Digital Automation and AI: Trajectories and Cultures in and Outside the Workplace

Abstract

This issue of the American Behavioral Scientist brings together seven contributions that explore different facets of the two overarching themes connected to digital automation. The first section of the issue delves into the complex ways in which digital automation interacts with preexisting social and economic institutions, specifically professions, markets, and formal organizations. The second section includes contributions that explore the cultural side of digital automation in terms of time and humanness. The issue concludes with an examination of the complex entanglement of digital automation and the covid-19 pandemic as they reshape the post-automation/post-pandemic economic landscape, including labor markets, jobs, consumption, and economic growth.

As digital automation has come under increasing scrutiny from a variety of angles, new questions have emerged concerning both the trajectory of automation and the cultural consequences of automation across different societal arenas. Now understood as a process that both accommodates and reconfigures the foundational class and labor formations of late capitalist society, digital automation alters the dynamics of workplaces, professions, markets, formal organizations, and public opinion in important and unanticipated ways. At the same time, digital automation sets in motion novel cultural dynamics, reconstituting such fundamental experiential structures as humanness and temporality. These dynamics emerge from the constant interplay or “looping” between human social practices with both digitally automated physical systems—such as robots and driverless cars as well as well as nonphysical systems guided by software, electronics, and algorithms (Fourcade & Johns, 2020).

The first section of the issue Automated Futures: Work, Labor, and Technology opens with an in-depth case study by Daniel Menchik of the adoption and non-adoption of surgical robots in the field of heart surgery, a case which reveals what happens when automated Stereotaxis instruments are introduced into the work practices of relatively autonomous, highly compensated, and high-status professionals. Venturing beyond the traditional narrative of deskilling and labor-substituting technology (Frey, 2019; Shestakofsky, 2017), this case study illuminates the multiple factors which shape the stances of these high-autonomy professionals toward such automated technology. The case study demonstrates that the adoption of such technology as a work tool hinges on a range of factors connected to noneconomic considerations around human capital, professional networks of status and prestige, and other facets of the surgeons’ professional selves and communities.

In the next piece, we turn to a very different occupation, namely truck driving, a common job in the United States that has undergone a profound transformation due to deregulation, industry consolidation, and demographic change. A relatively high-paying job prior to the deregulation era, trucking is comparatively poorly paid and one of the occupations most exposed to labor-displacing automation. As a result, forecasts project that several hundred thousand truck drivers in the United States may be forced to seek alternative employment. In order to ascertain how these workers can transition out of this industry, Jenna van Fossen, Sheila Cotten and members of their research team enlist the occupational classification schemes created by the US government. On the basis of a statistical analysis of the government O*NET database alongside data from surveys of truck drivers, they identify what they term “transition occupations” which might serve as viable alternatives for displaced truck drivers. They find a strong concordance between the occupations that are objectively considered to resemble truck driving and the drivers’ stated preferences regarding potential future transition occupations.

We next turn to the impact of digitized communication on geographically dispersed collaboration networks among scientists, as studied by Tsahi Hayat, Dimitrina Dimitrova, and Barry Wellman through a case study of the GRAND network, a multidisciplinary multi-institution scientific collaboration network spanning Canada. Through a thorough and comprehensive analysis of scientific collaboration on this network, they find that, in digitally-enabled collaboration networks, multiple structural dimensions of the networks exert an impact on research output, productivity, and creativity. This study demonstrates that the widespread application of digital collaboration tools in digitally-enabled communication networks does not fundamentally alter the dynamics of scientific and intellectual production, which still hinge on underlying social structural facets of human relations.

This section concludes with an examination of the ways that public opinion responds to a particularly consequential form of digitally-enabled automation, namely the diffusion of driverless vehicles on the roads. Drawing on US-based survey data, the authors Gustavo Mesch and Matías Dodel show that public receptiveness to this technology lines up with socioeconomic divisions and sociodemographic axes such as age and gender. At the same time, openness to driverless vehicles aligns with “cultural” cleavages such as skepticism toward novel technologies, general political orientations, and individuals’ perception of the personal “usefulness” of the technology. The analysis suggests that distrust of driverless vehicles is more prominent among the very people who could most benefit from it, such as the elderly. On the other hand, it also points to the fluidity of public opinion regarding novel technologies such as automated vehicles—public opinion will continue to evolve as this form of automation becomes diffused.

The following section of Automated Futures: Work, Labor, and Technology takes up the themes of temporality and humanness. This study, authored by Ingrid Erickson and Judy Wajcman, specifically the ways in which automated digital calendaring and scheduling reconfigure the everyday temporal affordances of individuals inside and outside the realms of work and private life. The analysis, based on fieldwork carried out in Silicon Valley, ventures beyond the conceptualization of calendaring the scheduling as another kind of technological affordance (Davis, 2020) which promotes rationalization. Instead, the exploration characterizes calendaring as an economistic form of “auditing” in which temporal resources are assessed to maximize returns and minimize liabilities.

The issue continues with a reconsideration of the foundational question of “humanness” as it arises when AI-driven interactive systems and human practitioners both perform what the author, Allison Pugh, calls “connective labor” in person-to-person occupations such as therapy, teaching, and medicine. Drawing on a large set of in-depth interviews, Pugh shows that human practitioners in these fields felt compelled not only perform the tasks central to their professional duties, but also to distinguish themselves from automated systems in the eyes of their clients, students, and patients. Their interactive demonstrations of humanness took many different forms, depending on the clients, the field, and various characteristics of the practitioner. In many cases, the practitioners affirmed this humanness by attempting to form a distinctively human emotional connection with these clients, students, and patients felt to lie outside the reach of automated systems.

The concluding article in this issue, by Jeremy Schulz, deals with the entanglements of digitally enabled automation with the covid-19 pandemic. Examining shifts in work, occupations, labor markets, and consumption, the article sketches the contours of this confluence across developed economies. The article contends that, while long-term automation tends to disrupt jobs and occupations which involve what is dubbed screen-facing work and, to a lesser extent, object-facing work, person-facing work is most exposed to the reallocation shocks precipitated by the covid crisis. Where consumption is concerned, both automation and pandemic-driven shocks can precipitate mutually reinforcing shifts and act as socioeconomic stressors leading to greater divergence between the winners and the losers in the new economy.

In a world of pervasive computing and digital automation, it has become ever more urgent to grasp the complex feedback loops connecting digital automation—whether instantiated in physical machinery like robotics or intelligent software platforms—to social and economic institutions such as markets, occupations, social networks, and formal organizations. With respect to this theme, that the dynamics governing such institutions—whether capitalist consolidation, job polarization (Kalleberg, 2011), social status and prestige competition in professional fields, or technoskepticism in public opinion—combine with ongoing digital automation in complex ways. In some cases, preexisting economic institutions and social formations channel digitally-enabled automation processes in predictable ways, while in other cases they disrupt this process, slowing or complicating the march to a more fully automated economy. At the same time, the increasing reach and complexity of automated sociotechnical systems into human life inevitably alter foundational human practices such as management of time and perceptions of humanness both within and outside the workplace. In this sense, automation further expands the role of the powerful abstract systems that sustain depersonalized modernity.