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Technology, Work, and Inequality

Volume 4, Issue 1. Special Collection: Technology, Work, and Inequality (Introduction). DOI: 10.1037/tmb0000103

Published onFeb 08, 2023
Technology, Work, and Inequality

Disclosures: The authors declare that there is no conflict of interest.

Correspondence concerning this Collection should be addressed to Tara S. Behrend, Department of Psychological Sciences, Purdue University, 700 Third Street, West Lafayette, IN 47907, United States. [email protected]

Economic inequality is rising. For the first time in a century, children in the United States will not, on average, do better than their parents (Chetty et al., 2017). Technological changes have been identified as both exacerbating inequality and presenting potential solutions (Acemoglu & Restrepo, 2019; Autor & Dorn, 2013; Frey & Osborne, 2013; Johnson et al., 2020; Lee et al., 2019; Meda, 2019; White et al., 2020; World Economic Forum, 2018). Whether or how technology has these effects may be in large part tied to how technology is developed and deployed in the world of work.

First, technology both creates and limits access to work. Given that work is the main mechanism through which society allocates economic and social resources, unequal access to work and good jobs exacerbates inequality (Lai & Widmar, 2021; Van Fossen et al., 2022).

Second, technology plays a role in inequalities at work. Remote work is facilitated by technologies such as video conferencing and collaboration tools, which increase access to work for many people. These tools, though, can also have direct negative effects. For example, teams comprised of both in-person and remote workers marginalize the remote members, who may be remote due to family care or other needs (Mortensen & Haas, 2021). Technology-based electronic monitoring threatens to further disadvantage vulnerable worker populations (Ravid et al., 2020, 2022). Technologies are used to identify characteristics of workers that they would rather keep private, either intentionally or incidentally through big data analyses (Landers & Behrend, 2022; Oswald et al., 2020).

Third, inequality within the workplace shapes technologies themselves. Decisions about what tools workers may need, or how they will be used, or what negative effects they may have, are made by the “people at the table.” When decisions are made by nonrepresentative groups, the needs of marginalized workers are not considered. This may be reflected in choices about design, marketing, or research, or in how data sets are built. A frequently cited example concerns a facial recognition tool that only functions on White faces, due to a lack of diversity in the algorithm’s development data set, and lack of people of color involved in design and testing (Garvie & Frankle, 2016).

Given the huge growth in technological capabilities and changes in the institution of work (Azhar, 2021), there is an urgent need to understand how technology can contribute to or alleviate inequality in the context of work and employment. This special collection addresses this need by approaching the intersection of work, technology, and inequality from a psychological perspective. As Harley and Fleming (2021, p. 133) describe, although “social scientists have long been concerned with using their research to make the world a better place,” the incentive structures of the disciplines often leave “big picture” topics ignored or underexamined. Special collections provide (a) a call to action for researchers, (b) generate a body of work that together can stimulate new areas of research, and (c) produce implications for policy and practice. We saw Technology, Mind, and Behavior as an ideal outlet for such a special collection given its psychological lens, its reach across subdisciplines of psychology, and the willingness of the publication team (especially Editor-in-Chief Danielle McNamara) to make this special collection open-access with no charge to the authors. Paywalls or author charges for publication creates inequality in access to knowledge based on personal or institutional financial resources or values. Technology, Mind, and Behavior is an open-access journal, and making this special collection open-access with no cost to the authors reflects one (small) way we can use technology to help make scientific insights available for a broader audience and try to overcome inequality in whose voices are reflected in published research (Nelson, 2022).

In the below sections, we summarize the research reported in our special collection and provide a framework that we hope will serve as a further call for research on this increasingly pressing topic. It is important to note that we conceptualize the constructs of technology, inequality, and work quite broadly to be inclusive to a wide variety of issues that fall under these umbrellas. Inequality could be reflected in access to high-quality work, access to the benefits of work, or through the lens of work organization and reorganization. Although most of the papers in our special collection focused on paid employment, work could be conceptualized as either traditional employment or alternative forms of work, both paid and unpaid. Technology, which we define as any product of human innovation, is also an amalgamation and includes tools such as robots, Artificial Intelligence, and information systems such as email and smartphone apps. This is an expansive definition that runs the risk of being too large to grapple with. We generally adopt the technology-as-design paradigm (Landers & Marin, 2021) that focuses less on the technical specifications of technologies but on their social and psychological effects, which stem from a series of design and implementation decisions made by human decision-makers and reflecting a set of cultural assumptions. As such, emerging technologies that alter the work environment or the experience of work become most relevant for study.

