AI Exposure: 29% of Women's Jobs vs 16% of Men's. A Warning, Not a Funeral. Who Captures the Gains?

SPEAKER_1 (0:00)

Surviving AI is a podcast about superintelligence and the people selling you a date for it. Every week, we trace the claim, who measured it, who paid for it, and who collects. Then we ask what it means for the person in your seat. When we get it wrong, we say so out loud. Not doom, not hype. Signal you can act on. That's agency.

Welcome to Surviving Superintelligence. Now, here is the news. Women's jobs are almost twice as likely as men's to be exposed to generative AI, 29 percent against 16 percent, according to the International Labour Organization. That is exposure, not job loss. It is a warning, not a funeral. In the United States, one Brookings analysis counts about 6.1 million workers who are highly exposed and low in adaptive capacity, and about 86 percent of them are women.

Meanwhile, depending on the measure, women are roughly a fifth to a quarter of the technical pipeline that builds AI.

Are women being marginalized or is this data incomplete? Is there a gap between who is being automated and who is doing the automating? So, when the clerical layer shrinks, is this a tide that lifts everyone, including women, or is it a capture play for the people at the top?

Carlo Thompson (1:32)

So the way I read this is that there's something happening here, folks, that I am not 100 percent comfortable with, and I need to ask you a question, right? I need to ask the audience a question. Are you guys happy with what happened at the super intelligence conference or seminar at the White House? Right? This idea that you're going to get safe AI now. So don't worry about it. Keep building data centers, keep frontier models going, get to recursive self-improvement. Are you guys happy about that? We're going to get safety. Does that make you get the warm and fuzzies? Right?

I think that's just part of the story, in my opinion. And we beat the mantra of safety on the show, mostly with human in the loop and mostly with narrow AI. Right? Not super intelligent AI. But if we're going to get the super intelligent AI that's safe, there's another thing that's rumbling in the background. And this is the idea around job loss.

And none of that was resolved with the accord that every CEO of Frontier Model Development signed. None of that was resolved. And based on the news report that Ainsley just read, essentially, women are being marginalized, right? Where they are in more exposed industries than men.

Right? Are we happy about that?

Ainsley, am I reading this wrong or right?

SPEAKER_1 (3:22)

The danger is that we treat this like a brochure problem, where the answer is just a list of new rooms to enter. People are already saying the move is into health care or the care economy.

But that is just swapping one bucket for another. The real question is what you actually carry with you. The durable skills that don't evaporate when the clerical layer does.

Carlo Thompson (3:44)

So that's another good point, right? Because, you know, historically, right, we had this problem before. And I could go on and say that this time is different, but people are going to point me back to the historical data and say, hey, no, no, it happened a couple of times before, right? But before, you had to point somebody at a door to go walk through, to get their next career, their next way to make a living, the next way to put food on their table, okay? I don't have that clear right now. We don't have that cleanly. None of that was discussed in the accord at the White House.

Okay? So, with that basis, I can't really cleanly come and say, hey, you have a door to walk through, except for suggesting things like, hey, there's a shortage in health care workers, women. Why don't you go take a gander over there? Which is the same type of sorting, repeating itself. Sorting them into, or sorting women into a field, right? Which is fine in the realm of all things, right? But here's a problem, right? You go into a care industry that you have no interest in, what are you going to end up with?

Lack of care, right? Because you don't really care about working in there, all you're doing is trying to put food on the table, right? People gravitate to different industries and gravitate to different jobs that they go into because they're interested in it, because they feel some sort of pull towards it, okay? We can't push somebody into a career just because that's all that you have there. You're not going to end up with the right outcomes, okay? And that's what been happening, right? We've been marginalizing women through history.