Man vs. Machine — Manufacturing
One of the key points that brought President-elect Donald Trump so much support during his campaign is his promise to bring manufacturing jobs back to the United States and to protect domestic products with high tariffs. However, he may come to realize that technological progress, which he had used to his full advantage in his race for the White House and before, is precisely what will prevent him from fulfilling his promise.
This article is not about the harmful effects of isolationism and trade barriers for international corporations. Instead, let us simply discuss important trends in the manufacturing industry, within America and abroad.
Manufacturing in US
Since NAFTA took effect in 1994, the United States has lost about 4,500,000 manufacturing jobs. However, several companies have in recent years begun to build factories in the United States again; these new factories are highly automated, requiring far fewer employees and completely different skill sets.
Greenville, South Carolina once prospered because of their textile industry; however, since 1970, most companies closed down factories here in favor of cheap offshore labor in Mexico or Southeast Asia. According to the U.S. Bureau of Labor Statistics, there were 48,000 workers in textile factories in 1990, but now there are barely 6,000. Other cities abandoned manufacturing and turned to financial services or tourism; Greenville, however, created a new path for themselves—they became a center of new, advanced manufacturing. BMW, ABB, Fluor, Michelin, Bosch, and GE have all established plants here.
BMW’s Greenville site, established in 1994, its first factory outside of Germany and currently its largest factory in the world with 8,000 employees, is a perfect example of seamless cooperation between man and machine. The plant produces 1,400 cars a day (almost one every minute), many of them customized products. BMW has invested 7.4 billion dollars in developing automated equipment—20 years ago, machinery encompasses only 30% of the body shop process, but now machines do 99% of the work; the rooms are dimly lit, and workers supervise operations through their computer screens. On the assembly lines, with more need for human instincts, workers utilize machines while still maintaining flexibility.
Boston Consulting Group reports that it costs barely $8 an hour to use a robot for spot welding in the auto industry. A human doing the same job costs $25 an hour – and the gap is only to widen.
Creating the necessary workforce for more advanced manufacturing, however, is a challenge. These new jobs require more difficult skills, as well as soft skills like problem-solving and teamwork. Local colleges also work to provide training in working with computerized machines, using 3D printers, and performing project-based work that span several fields.
According to MIT Technology Review, in the past 20 years, the investments companies have made on automation and software has doubled every individual employee’s output. However, although the manufacturing industry as a whole has increased output by 40%, the number of people employed has decreased by 30%. The wages have increased, but the competition for jobs has only become more fierce.
Manufacturing in Other Countries
In Korea, there are 478 robots for every 10,000 workers; the number is 315 in Japan, 292 in Germany, and 164 in the United States. China, the manufacturing giant of the world, this number is only 36. However, China’s countless manufacturers are already planning changing production processes with robots on an unprecedented scale; the idea of cheap labor in China has started to become a thing of the past. According to government reports, 35 Taiwanese manufacturers (including Foxconn) with operations located in Kunshan, in Jiangsu Province, have invested 4 billion RMB on AI technology. Foxconn has eliminated 60,000 jobs, and 600 other companies have indicated to government surveys that they will follow suit. 
Shift of Job Opportunity
If we are to observe long-term trends and the impact of digital technology on our jobs (see diagram below), we can see that routine jobs (not just manual but also cognitive), have stopped growing and have even begun to decline in the past 20 years, while nonroutine jobs that require judgment show the biggest growth. On the other hand, nonroutine manual labor opportunities still exist, but are highly replaceable and earn low wages.
To understand how AI affects future society, the White House has published research since October 2016 in hopes of positively affecting AI’s impact, nurturing a competitive workforce, and preventing the loss of jobs to AI and thus worsening social inequality. Policies aim to prevent bias in algorithms and strengthen academic and technical education. 
We will continue to discuss how AI is being utilized in cognitive work in future articles, and what this means for future workforce and learning. Please comment, share your ideas with firstname.lastname@example.org .