This Special Collection

Discussions about technology, work, and inequality have historically been the focus of the macrolevel disciplines. For example, the economics literature has long been interested in the implications of automation and technological development for labor market outcomes, including whether work itself will continue to exist (Frey & Osborne, 2013). The macrolevel focus is understandable given that work is a macrolevel institution, and inequality and technology are inherently macrolevel concepts. Yet, as many have argued, macrolevel economic and societal phenomenon have at their roots actions by individuals and organizations (MacLachlan, 2014; Shoss & Foster, 2022).

In this sense, most commentators argue that technology’s impacts will be shaped by not only by the nature of the technology itself, but also how it is developed and incorporated into work (National Academies of Sciences, Engineering, and Medicine, 2017). In our opinion, this highlights the need for a psychological perspective. Psychological research focuses on the lived experiences of workers, how they adjust or do not adjust to technology, and how technology can be designed and deployed to enhance or reduce existing inequalities based on issues such as representation and organizational power. Moreover, psychological research examines how existing inequalities can manifest in the design of technology through constructs such as voice and representation; practices of employee recruitment, selection, and retention; and the design of data sets from which technological tools are developed (Landers & Behrend, 2022; Van Fossen et al., 2022).

The research papers in our special collection take up the charge to consider the intersection of technology, work, and inequality from a psychological perspective. Together, they highlight three main themes. First, the technologies that people are exposed to at work differs across groups. In other words, the technologies themselves are unequal in how they are deployed across different jobs. Second, inequality is “sticky” in the sense that existing inequality in worker pools is not necessarily easily addressed by new technological solutions and that existing inequality in work-related technological capabilities can have long-arm effects for workers in aspects of life beyond the workplace. Third, inequality serves as a contextual factor that may shape how people develop perceptions about workplace technologies. These findings offer several implications for policy and practice, which we encouraged authors to elaborate on in their papers.

Theme 1: People’s Unequal Experiences of Technologies at Work

In a sample of Swiss workers across industries, Toscanelli et al. (2022) found three profiles characterized participants’ experience with technology at work: “Tech-Enthusiasts” experienced technology as easy to use, useful, and not autonomy reducing; “Tech-Ambivalents” experienced technology as easy to use and useful, but indicated that the technology reduced their autonomy; and “Tech-Detractors” experienced technology as neither useful or easy and experienced autonomy reductions. They found that individual differences, including age, gender, and education, were related to membership in each cluster, suggesting that the nature of technologies people are exposed to at work may be a mechanism further accentuating inequalities in working conditions across demographic groups.

Echoing the idea that workplace technologies may be differentially implemented across worker groups, Pitcher et al. (2022) examined differences in the use of electronic performance monitoring across worker populations. They provide helpful data on a wide range of forms of electronic performance monitoring and the perceived acceptability by workers of each form. Although they did not find that socioeconomic status or job status related to greater exposures to technologies that workers deem as unacceptable, job tenure did play a role. This study speaks to potential power dynamics in the workplace and offers theory and data that will be useful for future research examining inequality in electronic performance monitoring.

Theme 2: Inequality is “Sticky”

Burch et al. (2022) identify a long-arm impact of workplace inequalities on mobile phone usage in a sample of older adults, suggesting that work can contribute to the digital divide. Their mixed method approach revealed that those with greater incomes at retirement and those whose occupations could be categorized as a professional occupation were more proficient at mobile phone usage. Their study helps to better understand the “digital divide” and the central role that work experiences have in enabling people to access and utilize technologies later in life.

