Unanticipated impact of automation and AI on blue collar jobs

In today’s lexicon, automation, artificial intelligence, and machine learning are 3 interchangeable terms that are often misinterpreted and mixed up with each other. An intuitive explanation of the terms would be as follows -

· Automation is the replacement of tasks performed by humans with machines, specifically designed and instituted for a specific purpose usually operating in the realm of manufacturing or other production process with minimal or reduced human intervention.

· Artificial Intelligence is a refined concept of technology aimed at simulating human skill sets such as logical thinking, reasoning and decision making.

· Machine learning is a branch of artificial intelligence, that provides the system the ability to identify inherent patterns and insights from data, improving itself without the need for explicit manual intervention.

These terms are the supreme inventions that are responsible for pivotal technological changes that the world is currently experiencing. Both automation and artificial intelligence has had all encompassing ramifications for all human ventures – from automated flight systems to improved assembly lines, to customer support chat bots to predictive analytics.

Although rapid technological advancements have recently become a prevalent issue, concerns regarding its ambiguous effects can in fact be dated back to the 1830s, where industrial workers first experienced the negative effects of automation. Instead of submitting to it, the textile workers renamed themselves as the “Luddites” and staged an audacious attack against the machines, burning and attacking the factories. This reaction was an implication of the fear of machines robbing them of their livelihood. While the advent of artificial intelligence and automation has reaped tremendous economic and social benefits, it has also since then proven to pose several unparalleled challenges. Specifically, there have been numerous controversies regarding its impacts on the future of blue-collar jobs.

Due to the common misconceptions amongst the public, the fear that automation and recently AI will wipe out the jobs and displace them has increased to paramount levels. In reality, the effects of automation and AI are rather ambivalent as it depends on the individual who is making that judgement. The current uncertainty around the possibilities with AI makes it extremely crucial for dedicated research be conducted to scope it out, and this is faced with limitations that have been imposed on the scientists such as the lack of quality data about the dynamic requirements o occupants, absence of empirical models of skill replacement and human-machine reciprocity, and the inadequate understanding of how cognitive technologies interact with social demographics.

The question remains – how do we measure the true effects of automation and AI? What data do we use and what are the study parameters? What are the jobs that will be truly impaired by this and what will be transformed? What is the study? and most importantly, who is conducting the research? The uncertainty around this has contributed to the widespread prejudice against advancements in AI. Regardless of this, there is ample evidence that suggests that while automation will cause disruptions to the workforce, it will not heavily impact the blue-collar jobs because of its greater impact on white-collar jobs, the growing scarcity of blue-collar workers and rapid job transformation effects.

A blue-collar worker refers to someone whose profession requires them to participate in some type of labor-intensive task that may fall under skilled or unskilled bucket depending on industry needs and type of work. Whereas white-collar workers are non-manual workers whose job entails mental or administrative work, such as in a corporate office where the work is knowledge-intensive and requires highly specialized skill sets. The primary differences between white-collar workers and blue-collar workers are found in their nature of work, salary, education, and work setting. The routine nature of blue-collar jobs is often cited as the reason for greater risk of being substituted by the ‘computer capital’. As such, it has become conventional wisdom to think that the robot revolution is apocalyptic, and this idea is largely commercialized because it elicits the image of gigantic automated machines manufacturing a car and completing everything a employee did before faster.

Until recently, the consensus among researchers seemed to be that workers with higher levels of education and higher up on the corporate hierarchy would be less affected by automation than blue-collar hierarchy. Now, new research by the Brookings Institution suggests that higher-educated and higher-paid, white-collar workers may be facing just as much significant disruption. The report, conducted by Stanford University doctoral candidate Michael Webb, analyzes the types of jobs most exposed to AI and to what extent it impacts future employment rates. Webb accumulated his findings in his paper and concluded that the “most-exposed occupations include clinical laboratory technicians, chemical engineers, optometrists, and power plant operators” (Boudreau) is consistent with those results. He deduces that “high-skill occupations are most exposed to AI, with exposure peaking at about the ninetieth percentile. While individuals with low levels of education are somewhat exposed to AI, it is those with college degrees, including Master’s degrees, who are exposed” (Boudreau).

