Dario Amodei: prediction

Transcript context

…I think that’s going to be one of the areas that changes fastest for two reasons. One, programming is a skill that’s very close to the actual building of the AI. So the farther a skill is from the people who are building the AI, the longer it’s going to take to get disrupted by the AI. I truly believe that AI will disrupt agriculture. Maybe it already has in some ways, but that’s just very distant from the folks who are building AI, and so I think it’s going to take longer. But programming is the bread and butter of a large fraction of the employees who work at Anthropic and at the other companies, and so it’s going to happen fast. The other reason it’s going to happen fast is with programming, you close the loop both when you’re training the model and when you’re applying the model. The idea that the model can write the code means that the model can then run the code and then see the results and interpret it back. And so it really has an ability unlike hardware, unlike biology, which we just discussed, the model has an ability to close the loop. And so I think those two things are going to lead to the model getting good at programming very fast. As I saw on typical real-world programming tasks, models have gone from 3% in January of this year to 50% in October of this year. So we’re on that S-curve where it’s going to start slowing down soon because you can only get to 100%. But I would guess that in another 10 months, we’ll probably get pretty close. We’ll be at least 90%. So again, I would guess, I don’t know how long it’ll take, but I would guess again, 2026, 2027 Twitter people who crop out these numbers and get rid of the caveats, I don’t know. e’ll be at least 90%. So again, I would guess, I don’t know how long it’ll take, but I would guess again, 2026, 2027 Twitter people who crop out these numbers and get rid of the caveats, I don’t know. I don’t like you, go away. I would guess that the kind of task that the vast majority of coders do, AI can probably, if we make the task very narrow, just write code, AI systems will be able to do that. Now that said, I think comparative advantage is powerful. We’ll find that when AIs can do 80% of a coder’s job, including most of it that’s literally write code with a given spec, we’ll find that the remaining parts of the job become more leveraged for humans, right? Humans, there’ll be more about high level system design or looking at the app and is it architected well and the design and UX aspects and eventually AI will be able to do those as well. That’s my vision of the powerful AI system. But I think for much longer than we might expect, we will see that small parts of the job that humans still do will expand to fill their entire job in order for the overall productivity to go up. That’s something we’ve seen. It used to be that writing and editing letters was very difficult and writing the print was difficult. Well, as soon as you had word processors and then computers and it became easy to produce work and easy to share it, then that became instant and all the focus was on the ideas. So this logic of comparative advantage that expands tiny parts of the tasks to large parts of the tasks and creates new tasks in order to expand productivity, I think that’s going to be the case. Again, someday AI will be better at everything and that logic won’t apply, and then humanity will have to think about how to collectively deal with that and we’re thinking about that every day and that’s another one of the grand problems to deal with aside from misuse and autonomy and we should take it very seriously. But I think in the near term, and maybe even in the medium term, medium term like 2, 3, 4 years, I expect that humans will continue to have a huge role and the nature of programming will change, but programming as a role, programming as a job will not change. It’ll just be less writing things line by line and it’ll be more macroscopic. And I wonder what the future of IDEs looks like. So the tooling of interacting with AI systems, this is true for programming and also probably true for in other contexts like computer use, but maybe domain specific, like we mentioned biology, it probably needs its own tooling about how to be effective. And then programming needs its own tooling. Is Anthropic going to play in that space of also tooling potentially?…

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