Introduction
With Elon Musk of Tesla advancing the field of automation at a rapid pace and envisioning a million “robotaxis” on the roads by 2020, the question of risk management is one that has to be considered with respect to the field of automation. Numerous companies are turning more and more to robotics. Amazon uses robotics in its shipping and supply warehouses to streamline processes and keep shipping moving at an acceptable rate. One of the risks created by this advancement in technology, however, is the risk of automation displacing human employees. This risk has substantial social and economic downside plus potential political risk, as political backlash tends to follow social and economic developments. When America began offshoring jobs in the 20th century, it resulted in the rise of the working poor and the widening of the income gap between the upper and lower classes. If more workers are displaced by automation in the coming years, it could be another trend downward for unskilled laborers as jobs are either exported or eliminated by way of automation. This paper will examine what experts in the field—De Smet, Lund and Schaninger (2016), Goldsmith (1994), and Wike and Stokes (2018)—have to say on the topic and discuss what it means for the field of risk management in general.
Background on Social and Economic Risks of Job Displacement
As Wike and Stokes (2018) point out, the concern over automation displacing jobs is a global one: “In South Korea, there are more than 600 installed industrial robots for every 10,000 workers in manufacturing facilities. In Japan there are more than 300 and in the United States nearly 200. Profit maximization, and the relatively high cost of human labor, helps drive automation” (p. 2). Automation is happening whether people like it or not—and there are very definite risks not only for people as individuals but also for the global economy, which depends upon consumers have disposable income. If consumers all turn into the working poor—i.e., individuals who work low-skilled, low-paying jobs and rely on government subsidies for basic expenditure, such as housing, health care, food, and education, there will be little to no disposable income to help support the economy. Either all markets will end up becoming centrally planned (which has not worked well in the past, if the Soviet Union is to serve as any example), or they will crash—and it is quite likely that some combination of the two may occur. The people have noticed. Wike and Stokes (2018) note that “in all 10 advanced and emerging economies polled, large majorities say that in the next 50 years robots and computers will probably or definitely do much of the work currently done by humans. In three countries—Greece, South Africa and Argentina—four-in-ten or more believe this will definitely happen” (p. 3). It is therefore important to pay attention to what this means and what risk management should consider. The first place to look is the statistics on job displacement as caused by offshoring and what it does to increase the level of working poor in the nation. The rise of automation risks leading to a greater rise in the level of the working poor.
Economic Risk and Problems Currently Impacting the Sector
Job displacement in the U.S. has led to the rise of the working poor. Who are the working poor? The working poor, according to the Center for Poverty Research at University of California, Davis (2018), are “people who spend 27 weeks or more in a year in the labor force either working or looking for work but whose incomes fall below the poverty level.” There are currently 12 million working poor in America today (Policy Link, 2019).
The demographics show that the working poor in the U.S. generally fall into these categories:
· 11.7% Black, 11.7% Hispanic/Latino, 5.5% White, 4.3% Asian
· 7.2% women, 5.5% men
· 18.3% with less than a high school diploma
· 8.3% high school graduates with no college education
· 2% with a bachelor’s degree or higher (Center for Poverty Research at University of California, Davis, 2018)
Latinos and African-Americans make up the main shares of the working poor in the U.S., and women tend to be among the working poor more than men (often because they are single mothers). Nearly 1 out of every 5 working poor lacks a high school diploma. Nearly 10% of them have no college education, and only 2% of the working poor have ever obtained a bachelor’s degree. Thus, education is a big factor in explaining the conditions of the working poor, as most of them have never obtained a four-year degree that could be used to get a better job.
Moreover, the Pew Research Center (2014) shows that the gap between the rich and everyone else has never been higher: “America’s upper-income families have a median net worth that is nearly 70 times that of the country’s lower-income families, also the widest wealth gap between these families in 30 years.” The average income for the rich is $634,000 per year. The average income for the middle-income family is $96,500. The average income for the working poor is $9,300, less than 10% of the middle-income family, and a little more than 1% of the income of the higher end of the upper class family (Pew Research Center, 2014). These statistics show a staggering gap between the rich and the working poor in the U.S.