What about using technology to fix existing inequalities? Auer et al. examine the applicant pool of a large U.S. based manufacturing plant (N = 24,963) over 8 years using interrupted time series modeling of complex data and taking advantage of a quasi-experimental design. They found that a shift to unproctored internet testing increased the overall size of the applicant pool, as might be anticipated given unproctored internet testing provides greater access to applicants who might otherwise face barriers (e.g., transportation, time off from work) to applying for jobs or participating in proctored testing. Contrary to popular thinking, however, it did not significantly impact pool diversity. Based on these findings, the authors conclude that technology changes alone are insufficient to meaningfully enhance diversity in organizations.

Theme 3: Inequality as Context

Finally, Shoss and Ciarlante (2022) focused on inequality as context. They argued that societal inequality heightens concerns about potential workplace disruption. Using the Eurobarometer data set, they find that people living in countries with greater income inequality tend to hold more negative views of emerging technologies (AI/robots), anticipating that these technologies will serve to take away jobs. Their study points to inequality as an important context for how workers, in aggregate, may react to technological change.

Theme 4: Policy Implications

Given the importance of these issues, the charge for researchers is not only to understand the nature and consequences of the interplay between technology, work, and inequality, but also to identify research-based implications for organizational practice and government policy. The papers in our special collection suggested policies and practices for organizations, communities, and governments.

Wickert et al. (2020, p. 2) describe impactful research as research that shapes the thinking, behaviors, and practices of individuals, organizations, and/or social systems. Consistent with the goals of policy-relevant impactful research (Wickert et al., 2020), the special collection articles provide insights that (a) educate and caution practitioners and policymakers (Auer et al., 2022; Pitcher et al., 2022; Shoss & Ciarlante, 2022), (b) provide recommendations for expenditure-based instruments (Burch et al., 2022; Toscanelli et al., 2022), and (c) suggest goals for regulation (Pitcher et al., 2022). Table 1 highlights policy-relevant excerpts from each article.

Table 1
Policy Implications From Special Collection on Technology, Work, and Inequality


Selected policy/practice insights

Are robots/AI viewed as more of a workforce threat in unequal societies? Evidence from the eurobarometer survey
Shoss and Ciarlante (2022)

“Workplaces considering implementing advanced technologies, and policymakers should account for the broader context of inequality when anticipating how people may react to these technologies.”

“To the extent to which people’s views about technology limit the successful introduction of advanced technologies, one might wonder whether, or if, this countervailing force could serve to temper the growth of inequality-producing technologies.”

Antecedents and consequences of technology appraisal: A person-centered approach
Toscanelli et al. (2022)

“Organizations should provide the necessary resources (awareness-raising measures, continuous training, gender, and age-equitable management) to help employees overcome disadvantages and develop the necessary skills to cope with technological demands.”

Socioeconomic and job status differences in the experience of perceived unacceptable electronic performance monitoring
Pitcher et al. (2022)

“It is advised that organizations be cautious and thoughtful when implementing EPM. This forethought should include a consideration of how monitoring workers will affect workers psychologically, especially their sense of autonomy, privacy, and transparency.”

“Additionally, it is imperative for policymakers to develop legal protections from oppressive EPM practices when employers fail to do so. These policies should specify the forms of EPM and general data practices that violate workers’ rights based on empirical data regarding when and for whom EPM is violative, and they should introduce legal safeguards against these practices.”

Work and personal determinants of mobile-technology adoption and use among community-dwelling older adults: a mixed-methods approach
Burch et al. (2022)

“Policies aimed at providing senior centers (a community resource for community-dwelling older adults) the resources necessary to implement local technology training programs may be beneficial in starting to bridge the divide for community-dwelling older adults.”

“Furthermore, technology companies can do more to assist in bridging the digital divide for older adults. Mobile technology not only changes on a daily basis, but many mobile interfaces are challenging for older adults to see and manipulate.”

The effects of unproctored internet testing on applicant pool size and diversity: Using interrupted time series to improve causal inference
Auer et al. (2022)

“Practitioners looking to increase the size of their applicant pools should implement UITs only after careful considerations of the risks involved (e.g., cheating on cognitively loaded tests, score differences among proctored and unproctored tests).”

