Blaming the Machine

Something has shifted in how layoffs are announced this year. By the count of Challenger, Gray & Christmas, the outplacement firm that tracks these things, AI has become one of the most frequently cited reasons in US layoff announcements - for several months running, by some readings the single most cited one.

I want to be careful here, because this is a subject where people get hurt, and where a lot of commentary is careless.

Stated reasons are not the same as reasons

Challenger counts what companies say. That’s useful data. But a company’s announced reason for a layoff is also a story, told to investors, to the press, and to the employees who remain. And “we’re restructuring around AI” is, right now, a very good story. It sounds forward-looking rather than desperate. It suggests efficiency rather than mistakes. It tells the market the company is modern.

Some of these layoffs genuinely are about AI. Work that used to require people now doesn’t, and pretending otherwise helps nobody.

But some are the ordinary kind - over-hiring, a weak quarter, a strategy that didn’t work, a need to cut costs before the next earnings call - wearing new clothes. I’ve lived through enough cycles to recognize the pattern. In 2022 it was “the end of free money.” Before that, “efficiency.” The reasons change their names. The pain is the same.

Why it matters which is which

It matters because the story we tell about why something happened shapes what we do next.

If a company believes its own story - that it can replace people with AI - but the real reason was something else, it may cut the wrong people. Often it’s the experienced ones who held quiet knowledge nobody had written down. Months later, things start to break in ways nobody can explain.

And it matters for the people who were let go. Being told you were replaced by a machine is a particular kind of wound. It suggests you were obsolete, when often you were simply on the wrong line of a spreadsheet during a hard quarter. If that’s you: please don’t take the press release as a verdict on your worth. It was written for investors, not for you.

A word to leaders

If you’re the one making these decisions, I’d ask for one thing: honesty, first with yourself.

Is this genuinely work that AI now does well, which you’ve tested and measured? Or is AI a convenient explanation for a decision you’d have made anyway? Both can be legitimate business choices. But only one of them is true, and your organization will be shaped by which one you believe.

And whatever the reason, the way you do it matters. People remember how they were treated on the way out, and so does everyone who stayed. A calm, honest, generous layoff costs a little more in the short term. A careless one costs trust, which is very expensive to rebuild.

A word to everyone else

The machines are changing work. That’s real, and I’ve written a great deal about it. But I’d encourage some skepticism toward anyone - companies, commentators, or AI labs - whose interests are served by making that change sound faster, bigger, or more inevitable than it is.

There’s an old principle in Jewish ethics against geneivat da’at, literally “stealing the mind”: creating a false impression in someone else’s understanding, even without saying anything technically untrue. A lot of what’s said about AI and jobs right now comes close to that line, in both directions. The antidote is the same as always: look at what’s actually happening, not at what people say is happening.

The machine gets blamed for a lot. Sometimes it did it. Sometimes it’s just a good story.