As Lee (2018) notes, the working poor consist of “those who tip-toe just above the government’s official poverty line, which for a family of four means an annual income of less than $23,850 and for an individual means an annual income of $11,670.” Recent reports suggest more than 50% of food stamp recipients are the working poor. Many of them are migrant workers, so it is difficult to tell who is homeless and who is not, as the statistics are not available (Lee, 2018)....…for the Pew Research Center. They note in their study of the rise of automation and public fears that people tend to expect their governments to intervene to protect them and ensure that they are not displaced from their jobs by automation. Wike and Stokes (2018) show that various populations
Place responsibility for dealing with the evolving nature of work on a variety of institutions and actors. Government looms large in the minds of many. Nearly eight-in-ten Argentines say government has a lot of responsibility for ensuring that the nation’s workforce has the right skills and education to succeed in the future, and more than seven-in-ten hold this view in South Africa, Brazil, Greece and Italy. Only in the U.S. do fewer than half believe the government has a lot of responsibility for preparing the nation’s workforce (p. 6).
In some parts of the world, such as Denmark, government is investing in ways to help people adapt to the trend towards automation. Education is part of that investment, but not every laborer will be able to meet the demands of learning a skilled-trade. Unskilled labor was a backbone of American industry for years—but, first, with offshoring, and now with automation, that backbone is broken. There is nowhere for the unskilled laborer to go. Some look to organizations and businesses to address the problem ethically, and that is what Goldsmith has called on companies to do—but it is by no means an easy solution, as companies are already feeling the pressure to use automation to stay ahead of the curve. However, they are undermining their own advantage because the working poor will not be able to support the companies’ business models in the future.
Intervention will be needed in some manner, but the trend towards automation risks causing a massive wave of poverty growth around the world. Automation may benefit those who have learned skilled-trades or who are able to work with AI, but this population will eventually dwindle as well because the economy will not grow at the same time poverty is increasing exponentially. The only remedy for poverty is labor paid with a fair wage. If there is no labor to be offered because everything has been taken over by automation, the future of mankind is seriously in jeopardy, and Wike and Stokes (2018) show that this concern is widespread among the populace.
Conclusion
The issue of automation and the risk it brings of displacing jobs is a real one that must be faced, according to the experts in the field. The companies of the world are moving more and more towards automation, but they may be rushing headlong into their own demise. Companies must participate in a two-way exchange with communities: they provide jobs and communities provide consumers. If that exchange becomes one-sided, the relationship breaks down and the social organization completely falls apart altogether. This is the greatest risk to manage of all.
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Center for Poverty Research at University of California, Davis. (2018). Who are the working poor? Retrieved from https://poverty.ucdavis.edu/faq/who-are-working-poor-america
De Smet, A., Lund, S., & Schaninger, W. (2016). Organizing for the future. McKinsey Quarterly, 1, 30-43.
Desilver, D. (2018). For most U.S. workers, real wages have barely budged in decades. Retrieved from
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Goldsmith, S. J. (1994). The trap. Carroll & Graf.
Lee, T. (2018). Geography of poverty. Retrieved from http://www.msnbc.com/interactives/geography-of-poverty/index.html
Pew Research Center. (2014). America’s wealth gap between middle-income and upper-income families is widest on record. Retrieved from https://www.pewresearch.org/fact-tank/2014/12/17/wealth-gap-upper-middle-income/
Policy Link. (2019). An overview of America’s working poor. Retrieved from http://www.policylink.org/data-in-action/overview-america-working-poor
Wike, R., & Stokes, B. (2018). In Advanced and Emerging Economies Alike, Worries About Job Automation. Pew Research Center, Global Attitudes & Trends. Retrieved from https://www.pewglobal.org/wp-content/uploads/sites/2/2018/09/Pew-Research-Center_In-Advanced-and-Emerging-Economies-Alike-Worries-about-Job-Automation_2018-09-13.pdf
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