The backstory: The last wave of technological disruption — the IT revolution of the 1980s — created new jobs, but the bulk of the job and wage gains were on the high and low ends of the labor market. Scores of middle-wage, middle-skill jobs in manufacturing, largely in the middle of the country, were automated away or sent abroad.
Now, the new wave of automation and AI is projected to hit high- and low-paying jobs in addition to middle-income jobs, says Marina Gorbis, executive director of the Institute for the Future.
The next crop of vulnerable jobs — which include middle-wage occupations like trucking and administrative office work as well as lower-wage jobs like waiting tables and farming — are scattered all over the country, but the highest concentration is once again in the heartland, per a new report from the Brookings Institution.
By the numbers:James Bessen and James Kossuth at Harvard Business Review:
But the extent of the hit to middle America is even clearer when zooming in to the county level.
- A quarter of all jobs across the U.S. have high chance of being wiped out by automation.
- The five states with the highest share of at-risk jobs are Indiana (29%), Kentucky (29%), South Dakota (28%), Arkansas (28%), and Iowa (28%) — all of which went for President Trump in 2016.
- Compare that to the bottom five: New York (20%), Maryland (20%), Massachusetts (21%), Connecticut (22%) and New Mexico (22%), all of which went for Hillary Clinton.
- For example, in Jerauld County, South Dakota, 53% of jobs are hanging in the balance.
- 48% of jobs are vulnerable in Scott County, Miss.; 48% in Dakota County, Neb.; and 46% in Colfax County, Neb.
New AI and robotics technologies are increasingly automating work tasks. How much of a threat does automation pose to workers? A new study by one of us (James Bessen), along with Maarten Goos, Anna Salomons, and Wiljan van den Berge, provides the first large-scale quantitative evidence of how automation affects individual workers, using government data from 2000-2016 for 36,000 firms in the Netherlands, covering about 5 million workers each year.
We found that automation does indeed affect many workers. Each year, about 9% of the workers in the sample are employed at firms that make major investments in automation. Yet relatively few workers are adversely affected. Only about 2% of tenured workers at automating firms leave the year of the automation event as a result of automation; after five years, 8.5% will have left, cumulatively. (We can’t differentiate between those who choose to leave and those who are let go or fired.)
Nevertheless, those who do leave suffer significant economic costs, largely due to spells of unemployment. This affects both their economic prospects and their overall wellbeing. And though welfare programs like unemployment insurance are often framed as the way to address these costs, our data confirm that they don’t nearly make up for the income that workers lose.
Surprisingly, this burden falls more frequently on highly-educated and highly-paid workers. Contrary to conventional wisdom, they are more likely to leave as a result of automation, although they also seem to find new jobs faster. In other words, highly-paid workers are more commonly affected, but the effects are more severe for less well-paid workers.