Risk Management and Automation

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). They move from rural area to rural area for seasonal work, or they migrate to urban areas. Many of the working poor live in suburbs today, as is the case in Atlanta’s suburbs where more than 80% of the region’s working poor can be found (Lee, 2018). Thus, it is a complex mix of demographics geographically speaking.
As many unskilled workers relied on manufacturing jobs in the 20th century, they were able to find work until manufacturing in the U.S. began to be offshored and sent overseas. This created a vacuum for the unskilled worker, who struggled to find employment in the loss of America’s manufacturing base. Today, these workers have been forced to take low-skilled, low-paying jobs in the services industry—i.e., they are bartenders, waiters, waitresses, or engaged in other services such as housekeeping, teaching or tutoring, or nursing. Some jobs will pay more but the ones that pay more require credentials obtained from four years in college—which only 2% of the working poor actually have.
The loss of low-skilled manufacturing jobs has put low-skilled workers out of the jobs they used to rely upon, so now they are treading water as best they can by working in services that pay less and force them to rely on tips in many cases. This was caused by the rise of globalization in the latter half of the 20th century. Corporations found that they could obtain cheap labor from overseas so they began sending work to Asia and other parts of the world to increase their margins. This negatively impacted workers at home, however, as they now found themselves with recourse to the same jobs that had existed in the sector previously.
Social Risks
The rise of automation has led to the expansion of numerous industries getting involved in automated machines. Uber, Lyft and Google have all dabbled in automated automotive engineering, with self-driving cars predicted to be the future (Duhigg, 2018; Kosoff, 2018). The rise of artificial intelligence has also change the way people think about managing their own lives. Google Assistant, Amazon’s Alexa, and Apple’s Siri are all listening on all devices, waiting for their owner to mention their name so that they can respond (Navarro, 2018; Pesce, 2018). The technology is not perfect yet, however. Forsberg (2003) has noted that speech recognition software can be faulty and that has led to some people having their entire lives recorded by their devices without their even realizing it (Chokshi, 2018). With Amazon’s Echo, one is supposed to say, “Hey, Echo,” and the device will activate—but as some consumers have learned, the device may be activated unwittingly and it may even end up sending private information to people who should not have it (Chokshi, 2018). This has obviously led to security and privacy concerns as well, which is what this policy paper intends to deal with.
The benefits of AI algorithmic decision-making are that the machines can work quickly to help people perform functions that used to take longer. For instance, in market trading, algorithms have been written to help traders read the news headlines, interpret messages on public social media profiles and scan the Internet for all relevant data before making a trade—and all this performed within the blink of an eye (Yip, 2018). This kind of AI usage obviously has its benefits for traders who are looking to profit off information before human users have time to process information and put on a trade. However, it has its limitations. Algorithms can cause flash crashes in the market because they fail to interpret moves or information correctly and they all pile into trades that make no logical sense and that human traders can see and profit from.
De Smet et al.
One group of experts has identified the coming automation and its impact on workers—i.e., via displacement—is one that Human Resources Managers are going to be considering carefully, as it will provide them with a way of managing human capital. De Smet et al. (2016) state that “this coming digitization of the workforce—and the powerful economics of automation—will require a sweeping rethink of organizational structures, influence, and control” (p. 30). In other words, organizations will see the benefit of automation in terms of reducing the need to rely upon human capital. By investing in automation, they will be able to scale down reliance on human workers and divest themselves of the costs associated with hiring, training, and providing benefits for workers while employed and post-retirement. The speed with which information can be shared, sent, and recorded has increased, and the nature of communications allows for new remote management possibilities throughout virtually every sector of business, which means that automation will be used to enhance operations both domestically and internationally. So workers at home and workers abroad will both be impacted. In short, not only will workers in the domestic circle be displaced but so too will the cheap laborers who have benefited from offshoring in the past few decades. Their jobs are also at risk. Human resources leaders have already recognized that the “combination of platforms, markets, and deeper engagement with digitally enabled workers holds appealing implications for managing human capital” (De Smet, 2016, p. 34). These appealing implications for managing human capital are simply this: automation will allow managers to divest themselves of human capital and reduce costs.
The effects of this on the workers, however, could be quite significant, as the statistics on the working poor show: 12 million individuals already make up the working poor in America, and that number could increase exponentially internationally if companies move more and more towards automation.
Sir James Goldsmith
Sir James Goldsmith was an Anglo-French financier, tycoon and politician and a Member of the European Parliament. As an entrepreneur, he had extensive experience, background and expertise in the field of business operations. He was an avid critic of offshoring labor and believed that companies that displaced workers from jobs domestically did so at their own peril: those workers were the ones who supported the organizations and served as the consuming public. If they became the working poor, they would not have the income needed to sustain the business or its productions—no matter how much it saved in labor by offshoring. This was the argument of Goldsmith and it is pertinent and relevant to the discussion of risk management with respect to automation today.
Sir James Goldsmith (1994) discussed the role and effect that automation will have on jobs in the future when he stated: “High-tech industries can, indeed, survive and prosper under these circumstances, for the very reason that they are highly automated and therefore employ few people” (p. 28). In other words, the industries that turn to automation will be able to save costs in labor—but there is a problem that must be addressed because companies do not operate in a vacuum. The costs of displacing workers can come back and impact the global economy. For companies, they feel to see this because they look at labor only as a cost for business and not as a necessary component of the global economy. To companies, “labour is no more than a minor item in the overall cost of the products they make. But obviously they cannot compensate for the lost manufacturing jobs: the fact that they employ few people means that they are incapable of employing very many. As soon as they need to employ a reasonable number, they will be forced to move offshore” (p. 28)—and in doing that they further undermine the social and economic platform that supports their very industry. Industry requires that there is a consuming population with money to put back into the economy. If automation displaces the unskilled worker, the impact is not isolated to the worker: it comes back to haunt the economy and undermine the platform of the business.
The social and economic stability that follows then turns to political interference. Political leaders begin to legislate and try to solve the issue by interfering with the business model that the company should have, ethically speaking, been adjusting from the beginning. The free market is not without the need for principles and ethical standards, Goldsmith (1994) notes. It is these standards that help to prevent risky business models from being implemented. Turning to automation and displacing jobs comes with substantial risk and the ethical principle that should be used to guide companies in this issue is the duty that the company owes to its community, to employ the workers from its own domestic sphere and to ensure that there is a symbiotic relationship between the company and the community. The community provides labor and the company provides the pay. If that relationship breaks down, the whole of social balance can break down and pave the way for unrest and potential revolution.
Wike and Stokes
Wike and Stokes (2018) examine this issue 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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