判断机器人的能力:人们如何对机器人的能力形成隐含和明确的印象
Nicholas Surdel1, Yochanan E Bigman2, Xi Shen3
1Yale University, Department of Psychology.
Journal of experimental psychology. General
|April 22, 2024
概括
人民的人民的人民.
科学领域:
- 人与机器人的互动
- 社会的认知社会认知.
- 人工智能的心理学 人工智能的心理学
背景情况:
- 越来越多的机器人存在需要了解人类对机器人能力的看法.
- 有效的人机协作取决于准确的能力评估.
研究的目的:
- 调查机器人学习经验如何塑造明确和隐含的能力印象.
- 识别隐式和显式能力判断之间的分离.
主要方法:
- 六项研究涉及2660名参与者与机器人玩竞争游戏.
- 在互动后测量明确和隐含的能力印象.
- 对出乎意料的机器人行为和印象更新的敏感性分析.
主要成果:
- 显式印象对罕见的,不寻常的机器人行为敏感,而隐式印象需要适度的流行.
- 显式印象在初始强烈印象后的更新中显示出积极性偏差,与隐式印象不同.
- 在隐式与显式层面上对机器人能力信息进行明确的处理.
结论:
- 人类与机器人的学习经验产生了不同的隐式和显式能力印象.
- 这些发现为人类与机器人的互动和对机器人的心理学提供了社会认知理论.
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