工人觉得无聊的任务更愿交给AI，且认为这些任务无需太多人工监督。
Will AI Agents Free Us From Meaningless Work? A Human-Centered Analysis
- 基于格雷伯理论，用202人评估171项任务，验证了五项无聊感量表
- 任务无聊感越强，越希望用AI替代，且认为无需太多人工监管
- 为AI自动化提供人性化依据，适合关注人机协作的从业者
有人宣称AI代理将解放劳动者脱离枯燥工作，但很少了解劳动者如何判断哪些任务应被自动化。以往研究聚焦职业整体，忽视同一岗位内不同任务带来的意义差异。本研究基于格雷伯的‘无意义工作’理论，在202名工人对171项工作任务的评分基础上，（1）验证了一个包含五个项目的无聊感感知量表；（2）发现无聊感强烈预测了对AI代劳的意愿；（3）揭示这类任务也被认为需要较少人工监管。结果表明，被视作无意义的工作天然适合作为AI自动化的候选，契合劳动者偏好与实际可行性。
原文摘要 · Abstract (English)
Some claim that AI agents will free workers from the boring parts of their jobs, yet little is known about how workers themselves identify which tasks should be automated. Prior research focuses on occupations, overlooking that workers experience varying levels of meaning across tasks within the same role. We address this gap with a task-level analysis grounded in Graeber's theory of bullshit jobs. Using ratings from 202 workers on 171 workplace tasks, we (1) validate a five-item scale of perceived bullshitness, (2) show that perceived bullshitness strongly predicts desire for AI delegation, and (3) find that such tasks are also seen as requiring less human oversight. Together, these findings suggest that tasks perceived as bullshit are natural candidates for AI delegation, aligning worker preferences with perceived feasibility.
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