The rise of artificial intelligence (AI), machine learning, and robotics will lead to the loss of up to 20 million manufacturing jobs worldwide by 2030, according to a Wednesday report from Oxford Economics.
Around 1.7 million manufacturing jobs have already been lost to robots since 2000, the report, titled How Robots Change the World, found. These include 260,000 jobs in the US, 400,000 jobs in Europe, and 550,000 jobs in China.
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Global stock of industrialized robots has more than doubled since 2010. If this rate of robotization holds, the global manufacturing workforce will shrink by 8.5% by 2030, according to the report.
Each new robot installation replaces an average of 1.6 manufacturing employees, Oxford Economics found. The use of robots in service industries will also increase rapidly in the coming five years, thanks to advances in AI, machine learning, and engineering. This will impact sectors including logistics, healthcare, retail, hospitality, and transportation.
China currently has the most robots installed, representing one out of three worldwide, the report found. By 2030, China will have as many as 14 million industrial robots in use, consolidating its position as the world’s largest manufacturing hub, the report predicted.
Displacing the most vulnerable workers
Unsurprisingly, the displacement of jobs due to the rise of robots will impact poorer regions the most, according to the report. Lower-skilled regions, which tend to have weaker economies and high unemployment rates, will be most vulnerable to the loss of jobs due to robots. Each additional robot installed in those regions will lead to an average of almost twice as many job losses as those installed in higher-skilled regions of the same country, the report found.
Jobs that involve repetitive functions, such as warehouse work, will be most affected by robots, the report found. While jobs that are less structured and require more creativity, compassion, or social intelligence will likely continue to be dominated by humans, robots will play an increasingly large role even in those areas, it added.
Despite the job losses, robotization will ultimately boost productivity and economic growth, and create new jobs at a similar rate that it destroys old jobs, Oxford Economics noted. Millions of new jobs are expected to be created throughout all sectors of the global economy.
Worldwide, a 1% increase in the stock of robots per manufacturing employee leads to a 0.1% productivity boost in terms of output per worker and driving meaningful growth, the report found. Faster adoption of robots increases both short- and medium-term growth: A 30% rise in robot installations above the baseline forecasts for 2030 would lead to a 5.3% boost to global GDP that year, equivalent to nearly $5 trillion, Oxford Economics predicted.
Policy implications of AI
As companies across sectors continue to implement robotics, policymakers will need to grapple with the fact that while this technology enables growth, it also exacerbates income inequality, the report noted.
More than half of US workers who have left production jobs in the past two decades moved to jobs in transportation, construction, maintenance, and office and administrative work, Oxford Economics found. This is concerning, as those sectors are among the most vulnerable to automation in the next decade.
While this should not lead policymakers to slow or stop the adoption of robotics, the focus should instead be on how to use the revenue created from the technology to help those in vulnerable regions prepare for the changes ahead, the report said.
Business leaders should not hesitate to seek technological solutions to business challenges to remain competitive in their field, the report noted. However, they should seek buy-in from their workforce when making technology investments, and communicate their robot-related intentions directly. This also means investing in training and education programs along with robotics, the report said.
For more, check out Robotics in business: Everything humans need to know on TechRepublic.
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