feedback), and thus violation of expectations. In sum, our findings show that incongruence in pre‐ and post‐decision social signals from a robot significantly influences task performance, highlighting the importance of understanding expectations toward social robots for effective human–robot interactions.

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