whaaswijk
Joined 12 years ago
Joined 12 years ago
How does that prevent AI from becoming superhuman in all intellectual domains, thus creating ASI? We set "become good as chess" as the metric and it became superhuman in that domain.
> The problem is what happens when you max that out.
I'm not sure how you conceptualize "maxing out" the intelligence metric. Again, taking chess ability as a proxy metric for intelligence, there is no reason to believe we have maxed out chess performance, but AI is already far superior to humans. And better bots are created all the time. There is no need to design a new metric to improve chess performance. The old "How many currently existing players can I beat?" is good enough. Also, why couldn't it design better metrics after achieving superhuman intelligence?
But even if we suppose there is some kind of fixed point limit to this process, it would still be far above human level. That is all that is required for ASI.
Regarding X-risk: the point is that it becomes easy even for people who, unlike you, haven't studied biology. For things such as atomic war, the AI does not necessarily need to acquire the materials. It can access them digitally by hacking the weapons systems, possibly in collaboration with some human actors. Or maybe it spoofs detection systems causing countries to fire upon each other. Generally, it seems to me that the barrier to entry for bad actors to cause these scenarios is decreasing. Whether these scenarios are more likely than D-risk I don't know.
But let's grant that the models only communicate through certain phone lines. I think very bad scenarios are still possible. There are at least two that I can see. 1) The models exploit the users which have direct access to it. It somehow convinces them to perform tasks for it or to give it more access. 2) Control of the AI is held by a small number of people. This could be bad because it grants them an outsized power over all humans without such access, and thus lead to oligarchy/dictatorship.
I think the main argument for ASI is something like (i) extrapolating the progress from the past 10 years into the future, (ii) rapid progress apparently still being made, and (iii) seeing no obvious theoretical limitations.
> How does it know it's improving and not overfitting to its own recursive definition of intelligence? It can't, and that's exactly what it will do. I haven't given this much thought, so maybe I'm missing something, but I don't see how this follows. One possible solution: to avoid overfitting, can it not just make a copy of itself, modify the copy, and empirically check if the model performs better? That's essentially what humans are currently doing when designing AIs.
Regarding the X-risk vs D-risk: I think how one weighs these risks partially depends on what one thinks the capabilities of the models are. Call me a boot-licker, but if the models get smart enough to explain, in detail, to any psychopath, how to construct a bomb or synthesize a deadly virus, I don't think benefits society to distribute them widely. Therefore, to argue for widespread distribution you have to argue that either (i) the models aren't that capable or (ii) the guardrails are robust enough to prevent them from being used in catastrophic ways by bad actors. I think we may be rapidly approaching a time where neither of these hold. Having said that, I certainly agree that the D-risk is also real.
Btw, wouldn't AI increase the risk factors you mention such bioterrorism or nuclear war? It seems like we're not far off from AIs being able to enhance the capabilities of bad actors in the near future.