> Before approving construction, I would want communities of humans to understand why the design works and what justifies confidence in its safety. I would hope that we all would.
Until very recently, I pored over every single line of code Claude generated with razor sharp scrutiny. I would usually catch issues with every response. I'm catching fewer problems these days. Maybe the model is just getting better, and maybe I'm being less careful while under pressure to ship more and more often. But model capability is obviously growing. Even back in March, you could tell it "give me a function that adds two numbers" and you could be 100% confident that it would write the correct function. There was almost no point in looking at the code. Since then, the complexity floor of problems in the category "this is so simple that the model couldn't possibly get it wrong" is rising, and with it, my cognitive surrender to the model is increasing too. Why check it? It's obviously going to be correct.
If AI designs a terawatt fusion plant, then of course we're going to meticulously pore over every detail to ensure safety, reliability, efficiency, whatever. If we find no flaws in the design whatsoever, will we be less careful about the second one? The third one? What about the ten thousandth one? Will "a nuclear fusion plant" become something that models couldn't possibly get wrong?
Terence Tao is arguing that the human involvement in research is crucial, but doesn't convincingly justify why, in my opinion. He says that "human agency is a value of fundamental importance" and that we will need to build "thriving human communities that can understand [AI ideas] together" - not for the sake of correctness, which AI may surpass us on, but for, I guess, the possibility of reclaiming human meaning and purpose. I don't disagree with this at all, but it's not an argument, it's a statement of values. Unfortunately, the stark reality is that if AI does surpass humans, it will become the economically dominant strategy to not verify them and not double check them, but to just do whatever they say. This seems like a great way to raise p(doom). But as the models get better and better, and as I'm scrutinizing Claude's output less and less... I just hope that there are more Terence Taos out there than people like me.
A metaphor I'm constantly drawn to is the transition from agrarian to urban societies following the Industrial Revolution. Somebody who somehow saw the Industrial Revolution coming from the perspective of somebody living in an agrarian society might have envisioned it leading to 'super farms.' And it did.
But the biggest change wasn't what it did to farming, but enabling people and societies to start doing much more than just farming, as well as enabling some great social change as well by simply economically obsoleting slave labor. And trying to imagine all of the implications of this, as well as much society might look like, from the perspective of somebody living in an agrarian society would probably have been simply impossible.
I think people keep ignoring this possibility for things that LLMs will change. There's a vast amount of the 'cognitive economy' that LLMs stand to be able to automate. And I think that will open up a vacuum in society for people to build on top of what LLMs will do (and already are doing). I don't know what that means exactly, but that's because we still live in that 'agrarian society' and trying to imagine what things will look like after the 'Industrial Revolution' is probably just impossible.
> I think that will open up a vacuum in society for people to build on top of what LLMs will do (and already are doing).
If an AI can replace me on the mental aspects of work, and robotics are on their way to replacing humanity on the physical aspects of work... then what's left? When there was agrarian societies, there were writers, priests, bankers, merchants, and laborers before and after - I really don't think things were that unclear even at the time. Now that we have machines that are close to exceeding humans in every way, what good are humans?
> If an AI can replace me on the mental aspects of work, and robotics are on their way to replacing humanity on the physical aspects of work... then what's left?
At the risk of sounding new age, my answer to this is "emotional work".
What exactly that would mean in the equivalent of the post-agrarian society that LLMs might bring, I cannot know.
You can't ignore how economies shift in response to the surplus of things. When software or other such things can be produced trivially, its cost and value is going to approach as close to $0 as it possibly can. By contrast the value of other things will go up.
So for instance in the past it used to be that literacy was a high value skill. Transcription and other such services were highly valued. Now that literacy is ubiquitous, such skills have basically no value in and of themselves. But instead, we've built a mountain of stuff on top of those skills and in domains which simply did not even exist before, and those things are now valued. But what we value now a days is no more permanent or inherent in its value than anything else that ultimately failed to stand the test of time.
pyridines · · focus · HN ↗
Until very recently, I pored over every single line of code Claude generated with razor sharp scrutiny. I would usually catch issues with every response. I'm catching fewer problems these days. Maybe the model is just getting better, and maybe I'm being less careful while under pressure to ship more and more often. But model capability is obviously growing. Even back in March, you could tell it "give me a function that adds two numbers" and you could be 100% confident that it would write the correct function. There was almost no point in looking at the code. Since then, the complexity floor of problems in the category "this is so simple that the model couldn't possibly get it wrong" is rising, and with it, my cognitive surrender to the model is increasing too. Why check it? It's obviously going to be correct.
If AI designs a terawatt fusion plant, then of course we're going to meticulously pore over every detail to ensure safety, reliability, efficiency, whatever. If we find no flaws in the design whatsoever, will we be less careful about the second one? The third one? What about the ten thousandth one? Will "a nuclear fusion plant" become something that models couldn't possibly get wrong?
Terence Tao is arguing that the human involvement in research is crucial, but doesn't convincingly justify why, in my opinion. He says that "human agency is a value of fundamental importance" and that we will need to build "thriving human communities that can understand [AI ideas] together" - not for the sake of correctness, which AI may surpass us on, but for, I guess, the possibility of reclaiming human meaning and purpose. I don't disagree with this at all, but it's not an argument, it's a statement of values. Unfortunately, the stark reality is that if AI does surpass humans, it will become the economically dominant strategy to not verify them and not double check them, but to just do whatever they say. This seems like a great way to raise p(doom). But as the models get better and better, and as I'm scrutinizing Claude's output less and less... I just hope that there are more Terence Taos out there than people like me.
somenameforme · · focus · HN ↗
But the biggest change wasn't what it did to farming, but enabling people and societies to start doing much more than just farming, as well as enabling some great social change as well by simply economically obsoleting slave labor. And trying to imagine all of the implications of this, as well as much society might look like, from the perspective of somebody living in an agrarian society would probably have been simply impossible.
I think people keep ignoring this possibility for things that LLMs will change. There's a vast amount of the 'cognitive economy' that LLMs stand to be able to automate. And I think that will open up a vacuum in society for people to build on top of what LLMs will do (and already are doing). I don't know what that means exactly, but that's because we still live in that 'agrarian society' and trying to imagine what things will look like after the 'Industrial Revolution' is probably just impossible.
gWPVhyxPHqvk · · focus · HN ↗
If an AI can replace me on the mental aspects of work, and robotics are on their way to replacing humanity on the physical aspects of work... then what's left? When there was agrarian societies, there were writers, priests, bankers, merchants, and laborers before and after - I really don't think things were that unclear even at the time. Now that we have machines that are close to exceeding humans in every way, what good are humans?
pelario · · focus · HN ↗
At the risk of sounding new age, my answer to this is "emotional work".
What exactly that would mean in the equivalent of the post-agrarian society that LLMs might bring, I cannot know.
jacquesm · · focus · HN ↗
somenameforme · · focus · HN ↗
So for instance in the past it used to be that literacy was a high value skill. Transcription and other such services were highly valued. Now that literacy is ubiquitous, such skills have basically no value in and of themselves. But instead, we've built a mountain of stuff on top of those skills and in domains which simply did not even exist before, and those things are now valued. But what we value now a days is no more permanent or inherent in its value than anything else that ultimately failed to stand the test of time.