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

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

doi:10.1016/j.dib.2025.111750

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

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

Authors

Yu Andrew Liu¹, Gurpreet Kaur¹, Natasha Kholgade Banerjee², Sean Banerjee²

Affiliations

¹ Department of Computer Science, Clarkson University, 8 Clarkson Avenue, Potsdam, NY 13699, USA.
² Department of Computer Science and Engineering, Wright State University, 3640 Colonel Glenn Highway, Dayon, OH 45435, USA.

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.

Keywords: Attitude towards robots; Blue-collar robotics survey; Robot acceptance; Robot privacy; Worker opinions; Workplace robotics.