Stanford's AI Economist: The Next 10 Years Will Be the Best AND the Worst in History | Erik Brynjolfsson

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**Erik Brynjolfsson** (1:00)
There are a bunch of jobs, millions of jobs that are going to disappear.

**Marina Mogilko** (1:04)
How soon?

**Erik Brynjolfsson** (1:05)
Already, it's already happening.

**Marina Mogilko** (1:06)
This is Erik, Stanford economist who saw AI coming before almost anyone. He spent 30 years measuring what technology does to jobs. And he says, we've just turned the corner, but what happens next depends on what we do right now.

**Erik Brynjolfsson** (1:21)
I think it's going to be even bigger than most people realize. The Industrial Revolution allowed machines to augment muscle power. Now we're doing the same thing for our brains, our minds.

**Marina Mogilko** (1:32)
If intelligence is automated, what is left for humans to make money with?

**Erik Brynjolfsson** (1:36)
The next decade, if we play our cards right, will be the best decade in human history by far. Or this could be like one of the worst 10 years ever.

**Marina Mogilko** (1:45)
What can someone like me do?

**Erik Brynjolfsson** (1:46)
I think what you really need to do is...

**Marina Mogilko** (1:49)
You just had this lab paper called Canaries in the Coal Mine. That shows that AI has already wiped out 16 percent of entry-level jobs, but only for people under 25 Can we talk about that?

**Erik Brynjolfsson** (2:00)
Sure. It's not just under people under 25 It's also specifically in the most exposed occupations. You can rank all the occupations in the economy by whether AI can affect them. So we did that and we looked at the most exposed occupations, and that's the number you just quoted, about 16 percent less employment for young people up to age 25 But it's also worth noting that in the other end of the spectrum, the least exposed occupations like home health aids, there's actually growing employment. Also, for older workers, growing employment and perhaps most interestingly, for people using AI to augment what they're doing versus automate what they're doing, we could look at the kinds of prompts that we're using.
Those people also did significantly better. So I don't want to sugarcoat it.
The core folks who are using AI to automate their jobs in places like coding and call centers that are highly exposed, there was double digit declines in employment. Since we published that paper, we've continued to track it and the effects just getting bigger every month.

**Marina Mogilko** (3:03)
What are these most exposed fields?

**Erik Brynjolfsson** (3:05)
So coding is obviously dead center, call centers, parts of sales, marketing.
We find the most useful way to do it is look at tasks as opposed to entire occupations. So every job is a bundle of tasks. Like Jeff Hinton, the famous deep learning researcher, talked about radiologists being replaced. But radiologists actually do 26 distinct tasks we've recorded. One of them is reading medical images. That one's getting done by machines. But they also sometimes conduct physical exams, they review lab data, they coordinate care with other physicians. Those are not nearly as affected by LLMs. If you look at all the occupations in the economy, there's not a single one where LLMs just run the table and can do everything. In each case, there's parts of the job that LLMs can help with, writing memos, doing emails, looking at labs.
There's others where LLMs can't help. They don't lift a box or drive a car, at least not yet.

**Marina Mogilko** (4:05)
For those most endangered fields, how much is AI doing in terms of tasks? Is it close to 80 percent or?

**Erik Brynjolfsson** (4:14)
Well, that's the other thing. Within tasks is varying quite a bit as well. In coding, it's happened so fast with agents.
I teach my course at Stanford. Even last year, the students all did projects and they presented at the end of the class, typically like PowerPoint presentations. This year, every single student, every single project, they have to have running code. Because whether or not they were a coder before or not, everybody is a coder now. That's a good message for your listeners. If you use tools like Replet or Cursor or Cloud Code, you can just have an idea, you describe it and Cloud Code or Replet will help create it. So they all presented, actually just Friday, we had our final presentations, 20 teams presented it. So that's something where it's doing a lot. Call centers, I did a paper on call centers.