Promoting Partnerships to Explore the Impacts of Technological Change on Work and Well-being

Technology has a longstanding record of impacting work, the workplace, and the workforce. Automation, or finding new ways for tasks to be completed by machines and computers, has been a common industry practice since the 1970s [1]. Historically, the increased automation of routine tasks also increased demand for highly trained and educated people to focus on the more complex aspects of work requiring creativity, critical thinking, and problem-solving skills [2].

In recent years, however, we have seen a dramatic spike in the sophistication and capabilities of available technologies. New developments in artificial intelligence (AI), for example, have expanded the use and accessibility of ‘smart’ computers and machines. Many of us now even carry around AI-enabled computers in our pockets and purses. Cell phones equipped with speech-recognition software applications, such as Siri or Google Assistant, are everyday examples of technologies that can perform non-routine and higher-order ‘thinking’-based tasks [3].

The growing function and application of advanced technologies like AI have raised many questions about the future of employment and the practice of occupational safety and health (OSH). In response, the NIOSH Office of Research Integration dedicated the 2022 Expanding Research Partnerships Webinar Series to Promoting Partnerships to Explore the Impacts of Technological Change on Work and Well-being. The three webinars in the series examined the intersection of technology and work through the lenses of work arrangements, disparities and inequities, and OSH systems. Key takeaways from each webinar are summarized below.

Work Arrangements

The first webinar of the series was held March 9, 2022. The featured speakers provided perspectives on the impact of new technologies on work arrangements from government (Rene Pana-Cryan, NIOSH), industry (Scott DeBow, Randstad North America), and academia (Lorraine Conroy, Center for Healthy Work, University of Illinois Chicago School of Public Health). Definitions were provided for some general work arrangement categories, including: (1) standard arrangements, where a single employer is responsible for the safety and health of employees; (2) agency arrangements, or co-employment and shared responsibility for workers among two or more employers; (3) contract arrangements, which are defined as a business rather than employment relationships; and (4) gig arrangements, where employment occurs by way of digital online platforms.

There is a growing body of evidence to suggest that work arrangement type, along with other factors including the use of technology at work, can have a significant impact on individual well-being. Workers in temporary or precarious jobs may be especially vulnerable to serious injuries and fatalities. These nonstandard arrangements tend to lack flexibility; provide lower wages and fewer benefits; and offer limited protections from physical hazards, discrimination, and exploitation.

Employee engagement was noted as a key factor to protecting and promoting the safety, health, and well-being of these worker groups. Participatory action approaches are one way to increase involvement in OSH at multiple levels. Workers, community members, and representatives from local organizations can help identify important safety and health issues and recommend solutions to address them. Focusing these collaborations on technology-related challenges as well as technology-enabled solutions may be particularly useful.

Disparities and Inequities

The second webinar of the series, held June 8, 2022, focused on the impact of technology on occupational health disparities and inequities. The expert speakers provided perspectives on these topics from government (Rashaun Roberts, NIOSH), organized labor (Eric Clinton, UNITE HERE! Local 362), and clinical practice (Maria Espinola, Institute for Health Equity and Innovation). They began by clarifying the difference between health disparities and inequities. Health disparities are differences in the burden of disease, injury, violence, or opportunities to achieve optimal health experienced by populations that have been historically disadvantaged by factors such as their social or economic status, geographic location, and environment. People in racial and ethnic minority groups, for example, tend to experience higher rates of hypertension, obesity, heart disease, cancer, and other negative health conditions compared to White people [4]. Health inequities are avoidable disparities stemming from unfair and unjust systems, policies, and practices that limit access to the opportunities and resources needed to live the healthiest life possible. Racism, for example, is a cultural system that restricts power, reduces opportunities, and limits access to health resources for racial and ethnic minority groups, thereby contributing to their disproportionately higher rates of poor health.

The relationship between technology and work-related disparities and inequities is complicated. On one hand, the use of technology in the workplace may exacerbate disparities and inequities. Automation, for example, can increase concerns related to job instability and reduce opportunities for promotions. Electronic monitoring at work may result in privacy concerns, which vulnerable or historically disadvantaged workers may be hesitant to raise, and the application of certain algorithms to these data may result in discriminatory employment practices. The use of technology in certain industries, such as food service and hospitality, can also have significant negative effects for specific worker groups. For example, workers in restaurants and hotels, who are primarily women and immigrants, have experienced notable decreases in work hours and wages because of technology.