The reasoning behind this unanticipated report is that “AI is especially good at completing tasks that require planning, learning, reasoning, problem-solving and predicting — most of which are skills required for white-collar jobs” (Liu). Hence, justifying the statistics that “workers who hold a bachelor’s degree (being) exposed to AI over five times more than those with only a high school degree” (Liu). Automation and hence, replacing blue-collar jobs, require significant investment into robots and machines that are designed for a specific task and hence deemed less scalable. In contrast, AI solutions that are significantly software based are cheaper to replicate and maintain, risking current white-collar positions.

In fact, according to Jeetu Patel, the chief product officer of Box, a cloud content management and file sharing service business company, “ half a billion white-collar jobs will be impacted” (Koetsier). This belief is also reinforced in a widely cited McKinsey & Company research, which asserts that “white-collar workers — even those whose work presumes more analytic thinking, higher paychecks, and relative job security — may not be safe from the relentless drumbeat of automation” (Koetsier). White-collar workers are usually hired based on their ability to display exemplary analytic thinking and judgment. Based on this requirement, AI has most certainly proven to be better “at tasks that involve judgment and optimization, which tend to be done by higher-skilled workers” (Liu). As such, even repetitive jobs entailing precision and skill in the white-collar job environment, such as data management and program management are succumbing to automation.

Perhaps the most improbable effect that is hard to fathom is the shortage of blue-collar workers in the United States. Since 2018, the number of job openings has been significantly higher than the number of job seekers. At the end of January 2018, “the US economy had 7.6 million unfilled jobs, but only 6.5 million people were looking for work” (Chamberlain) as per data released by the US Department of Labor. All types of jobs have become harder to fill because of plummeting unemployment rates which continue to sink, enabling several job seekers to find work more easily since the mid-90s. According to The Conference Board, a non-profit organization which researches the American business climate, there is a momentous blue-collar shortage occurring in the US and “the threat of labor shortages is more acute in blue-collar and low-pay services occupations than in more highly educated white-collar occupations''(The Conference Board Inc). The primary causes of the reduction in the blue-collar workforce include an increased number of people receiving higher education, getting skilled jobs by doing internships at professional services, and because lower-income workers are leaving the workforce based on disability claims such as alcohol or drug addiction.

As per Gad Levanon, lead report author and chief economist for The Conference Board, “The picture looks very different for the workers themselves. Compared to a few years ago, blue-collar workers are now much more likely to have a job they are satisfied with and experience rapid wage growth” (The Conference Board Inc). Although the reasons for their scarcity are not directly correlated to automation and the emergence of AI, nevertheless it plays a key role in determining how successful companies will be in terms of hiring the required supply of blue-collar workers. Technological investments would enable companies to use automation to make up for the tight job market, hence reducing the need for human labor. However, doing so may ravage several customer relations. For example, baristas, which suffice to the definition of a blue-collar to some extent, are one of the fastest-growing occupations today. Starbucks, the American company with the largest coffeehouse chain in the world, is not oblivious to the numerous technological innovations that can make the process of artisanal coffee quicker and more efficient. However, they purposefully choose to avoid it because they are well-informed of the reason why people prefer going to Starbucks rather than some upscale coffee shop in town. It is the performative dimension and the experience which gives it an edge over other mechanized coffee shops. This helps explain why there continues to be a big market for service-oriented jobs despite the incoming of new technology.

There are indeed fewer labor-intensive jobs available than there were 60 years ago (U.S. Bureau of Labor Statistics), but the blue-collar worker industry is very much present and rising. The trucking industry is an ideal example to demonstrate the difficulty in finding blue-collar employers. Truck drivers fall into the category of blue-collar workers and their profession requires the need for purchases and packages to be dropped off at people’s doorsteps. Artificial intelligence has given away to the meteoric rise in e-commerce which in turn has increased the demand for storage and transportation of consumer goods, hence increasing the demand for truck drivers. For this reason, blue-collar workers in industries like construction and transportation have substantial leverage over gaining employment and insisting on a higher wage or salary.

