你说什么与你做什么在人类-人工智能团队中利用积极的情感表达传递人工智能队友的意图

IF 5.3 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Rohit Mallick , Christopher Flathmann , Wen Duan , Beau G. Schelble , Nathan J. McNeese
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引用次数: 0

摘要

近年来,随着人工智能能力的迅猛发展,研究人员肩负着开发和改进以人为中心的人工智能协作的重任,因此有必要建立人类-人工智能团队(HAT)。然而,人类与人工智能在沟通方式上的差异往往使人类队友无法完全理解人工智能队友的意图和需求。其中一个核心差异是,人类在沟通过程中会自然而然地利用积极的情感基调来表达自己的信心,或者通过缺乏信心来表达对自己完成任务能力的怀疑。然而,这种沟通策略必须经过明确设计,才能让人工智能队友做到以人为本。在这项混合方法研究中,45 名参与者完成了一项研究,考察人类队友如何解读人工智能队友通过特定词语/短语表达不同积极情绪时的行为。定量研究结果表明,根据相应的行为,人工智能队友能够利用情绪展示来增加对人工智能队友的信任和人类队友的积极情绪。此外,我们的定性研究结果表明,参与者更喜欢他们的人工智能队友提高情绪表现的强度,以帮助降低人工智能队友行为的感知风险。综上所述,这些研究结果表明,人工智能队友在执行各种行为决策时表达情绪强度是一种持续的手段,可为更广泛的团队提供社会支持,并提高任务绩效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
What you say vs what you do: Utilizing positive emotional expressions to relay AI teammate intent within human–AI teams

With the expansive growth of AI’s capabilities in recent years, researchers have been tasked with developing and improving human-centered AI collaborations, necessitating the creation of human–AI teams (HATs). However, the differences in communication styles between humans and AI often prevent human teammates from fully understanding the intent and needs of AI teammates. One core difference is that humans naturally leverage a positive emotional tone during communication to convey their confidence or lack thereof to convey doubt in their ability to complete a task. Yet, this communication strategy must be explicitly designed in order for an AI teammate to be human-centered. In this mixed-methods study, 45 participants completed a study examining how human teammates interpret the behaviors of their AI teammates when they express different positive emotions via specific words/phrases. Quantitative results show that, based on corresponding behaviors, AI teammates were able to use displays of emotion to increase trust in AI teammates and the positive mood of the human teammate. Additionally, our qualitative findings indicate that participants preferred their AI teammates to increase the intensity of their displayed emotions to help reduce the perceived risk of their AI teammate’s behavior. When taken in sum, these findings describe the relevance of AI teammates expressing intensities of emotion while performing various behavioral decisions as a continued means to provide social support to the wider team and better task performance.

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来源期刊
International Journal of Human-Computer Studies
International Journal of Human-Computer Studies 工程技术-计算机:控制论
CiteScore
11.50
自引率
5.60%
发文量
108
审稿时长
3 months
期刊介绍: The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities. Research areas relevant to the journal include, but are not limited to: • Innovative interaction techniques • Multimodal interaction • Speech interaction • Graphic interaction • Natural language interaction • Interaction in mobile and embedded systems • Interface design and evaluation methodologies • Design and evaluation of innovative interactive systems • User interface prototyping and management systems • Ubiquitous computing • Wearable computers • Pervasive computing • Affective computing • Empirical studies of user behaviour • Empirical studies of programming and software engineering • Computer supported cooperative work • Computer mediated communication • Virtual reality • Mixed and augmented Reality • Intelligent user interfaces • Presence ...
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