Robots Will NOT Steal Our Jobs, Business Analysts ShowDoomsayers typically do not factor in all components of the job that a robot would have to replace or all of the true costs of trying, they say
At Fast Company, data analyst Jeffrey Funk and business prof Gary N. Smith dispute the claim that robots are coming for all our jobs. They point to a history of overblown claims:
In 1965, Herbert Simon, who would later be awarded the Nobel Prize in Economics and the Turing Award (the “Nobel Prize of computing”), predicted that “machines will be capable, within 20 years, of doing any work a man can do.” In 1970, Marvin Minsky, who also received the Turing Award, predicted that, “in from three to eight years we will have a machine with the general intelligence of an average human being.”
The implications for jobs were ominous, but robotic-takeover predictions have been in the air for a hundred years, ranging from Karel Čapek’s 1920 play R.U.R. (Rossum’s Universal Robots) to Daniel Susskind’s 2020 award-winning book, A World Without Work. Add in Elon Musk, who always seems to have something to say: “What’s going to happen is robots will be able to do everything better than us . . . all of us. . . . When I say everything—the robots will be able to do everything, bar nothing.” )Jeffrey Funk, Gary N. Smith, “Why our fears of job-killing robots are overblown” at Fast Company (July 21, 2021)
Even today (2021), one research group that Funk and Smith noted concludes that surgeons would more likely be replaced by AI than meat slaughterers. How likely is that?
By now, we should all be suspicious. Funk and Smith go on to point out that doomsayers typically don’t notice that many jobs have components that can be automated but others that can’t be. That would apply to, say, law, medicine, accounting, career advice, fashion design, hairdressing, interior design, creative writing and many other tasks.
As they put it, “you may be in for a surprise if you trust a robot to cut your hair simply because it can open and close scissors.” Generally, computing isn’t creativity and there is more to understanding a person’s “look” than just opening and closing scissors.
As a result, the hype we hear is often at odds with what is happening. Robots, for example, have difficulty sewing a T shirt. On the other hand, some of it is true: Better not plan your career around driving a delivery van. Under some circumstances, robots may be able to do that.
Business prof Jay Richards, author of The Human Advantage: The Future of American Work in an Age of Smart Machines, offered a career choice perspective in a Walter Bradley Center panel discussion (2019),
Now, the bad news is that lots of jobs do disappear, and so I actually agree that any job that can be automated is going to get automated. That’s a really good rule of thumb. This isn’t just manual labor. If you’re working in a factory and you’re doing something really simple and repetitive, that’s going to disappear really quickly. If you’re doing something in an office that’s really, really repetitive, that’s just simple number crunching, that could very well be replaced.
If you’re doing complicated things with your body that any three-year-old can do, we don’t have robots that can do that. So a carpenter or a painter or a welder, there are between five and seven million skilled trade jobs that are not filled right now because people aren’t being trained to do that. So we’re not going to have a robot housekeeper anytime soon. That’s not going to happen. What’s going to happen is all the things that can be reduced to algorithms are going to be.
But that the pace of change is so quick that unlike the change from the agricultural to the industrial economy took place over 150 years, we have entirely new industries come into existence and then become obsolete in five or 10 years. So that means we have to constantly be teaching ourselves and training ourselves with things.
So if whatever we are doing cannot be reduced to a calculation, we probably can’t be replaced by programs or robots.
You may also wish to read: Failed prophecies of the big “AI takeover” come at a cost. Like IBM Watson in medicine, they don’t just fail; they take time, money, and energy from more promising digital innovations. Business profs Jeffrey Funk and Gary Smith compare the costs vs. benefits of AI hype vs. small innovations that change the world.