This blog is part of the COMPAS Coronavirus and Mobility Forum.
The debates surrounding automation and unemployment has been prominent in the past decade, owing to the rapid development of algorithms, machine learning and artificial intelligence (Autor 2015; Ford 2015; Frey 2019). Optimists such as Armtz et al (2015) and David Autor (2015), have suggested that mass unemployment will not occur as the incorporation of automation will be gradual. This will allow time for governments and societies to respond, allowing those who might be displaced to be reskilled for the new economy.
The COVID-19 pandemic has, however, accelerated the change. Automation is being incorporated to tackle the pandemic. Yet, challenges of unemployment of gig workers and more widespread layoffs caused by lockdowns is imminent. Thus, scholars need to reexamine the effects of automation on employment.
Should countries speed up automation? Or should they slow down automation to preserve jobs?
Well before the pandemic scholars debated the possibility of automation substituting jobs. In one camp, there are scholars such as Ford (2015) who suggests that automation will cause mass unemployment, destroying more jobs than it will create. In the other camp, there are scholars who are optimistic about the future of work. Although Frey and Osborne (2013) suggest that a large proportion of United States employment is at risk of being lost, they are optimistic about the possibility of governments and societies in managing the transition to a new economy. Carl Frey, in The Technology Trap (2019), argues that time is an important factor in considering the possibility of mass unemployment. While he believes that many occupations are at risk of being displaced by automation, he argues that societies have historically been slow to take up technological advancements due to workers’ resistance and the belief by companies that investment in new technologies is unjustified when labor cost to perform the same tasks remains low. There is a need for societies to experience drastic changes for automation to penetrate the economy. Thus, Frey argues that there is time for societies to transition to the new economy. However, what was not predicted by Frey, is the acceleration of automation incorporation due to the need to address challenges presented by the COVID-19 pandemic.
Drastic Events
The punctuated equilibrium theory suggests that changes in societies are impelled by drastic changes. In particular, technology has been known to advance through punctuated events. Adner and Levinthal (2002) suggest that technology often develops and become employed in various niches across societies, in accordance with needs. The COVID-19 pandemic is one such punctuated event. The pandemic has created challenges within the workplace due to the inability of people to travel across extensive areas. In addition, the slowing economy has prompted businesses to reduce their employee costs. Thus, there has been increased adoption of technology in workplaces. In particular, automation has become a solution for many businesses. For example, while major companies such as Walmart and Amazon had started patenting drone delivery systems, more companies now are considering drones to tackle their supply chain disruptions (Coulter 2019). Other companies have adopted cloud technologies, which rely on cloud automation, to support remote work. These changes have created a stronger justification for companies to invest in automation technologies and incorporate them into the workplace, rapidly accelerating the pace of change for the adoption of automation in workplaces (see Bendor-Samuel 2020).
The accelerating pace means that the time for transition, as predicted by Frey is now challenged. Governments must quickly adapt to the widespread unemployment that is likely to persist due to the incorporation of automation. Scholars must re-examine the extent to which automation has displaced the workforce during the pandemic, the pace at which companies across different industries will adopt automation, and the examination of upskilling and reskilling specific to automation skills.
Read the associated blog: COVID-19 and its Impact on Remote Work
Nilanjan Raghunath is Assistant Professor of Sociology at the Singapore University of Technology and Design; Tony Tan is a PhD Candidate in Sociology, Purdue University.
