The rise of artificial intelligence (AI) and automation sounded alarm bells for many technologists and US workers, fearful that these technological advancements would steal jobs. Soon after, we saw a period of correcting that assumption, with new information reassuring workers that humans would work with robots, and not be replaced by them.
The reality will likely be somewhere in between this dystopia and utopia, according to a Thursday report from the Metropolitan Policy Program at the Brookings Institution. The report uses government and private data to develop both backward- and forward-looking analyses of the impacts on automation over the years 1980 to 2016 and 2016 to 2030 across about 800 occupations.
SEE: IT leader’s guide to the future of artificial intelligence (Tech Pro Research)
While automation and AI will affect tasks for virtually every job in the future, as IBM’s Ginni Rometty has posited, the impacts on workers will vary greatly, the report found. Only 25% of US jobs are highly susceptible to automation, meaning that more than 70% of their current tasks are at risk of being replaced by a robot. However, this figure represents 36 million jobs, including positions in food preparation, production, office and administrative support, and transportation.
“That population is going to need to upskill, reskill or change jobs fast,” Mark Muro, a senior fellow at Brookings and lead author of the report, told CBS News. The timeline for the changes could be “a few years or it could be two decades,” he added.
Another 36% of US workers (52 million) will experience medium exposure to automation, while 39% (57 million workers) will experience low exposure, according to the report.
The most secure jobs include a broad set of positions, ranging from creative professional and technical roles with high educational requirements to low-paying personal care and domestic service work, the report found. All of these jobs are characterized by non-routine activities, or the need for social and emotional intelligence, it added.
In the near future, automation will impact low-paying roles first, the report found. The average automation potential for occupations requiring a bachelor’s degree is just 24%, while that for jobs that don’t require the degree is 55%.
“Given this, better-educated, higher paid earners for the most part will continue to face lower automation threats based on current task content—though that could change as AI begins to put pressure on some higher-wage ‘non-routine’ jobs,” according to the report.
The report also examined automation by region, and found that smaller, more rural communities will face the greatest risks. Automation will be most disruptive in the Heartland states, due to the number of jobs in manufacturing and agriculture in that area.
To manage the impact of AI on the workplace, business and federal, state, and local leaders should take the following five steps, according to the report:
1. Embrace growth and technology
– Government must work with the private sector to embrace growth and technology to keep productivity and living standards high and maintain or increase hiring
2. Promote a constant learning mindset
– Invest in reskilling incumbent workers
– Expand accelerated learning and
– Make skill development more financially
– Align and expand traditional education
– Foster uniquely human qualities
3. Facilitate smoother adjustment
– Create a Universal Adjustment Benefit to
support all displaced workers
– Maximize hiring through a subsidized
4. Reduce hardships for workers who are
– Reform and expand income supports for
workers in low-paying jobs
– Reduce financial volatility for workers in
5. Mitigate harsh local impacts
– Future-proof vulnerable regional
– Expand support for community
The big takeaways for tech leaders:
- 25% of US jobs, representing 36 million workers, are highly susceptible to automation. — Brookings Institution, 2019
- In the near term, the jobs at least risk of automation are those characterized by non-routine activities, or the need for social and emotional intelligence. — Brookings Institution, 2019