Succeeding the Great Recession, automation and artificial intelligence caused immense perturbation regarding permanent mass unemployment. Feeding on a public alarm, several economists and researchers assessed the possible effects of the supposedly dooming innovations. Many feared that as AI and automation grows, it would supplant workers, render catastrophic job loss, and create a never-ending pool of unemployed workers. Today, after more than a decade of perpetual advancements in modern technology, the fear of automation continues to be entrenched in the country’s psyche. Present-day research counters the ubiquitous fear regarding the loss of jobs due to automation. The wave of automation has redefined the labor market by destroying but also creating several new job openings. It has also expanded long-standing ones. According to the World Economic Forum, “in the next four years, more than 75 million jobs may be lost as companies shift to more automation”(Shaban). However, the predictions have an upside: “133 million new jobs will emerge during that period, as businesses develop a new division of labor between people and machines” (Ratcheva).

For instance, automation has made language translation extremely convenient and is speculated to have displaced many human translators. However, according to the US Bureau of Labor Statistics, demand for human translators is escalating because with AI making translation automated, the cost of translation drops down to zero which subsidizes the cost of doing business with people who speak other languages. This, in turn, generates higher profitability by encouraging companies to conduct business with foreign nations where the need for human translators dramatically escalates. As per One Hour Translation CEO Ofer Shoshan, “a lot of translators and agencies will tell you that there are certain highly specialized translation services which will require a human touch for the foreseeable future” (Marr). This goes to show that despite automation displacing jobs, it is also creating just as many or perhaps many more jobs.

Another study about manufacturers, conducted by Deloitte found that despite the “800,000 low-skilled jobs that were eliminated due to the rise of automation, 3.5 million jobs were created, and those jobs paid an average $13,000 more per year” (Ghafourifar). Automation has numerous advantages which have made several lower and middle-class workers’ lives much easier. With the introduction of machines and robots, their jobs have become safer, less physically demanding, and have created more rewarding job profiles for the workers. These findings are in support of the notion that automation does not kill jobs but rather modifies them and emboldens people to expand their potential and abilities. In the case of Boxed, an online retail company, when “AI and robotics replaced the need for 100 fulfillment workers at Boxed New Jersey facility, the online grocery startup retrained and promoted them into different departments” (Marinova). As such, “several former temp workers became full-time employees and enjoyed a 13 percent pay increase” (Ghafourifar). The motive behind doing so was not financially driven, it was simply a values-driven decision to retain its workforce - an act that is much more commonly done than discussed.

In this manner, AI and automation will create millions of jobs that are beyond comprehensibility. Now, despite the accessible statistics and scientific information refuting the idea that mass job loss due to automation and artificial intelligence, several employees continue to remain petrified. The media has raised the alarm and commercialized this to a degree where blue-collar workers unequivocally accept that automation and artificial intelligence will supersede them. While this topic has garnered considerable attention, much of the press has mostly focused on the potential challenges arising from new technological advancements without proposing pragmatic solutions or ways companies can mitigate the fears of their workers.

The qualm and panic are an organic response to the changes introduced in a company and therefore it is the business leaders’ responsibility to manage the anxiety and mitigate it. By informing and familiarizing the workers with the reality of automation, the company will eliminate a lot of the mental stress that several workers go through; especially if they are the only breadwinners in the family. The companies should also acknowledge the need for new skills that are needed to keep their workers relevant and provide them with the necessary personalized learning paths. The rapid innovation also deems it necessary for investments in retraining and offering tailored recommendations to ensure that employees are engaged in continuous learning. It takes an effort to enable and allow the employees to leverage the efficiencies and benefits of artificial intelligence and automation. Most importantly though, the success of companies and their relationship with their employees is heavily dependent on their ability to adjudicate between valuable human acumen and lucrative technological innovations.