A new widely noted report from McKinsey Global Institute (MGI) that assesses the effects of automation in various socioeconomic environments suggests that while intelligent automation – the merging of artificial intelligence (AI) and automation – could put 73 million Americans out of work by 2030, a combination of economic growth with other factors of rising productivity could more than offset the losses.
The paper’s co-author, Susan Lund, believes that even-though the integration of new technologies, such as machine learning, self-driving cars, and AI systems, will radically change social and economic life, “[t]he dire predictions that robots are going to take our jobs are overstated”. Lund says there will be enough work “for everyone in most sectors.”
Yet globally the workforce remains divided into two groups: highly paid, skilled workers, and low-paid, unskilled workers. As more jobs get automated, this trend will most likely continue, making the ‘full employment’ scenario a massive challenge for the labor market and one, the report says, that rivals or exceeds the transition of the labor force from agriculture into manufacturing-dominated societies in the early 1900s in the US and Europe, and more recently in China.
In their report, entitled “Jobs lost, jobs gained: Workforce transitions in a time of automation,” MGI researchers estimate that globally, between 400 million to 800 million workers across 46 countries could be displaced by 2030, and as many as 375 million may need to switch jobs or learn new skills as a result of exponential improvements in new technologies. In the U.S. alone, and as mentioned, between 39 million to 73 million jobs could be destroyed. According to the study, about 20 million of those displaced workers, or as much as a third of the U.S. workforce, can be shifted into similar occupations. Up to one-third of the 2030 workforce in Germany, and nearly half in Japan will also be in need of learning new skills and find work in new occupations. The research however, predicts that the adoption rate of automation could be far slower globally, perhaps forcing less than 10 million workers to switch occupations.
So which jobs are most vulnerable to automation?
In particular, after examining the probability of computerisation for a wide range of occupations, the MGI study found that low-paying jobs, such as operating machinery and preparing fast food are the most susceptible to intelligent automation. The study also warned that most workers involved with processing and data collection are likely to be substituted by automation as these activities can increasingly be done better and faster with machines. Furthermore, many workers in services like mortgage origination, paralegal work, accounting, and back-office transaction processing could be displaced in large numbers.
Jobs safest from the effects of automation include health care/elder care providers, architects, engineers, scientists, IT professionals, educators, as well as gardeners, plumbers and electricians.
The MGI report reinforces the idea that in a technology-driven world, advances in automation will eliminate large numbers of jobs across a range of industries. In fact, changes to the future employment landscape are already underway. Companies like Walmart, Amazon and Taiwan-based FoxConn, one of the world’s top manufacturers, producing technology equipment for Apple, Google, Microsoft and a number of other companies have all begun replacing parts of their workforce with intelligent automated processes.
The report also suggests that developed markets like Germany, the US, Japan, and China will be hardest hit by automation while in places where labor is cheaper and tech is more expensive, jobs may be less vulnerable. In particular, the study finds that advances in automation and robotics as a process that raises productivity while shrinking employment could affect up to 100 million Chinese workers, a significant headcount that represents only 12% of China’s 2030 workforce.
The research concludes by emphasizing the fact that while the “labor markets adjust to changes in demand for workers from technological disruptions”, governments around the world will need to provide worker income support and other assistance to help smooth what could be a rocky transition.
“The model where people go to school for the first 20 years of life and work for the next 40 or 50 years is broken,” Lund, told CNN Tech. “We’re going to have to think about learning and training throughout the course of your career.”
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