Tech CEOs and politicians alike have issued grave warnings about the capability of automation, including AI, to replace large swaths of our current workforce. But the people who actually study this for a living — economists — have very different ideas about just how large the scale of that automation will be
For example, researchers at Citibank and the University of Oxford estimated that 57 percent of jobs in OECD countries — an international group of 36 nations including the U.S. — were at high risk of automation within the next few decades. In another well-cited study, researchers at the OECD calculated only 14 percent of jobs to be at high risk of automation within the same timeline. That’s a big range when you consider this means a difference of hundreds of millions of potential lost jobs in the next few decades.
Of course, technology also has the capability to create new jobs — or just change the nature of the work people are doing — rather than eliminate jobs altogether. But sizing the scope of sheer job loss is an important metric, because for every job lost, a member of the workforce will have to find a new one, oftentimes in an entirely different profession.
Is my job safe? It’s a question we have all asked ourselves at some point, but at no time has it been more relevant than today. With current advancements in robotics and software, the contemporary human workforce seems to be under siege. Some believe that their jobs are untouchable – that automation only affects unskilled labor or factory workers. That is a gross miscalculation. Today, even white-collar jobs are being cut due to technological advancements.
Throughout history, job loss due to technology and automation has always threatened the workforce. Do you know anyone who works as a switchboard operator, elevator operator, toll collector, or projectionist in a movie theater? Yes, jobs come and go, but the trend is widening and accelerating at an alarming rate. The best way to determine if your job is at risk is to have a look at some current statistics and projections.
The Data Isn’t Good Enough
To model the future, researchers have to start with data from the present — which is not always perfect. Economists do their best to take inventory of all the jobs out there and what tasks they involve, but this list admittedly isn’t exhaustive.
“There’s no assurance in the end that that we’ve captured every aspect of those jobs, so inevitably we might be overlooking some things,” said Carl Benedikt Frey, an economist at the University of Oxford.
It helps to know just how these experts make the predictions to fully understand the room for human error. In the case of the Oxford study, researchers gathered a list of hundreds of occupations and asked a panel of machine learning experts to make their best judgment as to whether or not some of those jobs were likely to be computerized. The researchers weighed in on only 70 out of the about 702 total jobs that they were most confident they could assess.
For the rest of the occupations, McKinsey & Company points out that the researchers used an algorithm that attributed a numerical value to how much each job included tasks that are technology bottlenecks — things like “the ability to come up with unusual or clever ideas” or “persuading others to change their minds or behavior.” But ultimately, even that algorithmic modeling isn’t perfect, because not everybody agrees on just how socially complex any given job is. So while quantitative models can help reduce bias, they don’t eliminate it completely, and that can trickle down into differences in the final results.
For all these reasons, some academics prefer not to forecast an exact number of jobs lost in a specific timeframe, but instead focus on the relative percentage of jobs in an economy at risk.
Having Technology Doesn’t Mean It’s Going to Be Used
Even as new groundbreaking tech becomes available, there’s no guarantee that it will be implemented right away. For example, while autonomous-vehicle technology could one day eliminate or change the jobs of the estimated five million workers in the U.S. who drive professionally, there’s a long road ahead to getting legal clearance to do that.
“The fact that a job can be automated doesn’t mean it will be,” Glenda Quintini, a senior economist at the OECD, told Recode. “There’s a question of implementing, the cost of labor versus technology, and social desirability.”
Take the job of a waiter. A robot may be able to take over some aspects of that job, like taking orders, serving the food or handling payments. But other parts, like dealing with an angry customer, maybe less so. Some studies, such as the OECD report, assess the likelihood of each task within an occupation, while the Oxford studies make an overall assessment of each job.
There’s a debate among academics about which methodology makes more sense. The authors of the OECD report say that the granularity in their approach is more accurate, while the Oxford report authors argue that for most occupations, the detailed tasks don’t matter: As long as technology like AI can do the critical portion of the work, it ultimately has a binary “yes” or “no” capability to be automated.
What the Numbers Show
As analysts sift through recent and historical data, the trends in job losses become evident. This data gives us a good idea as to what jobs will be affected in the near-term. However, attempting to predict the long-term future of our human workforce is where things become tricky, as many of the experts disagree on an accurate timeline. It all comes down to how fast technological advancements in robotics and artificial intelligence (AI) will proceed. In the meantime, whatever future projections the experts come up with, although informative, are no more than educated guesses.
Between 2000 and 2010, the United States lost over five-and-a-half million jobs in the manufacturing sector. Forbes notes that many politicians attribute this massive drain of employment to China ramping up manufacturing operations. However, a study by the Center for Business and Economic Research at Ball State University disagrees. According to this study, 85% of job losses during that period were due to technology and automation.
The remarkable thing about this statistic is the fact that even though there were fewer people in the manufacturing workforce, industrial output grew. In other words, the manufacturing sector became more productive with fewer people.
A projection from the University of Oxford states that almost half of all jobs in the United States will be under pressure from automation in the next several decades. This eye-opening estimate further states that the unskilled, low-paying jobs will be the employment category most at risk. However, it does not say that the higher-level, skilled workers will be completely safe either.
Yet another study put forth by the McKinsey Global Institute goes on to say that 800 million jobs may be lost to automation worldwide. The study focuses on advancements in robotics and AI as the culprit when it comes to human workforce reduction.
If you’re thinking these reports and studies are all doom and gloom, that’s not so. Many of them put a rosy spin on the truly appalling numbers, mentioning that automation will also open up whole new job categories. That may be a silver lining on a dark cloud, but it’s a very thin lining for someone who is on the verge of losing their job to a robot. So, which of us are most at risk?
