为什么自动化这个？探索机器人自动化愿望、投入时间与幸福感之间的相关性
Why Automate This? Exploring Correlations Between Desire for Robotic Automation, Invested Time and Well-Being
AI总结：
本研究利用BEHAVIOR-1K等数据集，发现活动时间并非自动化偏好的强预测因子，而幸福感和痛苦感是最强指标，并揭示了性别和收入水平的差异。
摘要：
理解人类倾向于自动化任务的动机对于开发无缝融入日常生活的机器人至关重要。因此，我们提出疑问：个体是否更倾向于根据活动消耗的时间或执行活动时的感受来自动化活动？本研究探讨了这些偏好以及它们是否在不同社会群体（特别是性别类别和收入水平）之间存在差异。利用BEHAVIOR-1K数据集、美国时间使用调查以及美国时间使用调查幸福感模块的数据，我们研究了机器人自动化愿望、花费时间以及相关感受（幸福感、意义感、悲伤感、痛苦感、压力感或疲惫感）之间的关系。我们的主要发现表明，尽管存在常见假设，但活动花费的时间并不能强烈预测自动化偏好；相反，幸福感和痛苦感是最强的指标。我们还识别出性别和经济水平的差异：女性倾向于自动化压力大的活动，而男性倾向于自动化让他们不快乐的活动；中等收入个体优先自动化不太愉快和有意义的活动，而低收入和高收入群体则没有显著相关性。我们希望我们的研究有助于推动机器人设计符合用户优先事项，使家用机器人朝着更具社会相关性的解决方案发展。所有数据和交互式工具均可在此https URL公开获取。
英文摘要：
Understanding the motivations underlying the human inclination to automate tasks is vital for developing robots that fit seamlessly into daily life. Accordingly, we ask: are individuals more inclined to automate activities based on the time they consume or the feelings experienced while performing them? This study explores these preferences and whether they vary across social groups, specifically gender category and income level. Leveraging data from the BEHAVIOR-1K dataset, the American Time-Use Survey, and the American Time-Use Survey Well-Being Module, we investigate the relationship between the desire for robot automation, time spent, and associated feelings: Happiness, Meaningfulness, Sadness, Painfulness, Stressfulness, or Tiredness. Our key findings show that, despite common assumptions, time spent on activities does not strongly predict automation preferences; instead, happiness and pain are the strongest indicators. We also identify differences by gender and economic level: Women prefer to automate stressful activities, whereas men prefer to automate those that make them unhappy; mid-income individuals prioritize automating less enjoyable and meaningful activities, while low and high-income show no significant correlations. We hope our research helps motivate the design of robots that align with user priorities, moving domestic robotics toward more socially relevant solutions. All data and an interactive tool are publicly available at https://robin-lab.cs.utexas.edu/why-automate-this/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
