Bought from Bots

If you hate interacting with people, Henn na Hotel in Japan may be for you.

This Tokyo hotel not only boasts modern, high-tech architecture, but also comes with a twist — it is run almost entirely by robots. Mechanical dinosaurs greet you at reception; robotic arms deposit your luggage into your room. It is a technophile’s dream.

Henn na Hotel may be extreme, but it represents a global trend towards increased automation  in even the most unexpected sectors. This change will be dramatic: The Brookings Institution estimates that about 25 percent of United States’ employment, or around 36 million jobs, are at risk of being replaced by automation in the coming decades. McKinsey predicts that worldwide, between 400 and 800 million jobs could be lost due to automation by 2030.

These staggering projections have caught the attention of companies and governments around the world. Not only must governments preserve the welfare of their citizens throughout this shift in labor demand, but companies must also find a way to transition smoothly from humans to automatons. The exponential development of automation and robotics threatens the jobs of millions around the world and must prompt serious discussion around how to best prepare the workforce for the future.

Rewiring the Workforce

Robots, artificial intelligence, and automated processes are capable of far more than vacuuming your floor or polishing steel in factories. A report by Oxford University finds that some of the jobs most at risk of replacement from automation are those regarding data entry, financial accounting, driving and transportation, manufacturing, and marketing. As technology continues to progress, the list of professions that robots can excel at will only expand.

But there is still hope for us mere humans. Projections from the World Economic Forum state that while millions of jobs will be lost from automation, it is possible that technological advancement could actually create almost double the jobs that it will displace. These jobs are primarily STEM-focused jobs, such as those requiring data analysis, software engineering, and automation expertise.

However, the jobs created by the wave of automation will likely require different skills from the jobs lost. The WEF continues to predict that by 2022, at least 54 percent of employees will need “reskilling” or “upskilling.” That means additional training, which may take anywhere from six months to over a year. The aforementioned McKinsey report corroborates this finding, estimating that up to 375 million workers globally will need to switch occupational sectors.

This mismatch between skills demanded and supplied in the labor market requires a shift in how the world pursues education. The WEF suggests that much of “upskilling” can be done within companies, where corporations develop training programs to maximize employee growth throughout their careers. Policymakers and educational institutions can play a role as well, whether it is offering targeted technical courses or providing more incentives to attain a higher education.

Gear-ing Up for Change

Just as technological change pushes the job market to become increasingly skill-stratified, automation also widens the socioeconomic gap between demographic groups. Because some jobs are easier to automate than others, artificial intelligence and robotics may threaten the jobs of those who need work the most. Based on trends in just the past few years, the groups that will be hardest hit are men with low levels of education working in manual labor and other blue-collar jobs and women who work in intermediate, administrative positions. Jobs that require more advanced education and interpersonal interaction are less at risk.

This asymmetry has the potential to widen the already-growing income inequality gap worldwide. Economists at the Federal Reserve Bank of St. Louis find that because occupations that are most likely to be replaced by robots are low-paying, automation in America will likely significantly increase the Gini coefficient, which is a measure of income inequality where a higher number represents more inequality. In the worst-case scenario, the Gini coefficient more than doubles.

Demographic gaps will likely grow as well. For instance, women are particularly at risk of being replaced by automation and are already underrepresented in the workforce. The Institute for Women’s Policy Research reports that women make up the majority of employment in high-risk occupations, such as those that involve routine data work, and are significantly underrepresented in the sectors that have the potential to grow, such as STEM-related jobs.

Many ideas have been suggested to alleviate the effects of potential job loss in vulnerable groups. One option is offering a universal basic income, which would hypothetically use some of the revenue generated by automation productivity gains to provide a periodic cash payment to citizens affected by automation — or even all citizens in general. Other ideas, perhaps less radical but certainly still controversial, include creating public-sector jobs, taxing robots, and providing a larger social safety net.

Regardless, only time will tell how much the technological revolution will change the landscape of our labor markets. For instance, Henn na Hotel has recently ‘fired’ half of its robot staff for the robots’ inability to perform tasks like recommending local attractions or understanding accents. In the foreseeable future, human employees will still be in demand in spite of — or perhaps, because of — increasing automation around the world. However, it is up to companies and policymakers to ensure that the workforce has the skills to capitalize upon these opportunities.

Image Credit: Unsplash/Andy Kelly

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