真实场景中，人对机器人出错会自然产生多样社交反应。
Signal or 'Noise': Human Reactions to Robot Errors in the Wild
- 在真实咖啡机器人部署中观察人类社交信号。
- 49名参与者在群体互动中频繁表达多样化反应。
- 适合关注人机交互社会性与真实场景设计的研究者。
现实中机器人常出现错误，但人们在实验室外对错误的社交反应仍不清楚。已有研究显示社交信号在受控交互中有效，但在真实场景中，尤其面对非社交机器人、重复或连锁错误时，其有效性尚不明确。为此，我们构建了一款咖啡机器人，并进行了公开实地部署（共49人参与）。结果发现，参与者在错误及其他刺激下表现出丰富的社交信号，尤其是在群体互动中。这些信号虽丰富（参与者主动提供交互信息），但存在显著“噪声”。本文讨论了在真实人机交互中利用社交信号的经验、优势与挑战。
原文摘要 · Abstract (English)
In the real world, robots frequently make errors, yet little is known about people's social responses to errors outside of lab settings. Prior work has shown that social signals are reliable and useful for error management in constrained interactions, but it is unclear if this holds in the real world - especially with a non-social robot in repeated and group interactions with successive or propagated errors. To explore this, we built a coffee robot and conducted a public field deployment ($N = 49$). We found that participants consistently expressed varied social signals in response to errors and other stimuli, particularly during group interactions. Our findings suggest that social signals in the wild are rich (with participants volunteering information about the interaction), but "noisy." We discuss lessons, benefits, and challenges for using social signals in real-world HRI.
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