研究发现职业场景和种族暗示会影响人们对机器人肤色的选择偏好。
From Human Bias to Robot Choice: How Occupational Contexts and Racial Priming Shape Robot Selection
- 通过1038名参与者实验，测试不同职业背景下对机器人肤色与外形的偏好。
- 医疗教育场景偏爱浅肤色机器人，建筑体育场景更接受深肤色机器人。
- 暴露于特定种族人类后，人们更倾向选择符合刻板印象的机器人。
随着人工智能代理逐渐融入职场环境，关于社会偏见如何影响人机选择的问题日益突出。本研究开展了两项大规模实验（N = 1,038），考察职业情境与刻板印象激活如何影响在建筑、医疗、教育和体育领域中对人工代理的选择。参与者从具有系统性肤色差异及拟人化特征的人工智能代理中进行选择。研究发现存在显著的情境依赖模式：医疗与教育场景中对浅肤色人工代理表现出强烈偏好，而建筑与体育场景则对深肤色替代方案接受度更高。参与者种族与不同职业领域中的选择模式存在系统性关联。第二项实验表明，接触特定种族背景的人类专业人员会系统性地改变后续对机器人代理的偏好，且方向符合刻板印象。结果表明，职业偏见与基于肤色的歧视可直接从人类-人类情境转移至人类-机器人评估情境。研究揭示了机器人部署可能无意中延续现有社会不平等的机制。
原文摘要 · Abstract (English)
As artificial agents increasingly integrate into professional environments, fundamental questions have emerged about how societal biases influence human-robot selection decisions. We conducted two comprehensive experiments (N = 1,038) examining how occupational contexts and stereotype activation shape robotic agent choices across construction, healthcare, educational, and athletic domains. Participants made selections from artificial agents that varied systematically in skin tone and anthropomorphic characteristics. Our study revealed distinct context-dependent patterns. Healthcare and educational scenarios demonstrated strong favoritism toward lighter-skinned artificial agents, while construction and athletic contexts showed greater acceptance of darker-toned alternatives. Participant race was associated with systematic differences in selection patterns across professional domains. The second experiment demonstrated that exposure to human professionals from specific racial backgrounds systematically shifted later robotic agent preferences in stereotype-consistent directions. These findings show that occupational biases and color-based discrimination transfer directly from human-human to human-robot evaluation contexts. The results highlight mechanisms through which robotic deployment may unintentionally perpetuate existing social inequalities.
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