AI May Not Kill Your Job—Just Change It

Don't fear the robots, according to a report from MIT and IBM. Worry about algorithms replacing any task that can be automated. 
A porche gets sprayed by robot arms in a factory
Photograph: Tobias Schwarz/Reuters

Martin Fleming doesn’t think robots are coming to take your jobs. The chief economist at IBM, Fleming says those worries aren’t backed up by the data. “It’s really nonsense,” he says. A new paper from MIT and IBM’s Watson AI Lab shows that for most of us, the automation revolution probably won’t mean physical robots replacing human workers. Instead, it will come from algorithms. And while we won’t all lose our jobs, those jobs will change, thanks to artificial intelligence and machine learning.

Fleming and a team of researchers analyzed 170 million online US job listings, collected by the job analytics firm Burning Glass Technologies, that were posted between 2010 and 2017. They found that, on average, tasks such as scheduling or credential validation, which could be performed by AI, appeared less frequently in the job listings in the more recent years. The recent listings also included more “soft skills” requirements like creativity, common sense, and judgment. Fleming says this shows that work is being resorted. AI is taking over more easily automated tasks and workers are being asked to do things that machines can’t do.

If you’re in sales, for example, you’ll spend less time figuring out the ideal price for your product, because an algorithm can determine the optimal price to maximize profits. Instead, you might spend more time managing customers or designing attractive marketing materials or websites.

In the study, researchers divided the listings into three groups based on the advertised pay, then examined how different tasks were being valued. What they found is that how we value tasks may be starting to change.

Design skills, for example, were in particularly high demand and increased the most across wage brackets. Within personal care and services occupations—which generally are low-wage—pay for jobs that included design tasks, such as presentation design or digital design, increased by an average of $12,000 over the study period, after inflation. The same can be said of higher wage earners in business and finance who have deep industry expertise that can’t yet be matched by AI. Their wages went up more than $6,000 annually.

Some low-wage occupations like home health care, hairstyling, or fitness training are insulated from the impact of AI because those skills are hard to automate. But middle-wage earners are starting to feel the squeeze. Their wages are still rising, but after adjusting for the shifts in tasks for those jobs, the report found, those wages weren’t growing as quickly as low-wage and high-wage jobs. In some industries, like manufacturing and production, wages actually decreased. There are also fewer middle-wage jobs. Some are getting simpler and being replaced by low-wage jobs. Others now require more skills and are becoming high wage.

Fleming is optimistic about what AI tools can do for work and for workers. Just as automation made factories more efficient, AI can help white-collar workers be more productive. The more productive they are, the more value they add to their companies. And the better those companies do, the higher wages get. “There will be some jobs lost,” he says. “But on balance, more jobs will be created both in the US and worldwide.” While some middle-wage jobs are disappearing, others are popping up in industries like logistics and health care, he says.

As AI starts to take over more tasks, and the middle-wage jobs start to change, the skills we associate with those middle-class jobs have to change too. “I think that it’s rational to be optimistic,” says Richard Reeves, director of the Future of the Middle Class Initiative at the Brookings Institution. “But I don’t think that we should be complacent. It won’t just automatically be OK.”

The report says these changes are happening relatively slowly, giving workers time to adjust. But Reeves points out that while these changes may seem incremental now, they are happening faster than they used to. AI has been an academic project since the 1950s. It remained a niche concept until 2012, when tests showed neural networks could make speech and image recognition more accurate. Now we use it to complete emails, analyze surveillance footage, and decide prison sentencing. The IBM and MIT researchers used it to help sort through all the data they analyzed for this paper.

That fast adoption means that workers are watching their jobs change. We need a way to help people adjust from the jobs they used to have to the jobs that are now available. “Our optimism actually is rather contingent on our actions, on actually making good on our promise to reskill,” says Reeves. “We are rewiring our economy but we haven’t rewired our training and education programs.”

Reeves wants to see more apprenticeships or “returnships” for workers who need to learn new skills. Colleges could include more programming and scholarship money for adult learners. Or we could change our credentialing system so that credits are more easily transferable or can be accrued from work experience. Then, workers would be able to take a few classes at different institutions and, over time, combine those credits to get a certification or diploma. That could help cut the cost of education and allow students to leave college, work for a time, and then come back when they want to acquire new or different skills or finish their degree.

There’s also the question of whether employers understand the skills their jobs require. This paper used job listings to measure how tasks and jobs are evolving, but job posts aren’t always indicative of what a job entails. “Job listings tell you a lot about what an organization or team thinks it wants, but not actually what it needs,” says Madeleine Clare Elish, a researcher at Data & Society who studies AI and work. She gives the example of someone who works alongside self-checkout machines. The job listings may include tasks associated with helping people check out or managing the stations, but what workers actually do often includes fixing the machines when they break down or soothing angry customers when the machines don’t work properly.

The paper’s findings are inline with work from the McKinsey Global Institute and The Partnership on AI.

For Reeves, of Brookings, the study sheds light on the jobs of the future—what they will involve, how much they’ll pay, and how satisfied workers will be. AI might increase productivity and income, but it might have other impacts that can’t be measured in dollars and cents. “The real question, I think, is will machines help people flourish in the workplace?” Reeves says. He’s guardedly optimistic that AI could ultimately help people create jobs that are more fulfilling and enjoyable. But that’s a future we have to actively work toward. The magic of the market won’t automatically lead us there.


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