让机器人在出错时说脏话，用户竟不反感还觉得有趣。
Oh F**k! How Do People Feel about Robots that Leverage Profanity?
- 通过视频实验测试机器人用脏话回应错误的效果
- 三组实验均显示说脏话与不说脏话无显著差异
- 适合探索非传统机器人性格设计的开发者
污言秽语几乎与语言同源，近百年来愈发普遍。与此同时，个人与服务类机器人常表现得过于礼貌，而过往研究显示打破常规可能带来益处。因此我们好奇：在出错场景中，机器人使用脏话是否能改善人类用户的社交感知？通过三个阶段的探索性研究——在线视频研究（学生群体，N=76）、在线视频研究（美国普通人群，N=98）以及校园空间现场原型部署（N=52），分别对比了无语音、非脏话回应和脏话回应三种条件。结果令人意外：尽管承认错误通常有益（符合以往发现），但非脏话与脏话回应之间差异不显著（与预期相反）。在美国文化背景下，多数用户似乎并不介意机器人说脏话，甚至可能觉得其更真实、可亲、幽默。这项工作揭示了一个富有潜力且略带叛逆的设计方向，挑战了传统机器人性格设定。
原文摘要 · Abstract (English)
Profanity is nearly as old as language itself, and cursing has become particularly ubiquitous within the last century. At the same time, robots in personal and service applications are often overly polite, even though past work demonstrates the potential benefits of robot norm-breaking. Thus, we became curious about robots using curse words in error scenarios as a means for improving social perceptions by human users. We investigated this idea using three phases of exploratory work: an online video-based study (N = 76) with a student pool, an online video-based study (N = 98) in the general U.S. population, and an in-person proof-of-concept deployment (N = 52) in a campus space, each of which included the following conditions: no-speech, non-expletive error response, and expletive error response. A surprising result in the outcomes for all three studies was that although verbal acknowledgment of an error was typically beneficial (as expected based on prior work), few significant differences appeared between the non-expletive and expletive error acknowledgment conditions (counter to our expectations). Within the cultural context of our work, the U.S., it seems that many users would likely not mind if robots curse, and may even find it relatable and humorous. This work signals a promising and mischievous design space that challenges typical robot character design.
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