On the other hand, technology may be useful in addressing work-related disparities and inequities. The use of robots and drones, for example, can reduce worker exposures to certain risk factors on the job. This can be particularly useful in high-risk occupations, such as construction and agriculture. Data gathered by artificial intelligence may also allow companies to identify psychosocial risks and pinpoint where OSH interventions are needed at the organizational level to prevent negative health outcomes, such as stress and fatigue. In addition, mobile technologies have improved the range of services that community health workers can offer, especially to vulnerable and disadvantaged populations.

To reduce the adverse effects of technology, it is important for management to consult and engage with workers and their advocates. Workers and labor representatives should be involved in all parts of bringing new technologies into the workplace, including the selection, development, design, implementation, and evaluation of new products. The technology sector currently has low worker diversity, but a growing number of programs seek to address this by offering coding and computer classes to young minority groups and other special populations.

OSH Systems

In the third and final webinar of the series, held September 14, 2022, experts from government (NIOSH) and academia/clinical practice (Zeke McKinney, HealthPartners Institute and University of Minnesota School of Public Health) shared their thoughts on the impact technology-driven OSH systems can have on worker safety, health, and well-being. Workers, for example, have expressed high levels of concern about the implementation of direct reading and sensor technologies (DSRT) in the workplace. There is also a lack of trust in the data produced by DRSTs. Health and safety management systems, which include communication and coordination, management leadership, and worker participation, can be applied to improve the integration of DRSTs.

OSH data systems, which may utilize technology for the collection, storage, coding, and retrieval of important health and safety data, currently face many structural issues. At present, occupational health data are collected separately by employers, clinicians, researchers, and insurance companies. These systems are often managed disjointedly, leading to missed opportunities to provide complete care for workers. In addition, there are quality and completeness issues with the demographic and occupational data these systems collect. These data collection challenges, coupled with mistrust in the data collectors and the data collection processes, present major barriers to health equity and worker well-being. Technology could be leveraged to enhance collaboration between OSH, workers’ compensation systems, healthcare systems, and employers to improve the integration of existing data systems. Trust between system administrators and workers may also be enhanced by (1) demonstrating awareness of persistent inequities; (2) actively hearing employee concerns; (3) ensuring adequate access to personal protective equipment at work; (4) engaging employees at all levels in the processes of safety leadership and ownership; and (5) improving the use of technology to code industry, occupation, injury, and demographic data.

To access the full 2022 webinar recordings, please visit the Expanding Research Partnerships webpage. Continuing education credits are available for the June and September events. Please visit the CDC Training and Continuing Education Online (TCEO) website for more information on archived activities WD4531-060822 (Disparities and Inequities webinar) and WD4531-091422 (OSH Systems webinar).

Sarah A Felknor, MS, DrPH, is Associate Director for Research Integration at NIOSH.

Jessica MK Streit, MS, PhD, CHES® is Deputy Director of the Office of Research Integration at NIOSH.

Nicole T Edwards, MS, is a Program Specialist in the Office of Research Integration at NIOSH.

References

1. Spitz-Oener, A. 2006. Technical change, job tasks, and rising educational demands: Looking outside the wage structure. Journal of Labor Economics, 24(2), 235-270. https://doi.org/10.1086/499972
2. Autor, D.H., F. Levy, and R.J. Murnane. 2003. The Skill Content of Recent Technological Change: An Empirical Exploration. The Quarterly Journal of Economics 118(4): 1279-1333. https://www.nber.org/papers/w8337

3. Frank, K., and Frenette, M. 2021. Are new technologies changing the nature of work? The evidence so far. IRPP Study 81. Montreal: Institute for Research on Public Policy. https://irpp.org/wp-content/uploads/2021/01/Are-New-Technologies-Changing-the-Nature-of-Work-The-Evidence-So-Far.pdf
4. Centers for Disease Control and Prevention. 2022. What is health equity? https://www.cdc.gov/healthequity/whatis/index.html