Is fear of automation in the United States justified?
The rise of automation in the workplace is a source of anxiety for most Americans. According to a December 2018 Pew Research Center Survey, 82% of Americans say that by 2050, robots and computers will inevitably or most likely do much of the work currently done by humans .
The same survey found that 76% of respondents said that by 2050, inequality between the rich and the poor would increase if robots and computers perform most of the jobs currently being done by humans.
This paper argues that these anxieties are justified and prescient. I use a paper from Frey and Osborne: The future of employment: How susceptible are jobs to computerization — to demonstrate that a variety of jobs are susceptible to technological developments .
I also use a paper from Acemoglu and Restrepo: Robots and Jobs: Evidence from US Labor Markets — which shows that robots can have robust negative effects on employment and wages across commuting zones .
These two pieces of scholarship will illustrate to us that skepticism about automation among a large subset of Americans is both justified and prescient.
The Effects of Automation on Jobs
The concerns surrounding automation are simple to understand. With the help of artificial intelligence (A.I), robotics, machine vision and sensor technology, computers have become able to efficiently perform a wide range of tasks that only humans could do just a few years ago .
This fear of automation is not a new phenomenon. In 1930, English Economist John Maynard Keynes expressed anxiety about the relationship between automation and work in his essay: Economic Possibilities for our Children. In the essay, Keynes warns of technological unemployment — which refers to the loss of jobs caused by technological change .
Keynes fear of technological unemployment animates and inspires Frey and Osborne’s paper on the future of employment. In this paper, Mr. Frey and Mr. Osbourne seek to address a quintessential question: How susceptible are jobs to computerization?
To address this question, they hope to build on the existing literature by utilizing recent advances in Machine Learning (ML) and Mobile Robotics (MR).
They then develop a novel methodology to categorize occupations according to their susceptibility to computerization. They implement this methodology to estimate the probability of computerization for 702 detailed occupations and examine impacts of future computerization on US labor market outcomes.
These estimates help Frey and Osbourne examine expected impacts of future computerization on labor market outcomes. They distinguish between high, medium, and low risk occupations, depending on their probability of computerization.
They estimate that around 47% of total U.S employment is in the high-risk category and could potentially be automated — perhaps over the next decade or two.
The model predicts that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, are at risk.
Surprisingly, it is also found that a substantial share of employment in service occupations — where most US job growth has occurred over the past decades — are highly susceptible to computerization. This model is evidence that the anxiety about technological unemployment that is brewing in the U.S is not misplaced.
Automation may very well have a robust negative effect on wages. Acemoglu and Restrepo investigate this phenomenon. Specifically, they examine how robots and automation technologies could displace workers from tasks that they were previously performing.
They focus on the variation in robot adaptation originating from the technological frontier proxied by trends in other economies that are more advanced than the United States in robotics technology — like Denmark, Finland, France, Germany, Italy, and Sweden.
These countries are ahead of the United States partly because their demographic trajectories have generated greater demand for automation technology.
In light on this, Acemoglu and Restrepo issue a warning. The claim that in the next decade, we are likely to witness major advances in artificial intelligence, machine learning, communication technologies, and more.
Although the effect of these technologies on employment and ages is yet to be explored in depth, it could have negative implications on employment and wages. They emphasize that if robotic technologies proceed as expected by experts over the next two decades, the future aggregate implications of robots could be larger.
Fear of automation in the United States is justified and prescient. Frey and Osbourne illustrate this to use when they find that many jobs in the U.S are susceptible to automation in the future.
Acemoglu and Restrepo find that if robotic technologies proceed as expected by experts over the next two decades, the future aggregate implications of robots could be large.Therefore, a new social contract must emerge between policymakers and citizens to make sure citizens right to work is protected.
 Geiger, Abigail W. “How Americans see automation and the workplace in 7 charts.” Pew Research Center. Retrieved March 1 (2019): 2020. https://www.pewresearch.org/fact-tank/2019/04/08/how-americans-see-automation-and-the-workplace-in-7-charts/
 Frey, Carl Benedikt, and Michael A. Osborne. “The future of employment: How susceptible are jobs to computerisation?” Technological forecasting and social change 114 (2017): 254–280.
 Acemoglu, Daron, and Pascual Restrepo. “Robots and jobs: Evidence from US labor markets.” Journal of Political Economy 128, no. 6 (2020): 2188–2244.
 Frey, Carl Benedikt. The technology trap. Princeton University Press, 2019.
 Keynes, John Maynard. “Economic possibilities for our grandchildren.” In Essays in persuasion, pp. 321–332. Palgrave Macmillan, London, 2010.