As Artificial Intelligence envelopes our lives, among the many sectors expected to enter a period of rapid transformation, is transportation. Increasing urbanization, rising incomes, influx of new technologies and the political economy of each of these changes will cause structural shifts in economies, polities and societies. As part of our special report on new technologies, this article is dedicated to analyzing the trucking industry in the United States of America and the changes technology is bringing to the fore in this quintessential American embodiment of freedom - roads.
The engagement trucking has with politics in America has become significant since President Trump rode to the White House on a rust belt vote. All the four key states won by President Trump in 2016 - Michigan, Florida, Pennsylvania and Wisconsin - count trucking as a dominant profession among their residents. The fact that three of these states, Pennsylvania, Wisconsin, and Michigan had not voted Republican since the 1992 Presidential Race, brought forth the anxieties of blue collar workers - from rapid globalization to automation. The consequent fall in incomes, coupled with a threat of skills acquired over decades becoming obsolete overnight, was enough to push them to a rallying cry of a glorious past, no matter how unachievable it might be in reality. What bolstered the sentiment, which Mr. Trump easily exploited, was that trucking in particular was witnessing stagnation in job creation. Bloomberg points out that while jobs in the industry, which constitutes 70% of America's domestic freight movement, had recovered from the depths of depression, job growth had started to slow since 2013. Combine this with the image of Elon Musk walking to cheering cameras with a self-driving truck, and you have the perfect mood of despair, and a perfect mix for disaster. However, recent research has indicated that a key behavioral aspect might just help make the automation less of the bloodbath than previously thought.
Source: US Bureau of Labor Statistics/Bloomberg.
“Artificial Intelligence, Automation, and the Economy”, written by President Obama’s top economic and science advisors just before the 2016 presidential elections estimates that automated vehicles could threaten or alter 2.2 million to 3.1 million existing U.S. jobs. That includes those of the 1.7 million driving tractor-trailers. Long-haul drivers, it says, “currently enjoy a wage premium over others in the labor market with the same level of educational attainment”, placing them in a precarious position of risk and unemployment trap, should they ever lose their jobs.
However, new research, particularly the open source economic analysis published by Uber’s Advanced Technologies group, claims that self-driving trucks will lead to a net increase in jobs. Their model of the industry’s labour market, based on data from the Bureau of Labour Statistics, looks at scenarios where the adoption rate of self driving trucks on the road affects the labour market. The division of trucking jobs into long haul and local haul connected by transfer hubs is central to their argument. As jobs in the latter category are predicted to increase in number and be exclusively available to human drivers, who can handle the complexity of the terrain, the model predicts a net increase in jobs augmented by lowering freight costs leading to increased demand for products, meaning more local haul trips as more people increase their consumption across the country. The prediction resonates with the views of government executives from the transport industry who believe that a driver’s job is more than just driving from A to B, and also includes handling a series of complex tasks between the drive, including the maintenance of the truck. Even sociological reasons exists for autonomous vehicles to take the long-haul burden off driver’s shoulder, as it would enable an easier lifestyle where drivers do not have to be away from home for 200 days of the year. Instead, through transfer hubs, they would enter good local jobs which enable them to be closer to their families, and reduce some of the nasty labour abuses in the low-paid trucking industry.
Navigating Change through Risky Means
As was the case with the ATM’s disruption of banking jobs, the process of creative destruction allowed for that sector to be pried open with some pain, invigorating possibilities offered by banking and enhancing consumer friendliness. A vast majority of studies that predict a doomsday for trucking jobs ignore the existing state of the industry and the potential that remains unexplored, making their analyses less robust, and the predicted doomsday, less likely.
However, the changes Uber envisages depend heavily on the leverage it has over the political system, as introduction of autonomous vehicles will force it to use its increasing clout in wresting changes in regulation and restructure wages. Uber’s responsibility to collectively bargain for truck drivers will also increase its control over the labour force, and will have to be balanced by regulatory changes that prevent its monopolization of the industry.
The political engagement with the changing faces of each sector awaiting disruption due to automation, are largely responsible for the skepticism driving the automation paranoia. Even the question of people adapting to these labour market upheavals by enhancing their skills is in doubt, when the unemployment benefits system does not have the capacity to assist that volume of personal enhancement as more people lose their jobs.
This engagement is not just restricted to the written law, but extends to the nature of the political discourse as well. President Obama, in his farewell speech to thousands in a packed convention hall in Chicago warned,
“The next wave of economic dislocations won’t come from overseas. It will come from the relentless pace of automation that makes a lot of good middle-class jobs obsolete.”
This message was a softer, perhaps more prudent reflection of the times, than the aggressive political discourse from the Trump campaign, which framed the stakes of the election in losses rather than gains, prompting middle class voters to swing the election in favor of the aggressive, unpredictable capitalist who billed himself as the riskier bet. The election, having been decided by the Rust Belt, was dominated by voters behaving in accordance with Kahneman and Tversky’s Prospect Theory. The theory suggests that given a choice of playing it safe when confronting gains and, taking risks when confronting potential losses, people prefer risks in the hope of minimizing the damage. For many who had suffered indignation at the hands of the elite and the 1%, Mr. Trump was the risk at a time of potential losses.
However, it is important to realize that, although the damage has been done through the election and its continuing aftermath, this risk-seeking behavior among the American middle-class might just be the crucial ingredient in dealing with the automation disruption. A class of individuals and families, who have made riskier political bets, and see little economic returns from them, can question their unending predicament and demand a change of their fortunes through collective action and enhancements to their repertoire of skills. Enduring upheavals that have resulted in economic gain for many, have often been a result of the constant particle accelerator-esque collision of changing attitudes, eventually crystallizing a complex interwoven structure that incorporates differences better than the quick-fix populist politics. A more optimistic outlook towards automation, allied with the constant fear of a robot snatching your job keeping you on your toes, might just be the ideal recipe for navigating the Fourth Industrial Revolution better than we think.
Comments and suggestions are welcome. Article has been updated for accuracy.
About The Author
Balasubramanyam Pattath is a Research Associate at the Indian School of Business. He holds a Masters in Development Studies, from the Graduate Institute of International and Development Studies, Geneva, Switzerland. Originally from Kerala, India, Balu has a Bachelor in Economics from the University of Delhi. His interests and past work concern migration, demography, labour and, employment. He has served as the co-chief editor of the Hans Raj college Economics journal in 2014-15. He has also published several papers on the intersection of AI with manufacturing and education in peer-reviewed journals. During his undergraduate studies, Balu was an active quizzer and respected quizmaster.