AI could make most human labor unnecessary within 20 years

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 35:01

   One of the main arguments against the impacts on labor is, well, we're going to automate a bunch of boring tasks and we'll create a bunch of demand for new tasks that humans have not been able to do because they were stuck in boring dead end jobs. I happen to think that if there was more subsidized health care in America or socialized health care in America, you would see a bunch of people quit their jobs to start new companies because AI makes it a lot easier to do the bureaucratic work of starting a new company.

2. 35:27

   That doesn't seem like it's on the table. Maybe it'll change after this election. Do you think that job loss is just a necessary outcome of the AI path we're on now? Or do you see that other argument? Jobs are an input to the economy and one that drives a lot of human welfare, a sense of purpose and income, a need to show up, building relationships with colleagues, getting something done. Jobs play a very central role, and as the AI achieves superhuman intelligence, the scarcity of white-collar skills goes away.

3. 36:11

   So that things like doing telesales or telesupport or helping in the accounting department, the ability of the AI to do that work radically cheaper, radically faster, and even more accurately means that that goes away. And there isn't some mountaintop of cognition that the AI does not achieve. You know, take, for example, what's going on in mathematics today, where these models that are trivial compared to next year's models are already publishing papers and making people go, wow, what's happening to mathematics will happen in other areas.

4. 36:59

   And that's sort of contrary to this old view that, well, the easy stuff will get done by the AIs. But modeling biology or physics or proving Navier-Stokes, only humans would be able to do that. The mathematics comparison is really interesting to me. You mentioned software engineering earlier. There's a verifiability in those domains, right? You can write the code. You can see if it runs. It's going to run or not.

5. 37:24

   Mathematics, more complicated, but you can write the lean code. You can see if you've solved the solution. You can irritate tens of thousands of mathematicians worldwide with your 770 proofs in one day. We'll see what happens. That's not the case in every field. It's the case in the field called capitalism. Yeah. Just in general, you can do any sort of economically viable task and capitalism will verify the result.

6. 37:45

   Yeah. People buy good products. They don't buy bad products. That's a reinforcement learning thing. It doesn't exist, you know, in terms of, OK, is this a good piece of poetry or not? So it may be the case that RL. you know, won't invade those domains where there is no objective outcome. But doing that accounting work, doing that telesales work, believe me, it is subject to analysis, just like medical diagnosis, just like invention of new materials.

7. 38:20

   This is, you know, how do you think humans learn these things? We, that reinforcement learning is how humans learn and how these machines learn. So there's not like some other thing that the machine can never understand. I mean, this is why I started by asking about like the nature of the technology here. If we really think we're building something that models human consciousness, my question is less whether, you know, my friends who are lawyers are going to run into a crisis of AI empowered legal software.

8. 38:52

   It turns out the verifier in the legal field is a judge who maybe hasn't had lunch, and they're fundamentally chaotic, right? There's just something there that will keep them there. But if we're building a cautiousness that learns the way you're suggesting humans learn, I'm thinking about my kids. And I'm thinking about them in two dimensions. One, my kids are very clever. And what they have learned is how to get around my rules and negotiate my rules and get around the boundaries, and they're very good at it.

9. 39:19

   And then two, what kind of world will they enter into that isn't purely nihilistic, right? Where any activity they may set themselves upon will quickly be seen as just another domain for AI to conquer. And then there's not a point. Those ideas seem to be running directly at each other, right? Kids are smart and clever and they're kind of with new ideas. And then at the first sign of economic viability, the rapacious capitalism machine will come and take it from them.

10. 39:46

    Well, I wouldn't say rapacious. I mean, the ability to build houses with human robots and make them cheap, the ability to do surgeries and cure diseases that wouldn't be cured otherwise, I wouldn't call that rapacious. That is fulfilling goals. The fact that there'll be less in the way of shortages, in fact, if you say, okay, 20 years from now, it's not clear what shortages there will be at all. And so humanity in that era of true abundance will have to find a way to organize and have purpose.

11. 40:25

    And hopefully they still have the control. The next 20 years. Can we just go back to hopefully they still have control? Well, that's the alignment problem that we discussed. But assuming you solve the alignment problem. This feels like a big assumption. It's an assumption, yes, and not guaranteed. But then the other problem you have is a problem of abundance and purpose at that point. But, you know, I'll leave it to younger people to figure out at that point in time how they choose to deal with that.

12. 41:03

    I mean, you could literally say, you know, let's be like the Amish and let's only use AI for certain things. I proposed in my memo the idea that some professions, you know, child care, food preparation, art, sports, a variety of things might get chosen to be human reserved, even though the AI could do those things better, that we would choose to do that. But that's going to be a policy question people will have.

13. 41:33

    But their freedom of choice, once you have that abundance, is very different than the shortage we have today where, you know, in countries in Africa, most people never meet a doctor or, you know, almost half the kids are malnourished and don't develop their brain. So you want to say even though that has challenges, you've eliminated a lot of the things that are tough about life. today. My big concern is this 20-year transition period where you'll have winners and losers and a lot of disruption, and we have to get through that in order to get to that period of abundance.

14. 42:18

    You think it's 20 years from now? You know, I pick that as a reasonably safe number. There's a variety of milestones. For example, For example, humanoid robots, you know, are those two or three years away, as some would say, or more like eight years away, as other people would say. There's not that many people saying that given the amount of capital and number of companies, particularly in China, that are working on that, there's no notion that it's unsolvable to have a hand and fingers and be able to deliver physical labor at very, very low cost.

15. 42:58

    And so I could be wrong about that number. It could be slightly less or slightly more. But on that order of magnitude, yes, if we don't choose to massively slow down or stop, then we will have robots that can build houses, grow food, do surgery.