We Just Don’t Know the Impact AI Will Have on Jobs

I like to think I know HR and workforce issues pretty well. I’ve spent a large part of my life researching them. But the more I read about these new technologies, the more I think we just don’t know the impact AI will have on jobs. We’re going to have to learn as we go.

Driverless Cars Are Coming, Till They’re Not, Or Are They?

Just a few years ago, the standard thinking was that a lot of blue-collar jobs would soon disappear due to the advent of driverless vehicles. But it turns out that driving is a lot harder than it looks and AIs just can’t handle the “edge cases” well. Sure, they can handle 98% of driving, but they can’t cope with the unexpected. For example, there’s the case of the self-driving car in San Francisco that didn’t obey an officer’s command to halt when it was in an area where firefighters were working. The cop smashed in the car’s windshield to stop it. That’s the kind of edge case that goes viral.

So, all those ride-sharing and taxi jobs are safe, right? That’s become the new conventional wisdom. For now.

“The white-collar employee’s future is more threatened than the Uber driver, because we still don’t have self-driving cars, but AI can certainly write reports,” Martin Ford, author of Rule of the Robots: How Artificial Intelligence Will Transform Everything, told the BBC.

Well, pardon my skepticism ,Mr. Ford, but I doubt you really know. Right now, there are hundreds of driverless cars in California, many in San Francisco. In fact, there are over 1,400 such vehicles registered in that state, up from just 900 last November, according to the Department of Motor Vehicles. In some parts of San Francisco, these vehicles have become a pretty common sight.

Now, maybe this surge is temporary. Maybe the public will turn against these cars, especially if there’s some well-publicized gruesome accident costing multiple lives. Or, maybe these cars will start appearing in city centers all over California and then beyond. If someone can pay a fraction of a price of an Uber for a ride in a driverless car, you can bet a lot of people will be willing to give them a try.

The point is, we just don’t know for sure. Mr. Ford is wrong in that we do have self-driving cars, we just don’t have a lot of them yet. The future is, as they say, already here but still unevenly distributed. Things could change…quickly….or not.

Now White-Collar Jobs Are Expected to Evaporate, But Will They?

The new conventional wisdom is that blue-collar jobs are safe while white-collar jobs are on the chopping block. Are all those software development jobs, for example, going out the window because the new generative AIs are pretty good at writing computer code?

Maybe. There are stories of programmers who are able to boost their coding productivity by three times or more as they leverage ChatGPT or other AIs. Let’s assume for a minute that the productivity claim is true. Does it mean that 2 out of 3 programming jobs are now expendable?

Could be. Or, it may be there’s a whole lot of development work out there that companies couldn’t get to because they just couldn’t afford to hire enough developers. If these professionals are three times more productive, then companies stand to earn more money per worker more quickly and can afford to hire more programmers.

Consider the Case of the ATM

Consider the case of the bank teller. For a while, the conventional wisdom was that automated teller machines, or ATMs, would cast bank teller jobs into the dustbin of history. But that’s not what happened. Since 2000, in fact, teller jobs have grown a little faster than the the labor force as a whole. The impact of the ATM machine was not to destroy teller jobs but to increase them.

James Pethokoukis writes, “What happened? Well, the average bank branch in an urban area required about 21 tellers. That was cut because of the ATM machine to about 13 tellers. But that meant it was cheaper to operate a branch. Well, banks wanted, in part because of deregulation [but also] for basic marketing reasons, to increase the number of branch offices. And when it became cheaper to do so, demand for branch offices increased. And as a result, demand for bank tellers increased.”

Tech Wiped Out Most Farm Jobs, Right?

Now let’s consider the job of the agricultural worker. Farming jobs have become so technologically productive that they are practically the poster child for productive-tech-kills-jobs idea. And, it’s true. We do have many fewer farmers per capita today than we did before the industrial revolution.


Guess what the top role is expected to be over the next five years in terms of net job growth?

If you’re sensing a theme here, then you’ve probably guessed it: agricultural equipment operators. The World Economic Forum states, “Surveys conducted for the Future of Jobs Report suggest that the highest job growth in 2023-2027 will be for agricultural equipment operators, for drivers of heavy trucks and buses, and for vocational education teachers. Mechanics and machinery repairers follow in fourth place.”

But Surely the Writers Are Doomed!

Now let’s talk about the most obvious victims of large language model AIs: journalists and other writers. Why should anyone hire a writer when they can get generative AI to write virtually for free?

Good question. Maybe there will be a vast reduction in such jobs. Why not? After all, journalism jobs have been on the decline for decades. The Center on Education and the Workforce reports, “Projected job losses for journalists are primarily due to newspaper downsizing and closures….[O]nly about 15% of journalism majors become editors or news analysts, reporters, and correspondents early in their careers.”

Now ChatGPT et al. will finish the job of killing off journalism jobs for good. Right?

It could happen. On the other hand, what if all these small-town newspapers that have closed over the years because the Internet nuked their business models suddenly become modestly profitable again because the AIs can inexpensively produce copy for online (or even print!) editions? If that happens, those papers will still need some actual journalists to attend the townhall meetings, investigate important local stories via interviews, track down leads, etc.

It’s possible–though I don’t know how possible–that these new technologies will actually lead to more journalism jobs in the same way that more ATMs were correlated with more bank teller jobs. High productivity is like that. It can be stochastic in its effect, so you can’t always anticipate the economic outcomes of rising productivity rates.

Don’t Pretend You’re Certain About Anything

Look, I’m not saying we shouldn’t try to forecast the future or that all predictions are doomed to be wrong. But, as Niels Bohr reportedly said to the legendary Yogi Berra, “It is difficult to make predictions, especially about the future.” 

Sometimes predictions that seem obvious today can prove to be dead wrong, and there will always be some future events capable of surprising us.

So, stay humble, you futurists, forecasters and would-be guru types. None of us really knows how any of this is going to turn out. And that’s okay. We’ll make our best guesses and then figure it out as we go.