Hiring's physics problem.

Policymakers across the spectrum are hoping employers will change their hiring quite a bit. They’re generally not.

Why?

Physics.

I spend a lot of time noodling on how to solve for a lot of challenges in the American labor market, the unique moment seizing it, and the aspirational shift in hiring that just isn’t happening yet. The other day that led me to think about physics and Newton’s Laws of Motion. Obviously.

Even if you didn’t know the name for it, you’ve probably heard the Laws of Motion many, many times in the course of your life. They go like this, per NASA:

For a second, let’s put a pin in the core mechanics of the universe to talk about the issues that describe where we are in workforce development and the labor market in the United States.

I hear from a lot of different people that they think hiring is broken. Employers don’t think they’re seeing enough of the talent they need and it takes too long to find people who are good enough to maybe work out. In the sector we typically label as “white collar,” there’s growing disenchantment with the college degree as a way of identifying talent. Some of it is logical (why do you need someone to have a four-year degree in a job that doesn’t really need one?). Some of it is annoyance at college graduates for expecting better working conditions (which is interesting). Some of it is political theatre (I’ve considered swapping “college” for “witchcraft” in some recent political messaging to see if it holds up conceptually).

I’m honestly shocked when I hear about someone out of college finding a job in fewer than three months or three digits’ worth of applications. The idea of AI is a factor—investors want to believe it can eliminate tons of overhead and make profits soar—but my read of the research is that The Robots are not taking all our jobs. Not yet, anyway.

Yet, many employers haven’t shown signs of an actual downshift away from hiring people with degrees, despite a lot of complaining about college grads and stripping off degree requirements. Skills-first hiring—meaning hiring based on skills verified during the application process, as opposed to hiring people based on degrees and skills they might have—does require employers to do some work, but at this stage, we’ve got at least a decade’s worth of research and strategy to help guide the way. It’s just not happening as much as many of us would hope.

We’re also well into the second decade of apprenticeship seeming like a great and more precise alternative to college for certain employers—or at least a good way of getting more people into (maybe) automation-safe jobs and retraining those who are in less automation-safe jobs. Registered Apprenticeship growth has been good—it’s hard to say a nearly 80 percent increase over the past decade is anything but—yet it’s not the overwhelming adoption we probably need if AI does slice away big chunks of the American labor market.

Here’s something employers, employer groups, and workforce professionals have noted to me from time to time: some employers just don’t want to do apprenticeship. The reasons may not be good, or even accurate, but the resistance is there because it’s something different than what they always have done.

Or, to sum all of this up: a lot of employers—who tend to control most of the hiring, I’ve noticed—see the challenges in hiring, and a lot of them even see value in policymakers’ usual solutions for changing hiring. But employers aren’t really changing hiring for the better, and the same old problems likely are getting worse because the idea of AI firing everybody remains real attractive to investors with limited regard for that prospect’s downsides.

Or, to put it in one other way: we’re dealing with the workforce version of the Laws of Motion.

Objects at rest will stay at rest until acted upon. Employers complain a lot about how they find talent. They aren’t changing how they hire. They won’t until they encounter a force that shifts behavior, and they haven’t met it yet.

Objects in motion will stay in motion at the same speed and the same direction until acted upon, and the acceleration of an object depends in part on the amount of force applied. Investors have put too much money into the dream of AI-related job cuts that lead to easy profits. Employers, especially public ones, are being pressed to move faster in that direction by a big honkin’ pile of money that’s created a lot of force.

Policymakers and political leaders are probably the best ones to deliver that force—but trying to change any of this is going to prompt an equal and opposite reaction from employers.

Which political leaders and policymakers tend to not be very good at handling…