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关于劳动力机器人技术在安全、独立性、工作保障和隐私方面的工人认知数据集。

Dataset of worker perceptions of workforce robotics regarding safety, independence, job security, and privacy.

作者信息

Liu Yu Andrew, Kaur Gurpreet, Banerjee Natasha Kholgade, Banerjee Sean

机构信息

Department of Computer Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA.

Department of Computer Science and Engineering, Wright State University, 3640 Colonel Glenn Highway, Dayon, OH 45435, USA.

出版信息

Data Brief. 2025 Jun 3;61:111750. doi: 10.1016/j.dib.2025.111750. eCollection 2025 Aug.

Abstract

With an aging blue-collar workforce spanning critical sectors such as construction, transportation and delivery, manufacturing, and warehousing, there is an increased need for collaborative workforce robots. Workers in these sectors are prone to lifting related workplace injuries that lead to a reduction in job longevity. Fear and perception of robotics is influenced by a broad range of demographic and socio-economic factors. In this paper we present a dataset consisting of 337 complete responses to a 40-question survey that we administered anonymously via Google Forms to blue-collar workers in Australia, Canada, United Kingdom, and United States of America working in six different job sectors, namely manufacturing, retail, transportation & delivery, warehousing, construction, and contract work. The questions range from worker demographics (7 questions), perceptions toward physical safety in the workplace (8 questions), perceptions toward working with human coworkers in the workplace (6 questions), perceptions toward working with robots (16 questions), and perceptions toward data privacy on robots (3 questions). The dataset will enable research on understanding worker concerns with sensing systems and data privacy in workforce robots and enable data informed recommendations on privacy and security preserving sensing systems on existing and future robots. The dataset will enable researchers to understand how workers perceive of robots of varying capabilities with regards to the worker's own perceptions of safety, independence, and job security. Researchers can also use the dataset to understand how barriers to safety in the workplace influence worker perceptions and understand how the existing blue-collar workforce views collaborations with other workers and robots. The dataset can also enable researchers to understand how perceptions of robotics is influenced by demographic factors, country of work, job sector, and workplace location.

摘要

随着建筑、运输与配送、制造以及仓储等关键领域蓝领劳动力的老龄化,对协作式劳动力机器人的需求日益增加。这些领域的工人容易遭受与搬运相关的工作场所伤害,从而导致工作年限缩短。对机器人技术的恐惧和认知受到广泛的人口统计学和社会经济因素的影响。在本文中,我们展示了一个数据集,该数据集包含对一项40个问题的调查问卷的337份完整回复,我们通过谷歌表单以匿名方式向澳大利亚、加拿大、英国和美国从事六个不同工作领域(即制造、零售、运输与配送、仓储、建筑和合同工作)的蓝领工人进行了调查。问题涵盖工人人口统计学(7个问题)、对工作场所人身安全的认知(8个问题)、对在工作场所与人类同事合作的认知(6个问题)、对与机器人合作的认知(16个问题)以及对机器人数据隐私的认知(3个问题)。该数据集将有助于开展研究,以了解工人对劳动力机器人传感系统和数据隐私的担忧,并就现有和未来机器人的隐私与安全保护传感系统提出基于数据的建议。该数据集将使研究人员能够了解工人如何根据自身对安全、独立性和工作保障的认知来感知不同能力的机器人。研究人员还可以利用该数据集了解工作场所的安全障碍如何影响工人的认知,以及现有蓝领劳动力如何看待与其他工人和机器人的合作。该数据集还能使研究人员了解机器人技术的认知如何受到人口统计学因素、工作国家、工作领域和工作场所位置的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0608/12210288/a88a25f5702a/gr1.jpg

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