Will a Robot Take Your Job? Artificial Intelligence's Impact on the Future of Jobs.
“All you have to do is type in ‘YouTube robot fail,’ says Chou, CEO of Chicago-based AI startup Catalytic.
Here, we’ll make it easier: click to see robots fail.
And even though they’re getting smarter all the time and serving industry in novel ways, Chou is firm in his belief that “we’re pretty far from ‘Terminator.’” In other words, artificial general intelligence — the human-like stuff.
Don’t misunderstand, though; it isn’t that the machines aren’t rising. It’s that they’re rising much more slowly than some of the more breathless media coverage might have you believe — which is great news for most of those who think robots and other AI-powered technology will soon steal their jobs. Most of being the operative words.
AI Will Replace Some Jobs
Will Artificial Intelligence (AI) Replace Jobs?
The consensus among many experts is that a number of professions will be totally automated in the next five to 10 years. A group of senior-level tech executives who comprise the Forbes Technology Council named 13, including insurance underwriting, warehouse and manufacturing jobs, customer service, research and data entry, long haul trucking and a somewhat disconcertingly broad category titled “Any Tasks That Can Be Learned.”
In an essay posted on Medium, AI guru Kai-Fu Lee — CEO of Sinovation Ventures and author of the 2018 book “AI Superpowers: China, Silicon Valley, and the New World Order” — posits that 50% of all jobs will be automated by AI inside of 15 years.
How Many Jobs Will AI Replace?
“Accountants, factory workers, truckers, paralegals, and radiologists — just to name a few — will be confronted by a disruption akin to that faced by farmers during the Industrial Revolution,” he wrote. “As research suggests, the pace in which AI will replace jobs will only accelerate, impacting the highly trained and poorly educated alike.”
And according to a recent story in Becker’s Hospital Review, AI will take over certain healthcare tasks related to revenue cycle management.
Considering those developments and predictions, and based on multiple studies — by the McKinsey Global Institute, Oxford University and the U.S. Bureau of Labor Statistics, among others — there is massive and unavoidable change afoot.
Theories abound on the nature of that change. And many of them, you might be pleased to learn, are neither gloomy nor doomy.
Artificial Intelligence Needs Human Ingenuity
Among AI’s biggest boons, many experts believe, is its ability to save humans from having to perform tedious repetitive tasks that are part of their overall duties so they’re free to focus on more complex and rewarding projects — or just take some much needed time off.
“There’s always a concern that technology is displacing this current body of workers or tasks, and that’s true,” Chou says. “But what always happens is that work, and that output, gets redirected to things that are much more productive.”
Some think increased productivity and efficiency might even shorten the work week. Which seems good in theory but comes with its own set of issues. Namely: how will pay and benefits be affected? And who reaps the bulk of monetary rewards? Companies? Workers? The government? Those remain unanswered questions.
“Up to this point, technology has created more work because it’s another thing you have to deal with,” says Justin Adams, formerly CEO at Digitize.AI and a vice president at its new Chicago-based parent company Waystar. “But I think there’s an inflection point where certain AI will get to a place where that actually flips.”
But Chou says that in order to facilitate technology adoption so it reduces workloads rather than increases them, you need people — lots.
“The more technology encompasses and the more we demand of technology, the more people are involved in doing that,” he says.
Chou cites video games as a good example. Back in the “DOS days,” he says, all it took was one hyper-dedicated “rogue” and six or so months of toil to create a game that could be disseminated as shareware. Now it takes a high-tech village to produce what Chou characterizes as a “movie studio-like undertaking” requiring voice talent, designer, sophisticated physics and a multi-million-dollar budget.
“The number of people that are necessary to deliver better and better technology grows massively,” he says. “So you move from worrying about the impact of high technology to actually helping to create the technology. When you look at AI, there's this nonstop need for training, for data, for maintenance, for taking care of all the exceptions that are happening. How do we monitor AI? How do we train it? How do we make sure that AI's not running amok? Those are all going to become new jobs.”
AI as Job Creator: A Different Kind of Work
Even now, armies of people around the world are involved in the development of AI. Per a recent New York Times story on the subject, “A.I. researchers hope they can build systems that can learn from smaller amounts of data. But for the foreseeable future, human labor is essential.”
Gigaom CEO Byron Reese has a similar, if more hyperbolic, take on how AI will affect human labor. As he opined in a recent essay, AI will be “the greatest job engine the world has ever seen.”
“In fact,” Reese wrote, “the BLS [Bureau of Labor Statistics] forecasts faster-than-average job growth in many occupations that AI is expected to impact: accountants, forensic scientists, geological technicians, technical writers, MRI operators, dietitians, financial specialists, web developers, loan officers, medical secretaries, and customer service representatives, to name a very few. These fields will not experience job growth in spite of AI, but through it.
“But just as with the internet,” he added, “the real gains in jobs will come from places where our imaginations cannot yet take us."
"The real gains in jobs will come from places where our imaginations cannot yet take us."
Chris Nicholson, CEO of the San Francisco-based machine learning company Skymind.AI, shares a similar view rooted in even more distant history.
“Everybody uses this analogy, but when the Industrial Revolution came, a certain kind of job disappeared,” he says. “But many jobs, and many [new] jobs, were created. So when you think about, say, England before and after the Industrial Revolution, it wasn’t a poorer place where there was less work. There was a lot more work, but it was a different kind of work.”
