If someone tells you they're sure that when artificial intelligence has infiltrated every corner of our working lives there will be plenty of jobs to go around, they are: a) lying, b) a human being, or c) both. Which is to say no single human can be certain what the future of work will look like when AI is as common as a head cold. That said, there are certainly some very knowledgeable human beings putting in a fair amount of time and effort into trying to predict what the future of work and labor will look like in an AI-dominant future.
Exhibit A: Some people who work for a little consulting firm called McKinsey. According to latest McKinsey predictions, "Investments in technology, including AI and automation, could add 20 million to 50 million jobs globally by 2030." However, "calculating job loss is more complicated, according to the firm, because in many cases people won’t lose their jobs outright, but instead will switch occupations."
Exhibit B: Kai-Fu Lee. Lee has worked for Google, Apple, and Microsoft, and now works in venture capital, specializing in AI. What's perhaps most interesting about Lee's predictions about AI and work is that they've been informed less by his rigorous scientific research than by his recent bout with cancer. Which led him to utter this very human statement (that could, incidentally, make a nice screensaver): “Facing death, nobody regretted that they didn’t work hard enough.”
Lee has also said this: "What’s more serious than the loss of jobs is the loss of meaning. Love is what differentiates us from AI.” At least for the moment it does. In any case, Lee believes that when AI starts to take many of the jobs that we do and hold now, we will need to focus on love and compassion, which AI is not so skilled in (yet). And so, "jobs like caretakers, teachers, social workers, and tour guides, in addition to those jobs like research analyst, artist, scientist, and CEO" are safer ones, and ones that, if you believe in Lee's love thesis, would be a good idea to pursue.
Which brings us to Exhibit C: The Apocalyptics. That is, there are many AI experts who present some pretty bleak futures, ones where love and compassion might not do us any good when AI comes gunning for our livelihoods. For these scenarios, you can read/watch what the writer Charlie Brooker has to say. Brooker is the creator of TV's Black Mirror, and most (but not all) Black Mirror episodes paint a rather dismal picture of a future when AI is with us 24/7.
For more bleak views, you can also listen to a prominent philosophy professor from NYU, or to a couple of the richest men on earth.
“I do worry about a scenario where the future is AI and humans are left out of it,” says David Chalmers, a professor of philosophy at New York University. “If the world is taken over by unconscious robots, that would be about as disastrous and bleak a scenario as one could imagine.” Chalmers isn’t alone. Two of the heaviest hitters of the computer age, Bill Gates and Elon Musk, have warned about AIs either destroying the planet in a frenzied pursuit of their own goals or doing away with humans by accident—or not.
Setting aside Matrix-like scenarios for the moment, it seems that most human AI observers and so-called AI experts agree that robots will not take the place of a certain set of jobs in the very near future (the next decade or so). These jobs include the aforementioned caretakers and teachers as well as jobs like nurses and others requiring a high level of empathy, interpersonal skill, and physical dexterity. In addition, there seems to be agreement that AI will create an increased demand for highly skilled tech jobs that mostly exist today as well as new AI-specific jobs that largely don't exist today.
Jobs in high demand today that will conceivably continue to be in high demand through 2029 include programmers, developers, and engineers. Job titles such as software application developer, system software developer, computer system analyst, and computer user support specialist will most likely be ones that employers will look to fill more and more in the coming decade.
With respect to AI research-specific roles, machine-learning engineers and computer-vision engineers (these working on improving robotic vision) will likely continue to be in high demand as well. Firms will likely be looking for plenty of Ph.D. level scientists "who are able to not just build the company’s products but also conduct research that will lead to improvements in future devices."
In fact, AI researchers are now among the most lucrative jobs in the U.S., with top researchers making seven-figure salaries and entry-level and mid-level researchers earning several hundred thousand dollars a year. One reason AI research salaries are so high is "there is a mountain of demand and a trickle of supply,” according to Chris Nicholson, founder and CEO of AI startup Skymind.
Jobs that mostly don't exist today but likely will in large numbers in Tomorrowland include "trainers," "explainers," and "sustainers." These are terms attributed to Paul Daugherty and H. James Wilson, co-authors of Human + Machine: Reimagining Work in the Age of AI, which was published this past March. Daughtery (the Chief Technology and Innovation Officer of Accenture) and Wilson (Managing Director of Information Technology and Business Research at Accenture Research) believe in a somewhat fruitful marriage between AI and the Average Joe. When AI goes mainstream, Daugherty and Wilson believe that millions of new jobs largely nonexistent today will be created.
As for what Daugherty and Wilson mean by "trainers," they mean roles that will help AI act more human, teaching AI compassion and rooting out any prejudice that AI might have picked up during its upbringing (that is, its programming).
For instance, it has been shown that an algorithm used to help judges determine proper sentencing wrongly pegged black defendants as future reoffenders at almost twice the rate as white defendants. White defendants, meanwhile, were mislabeled as low risk more often than black defendants.
"Explainers" act as liaisons between AI and staff as well as between AI and customers. Today, explainers are already employed by some companies, such as the old and massive insurer Guardian Life, where explainers (or "translators") "help employees understand the power of technology in serving clients, as well as understand the gaps in technology and the role of human coaches."
And "sustainers" will be the ones dealing with the regulators. After all, when AI comes gunning for jobs by the millions, governments are going to have a lot problems on their hands, to say the least. Sustainers will make sure all AI is compliant.
All of which is to say there is hope. And there is time. (As mentioned, how much hope and how much time nobody knows.) So, in order to make sure you aren't completely replaceable by hardware and software, you could do one or more of the following right now:
a) learn a new language (not Spanish or Mandarin but Python)
b) go back to school to get your Ph.D. in machine learning (or, if that's too daunting, at least take an online machine learning course or two)
c) improve your creativity, compassion, and empathy (a good place to start with empathy improvement is this podcast)
d) check with your employer to see what sort of retraining they're offering (which is very important since a recent survey of more than 1,000 CEOs found that nearly 75 percent plan to use AI to automate a signicant number of tasks but only 3 percent plan to boost investment in worker training and reskilling programs)
And, if none of the above appeal to you, there is always this:
e) lobby intensely for universal basic income
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