Note. AI = Artificial Intelligence; EPM = electronic performance monitoring.

The Future Study of Work, Technology, and Inequality

In editing this special collection, we saw author teams grapple with several challenges of doing psychological research related to the intersection of work, technology, and inequality. First, it is often difficult to distill large societal challenges into smaller research questions, as many have noted (e.g., Harley & Fleming, 2021). Second, there can appear to be a disconnect between the individual-level focus of psychology, which emphases variability between people, and the aggregate constructs of inequality and technology. As described above, most papers in the special collection sought to addresses these first two challenges by examining how technology, work, and inequality manifest in individual experiences as well as in different work environments. Finally, establishing causality/directionality in this research is challenging. As we argue below, technology, work, and inequality are inherently interconnected and shape each other in reciprocal ways over time. Thus, “what” causes “what” depends on the timeframe and context of what one is studying.

When resources are distributed unjustly, we have a responsibility to identify those injustices and seek to understand both causes and solutions. Thus, there is a need for more research-based solutions to guide the evolution of technology and work overtime in ways that reduce rather than exacerbate inequality. With the aims of encouraging systems thinking and stimulating a vibrant agenda of research in this area, we offer here a perspective on how work, technology, and inequality interface with each other over time, and the factors that shape the nature of this interface.

Our general perspective on this issue is that inequality exists at and emerges from the intersections of work, technology, and society. This dynamic viewpoint makes several observations possible and echoes many of the themes from our special collection papers. First, inequality at work is shaped by inequality in society and, in turn, reinforces and entrenches further inequality through the development of technology. For example, there are countless examples of the health and work inequalities faced by women from technology designed primarily by men based on data from mostly males. Inequality is inherently social and communal—therefore, it arises from the interaction between societal/communal factors and the manifestation of these factors in technology and work.

Second, technology has the potential to reduce inequality though shaping job dynamics, for example, those related to vertical inequality, worker autonomy and control, and power. But, whether and how this will happen is connected to context—what are current policies and practices around who has access to technology? To what extent is technology being employed as a control mechanism in a struggle between labor and management? Which workers are involved in decisions surrounding the use of technology? How does society or organizations regulate/audit technology (e.g., Landers & Behrend, 2022) and distribute its returns (e.g., Mazzucato, 2018)?

Third, the arrows of causality can go many different ways. Technology can change both society and work. Consider how the calendar structures our thinking about time (Cohen, 2018), and, more recently, the pervasive and profound impact of social media algorithms. Just as importantly, society can and does change technology. Consider data privacy policies, policies for interoperability, policies for electric vehicles being implemented in the EU. Organizations can change both technology and society by ensuring more equal access, equal voice, and equal distribution of rewards to technology across groups and individuals. As Acemoglu (2002, p. 13) writes, technology “is an outcome of the decisions made by firms and workers, in the same way as the level of employment or wages are. In other words, technology is “endogenous.” This brings us to the issue of technological unemployment—the loss of work due to automation (Postel-Vinay, 2002). Unemployment is not inherent to technology itself, rather, it is the outcome of public and organizational policies around where to invest and what to restrict.

This perspective is meant to be illustrative and thought-provoking and is not necessarily an exhaustive characterization of the interplay among inequality, technology, work, and society. We encourage research that considers reciprocal influences among the elements described here, as well as research that identifies high-impact leverage points to shift these dynamics toward reducing—rather than increasing—inequality. Research will inherently need to be multilevel, encompassing dynamic actions and reactions by individuals, organizations, communities, and cultures.


Our goal with this special collection was to (a) highlight multidisciplinary and diverse approaches to understanding and addressing technology, inequality, and work; (b) explore new forms of work made possible by technology and their implications for inequality; and (c) generate policy-relevant insights. Though technologies evolve rapidly, a solid foundation of understanding built on psychological theory and evidence is possible. It is essential to continue to build this foundation to ensure that future technologies are designed and deployed with human beings of all means and backgrounds in mind.

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