As part of a Ted Talk he gave in the Spring of 2017, futurist Martin Ford addressed the issue by harkening to the so-called Triple Revolution report that was assembled by a group of brainiacs (a pair of Nobel laureates among them) and presented to President Lyndon Johnson in early 1964. The report argued, in Ford’s telling, “that the U.S. was on the brink of economic and social upheaval because industrial automation was going to put millions of people out of work.”
That was more than a half century ago, he noted, “and of course that hasn’t really happened. And that’s been the story again and again. This alarm has been raised repeatedly, but it’s always a false alarm. And because it’s been a false alarm, it’s led to a very conventional way of thinking about this” — thinking which holds that technology “may devastate entire industries” and “wipe out whole occupations and types of work.” Nonetheless, he continued, “progress is going to lead to entirely new things” — new industries with new job opportunities “that today we can’t really even imagine.”
In a related discussion, Nicholson mentions a 2013 essay by American anthropologist and “anarchist activist” David Graeber titled “On the Phenomenon of Bullshit Jobs: A Work Rant.” Aside from his grumbling about the proliferation of “pointless” professions (the titular “bullshit jobs”), Graeber cites a then-recent study in which automation-spurred job loss in industry and farming coincided with the tripling of opportunities in other sectors ranging from professional and managerial to clerical, sales and service.
It remains to be seen whether the forthcoming crop of AI-spawned jobs necessitated by the introduction of as-yet-undetermined products and services will provoke similar ire. But one thing’s for sure: when it comes to work, humans will be just as necessary as they’ve always been, only in different ways. In many of the same ways, too.
“I feel like there’s this overwhelming sense that as we get more value from computers and AI, people become less important,” says Dan Platt, a technical product manager at Chicago-based AI company Narrative Science. “But I don’t see it that way. For the foreseeable and unforeseeable future, you will need contractors and plumbers and electricians and window installers — all these jobs that are immensely important and that the world does not operate without.”
Lee, too, is certain that many jobs remain safe from AI obsolescence. Namely, those that require creation, conceptualization, complex strategic planning management, precise hand-eye coordination, dealing with “unknown and unstructured spaces” and feeling or interacting “with empathy and compassion.” His full list of AI-proof professions includes psychiatry, physical therapy, medical care, AI-related research and engineering (duh), teaching, criminal defense law, computer science and engineering (again, duh), science, management and fiction writing. Rest easy, J.K. Rowling.
AI in the Workplace: Realistically Preparing for Impact
Earlier this summer, Amazon — whose warehouses buzz with robots and will be increasingly automated in years to come — announced that it would retrain a third of its 300,000-strong U.S. workforce to the tune of $700 million. Participation is voluntary in a program the company calls “Upskilling 2025,” which is designed to teach employees skills they can apply to work in technical roles inside or outside of Amazon.
More cynical observers might chalk that up to an expensive public relations campaign in light of less-than-flattering reports about how the company allegedly treats its workers. Besides that, Chou says, it’s infeasible. Why not simply make technology that’s more adaptable to more people, he wonders, so the learning curve is much lower? Retraining warehouse workers to be, say, engineers is completely unrealistic. Which isn’t to say there’s no value in additional education.
“I think that we should be trying to get people to understand a little bit about a lot of things so the jump is not very large and the opportunities come,” Platt says. “You're not going to train everybody to write in Python, but if you have people that are trained to understand the basics of engineering, or how things work, their chances [of not being displaced] are a lot higher.”
For Nicholson, surviving and thriving in an increasingly AI-powered world requires a multi-pronged approach. First and foremost, he advises, “Avoid bullshit jobs. If you’re bored in your job, it’s probably a bullshit job and the machines will probably eat it.”
“I think that we should be trying to get people to understand a little bit about a lot of things so the jump is not very large and the opportunities come."
Beyond that, his practical recommendations are surprisingly tech-less — even, you might say, quaint. And they can be summed up in two words: basic skills. Like, for instance, solid verbal and written communication: Listening, reading emotions, asking questions, writing clearly and structuring cogent arguments devoid of ambiguity.
“That's all very important,” he says, “and it's also very hard for machines to do. Barring a nuclear holocaust, there will be no lack of humans who need to be communicated with.”
Some math skills are crucial, too. Chiefly, deep knowledge of the so-called Riemann Hypothesis, a conjecture that the Riemann zeta function has its zeros only at the negative even integers and complex numbers with real part 1/2. Just kidding (thanks, Wikipedia). But it’s a good idea, Nicholson says, to cultivate a decent understanding of statistical concepts, calculus and algebraic linear regression in order to comprehend the “output of AI algorithms.” Arming oneself with that sort of foundational knowledge is key to “being able to adapt.” And in these tech-y times, adaptation has no patience for slow pokes.
“People like to compare AI to electricity,” Chou says. “And I actually agree with that analogy. But electricity took one or two generations to go from idea to widespread adoption, whereas today we’re seeing the impact of technology occur much faster. And so the rate of fundamental society change is increasing, and it’s taking a toll faster than people are ready and able to adapt.”
But in order to survive and thrive, they must. And so, while big change is coming, a little advance planning — by workers who stand to be replaced and the companies that employ them — goes a long way.
In short, stop fretting and start acting.
“There’s no doubt that the AI revolution will require re-adjustments and a great deal of sacrifice,” Lee wrote, “but despairing rather than preparing for what’s to come is unproductive and, perhaps, even reckless. We must remember that our human knack for compassion and empathy is going to be a valuable asset in the future workforce, and that jobs hinged on care, creativity and education will remain vital to our society.”