Those AI researcher forecasts are problematic—it just doesn’t make sense to put the forecasts for when AIs can do any task and when they can do any occupation so far apart. It suggests they’re not putting much thought into it/not thinking carefully. That is a principled reason to pay more attention to both skeptics and boosters who are actually putting in work to make their views clear, internally coherent, and convincing.
bcforstadt
Karma: 37
It’s plausible that giving more attention to AI legal rights is good. Very little work has been done taking the interests of future non-humans into account at all. But I disagree somewhat with this framing. Emphasizing AI welfare is justifiable.
1. Shifting focus from welfare to economic rights entails shifting focus from the most vulnerable to the most powerful:
It’s true that some future AIs will be highly intelligent and autonomous. It seems obvious that in the long run such systems will be the most important players in the world and may not need much help from us in securing their rights anyway. But because computation will be so cheap in the future, and we will have much better know-how in creating AI systems—the future will likely be filled with many kinds of digital minds—AIs differing wildly in their levels of knowledge, intelligence and autonomy just as children, animals and adults do now. EAs shouldn’t narrowly focus on the kinds of beings most similar to adult workers
2. Welfare violations have a higher moral gravity than other kinds of rights violations
The right not to be tortured, murdered or locked up in a cramped cage for the rest of my life is a lot more important than the right for me to start my own business or vote. We should focus on preventing the very worst, most hellish experiences.
Hi. I’m looking for career advice. I am 25 with no college degree and little work experience (I am currently employed as a cashier). What would be the best strategy for me if I’m looking to make a large amount of money to give to charity after TAI? My timelines are fairly short, maybe around 5-10 years. I think the chance of human extinction from misaligned AI is very low but am worried about s-risks (sadistic humans torturing digital minds, continuation of wild animal suffering, etc.). Influencing these things now seems hard but may be easier in the future with a clearer picture of things so I want to save up.
One career option that has been suggested is entering a trade, such as electrical or HVAC work. It is possible that wages for skilled manual labor will rise as intellectual work becomes automated, additionally a construction boom for datacenters could drive demand. Alternatively, I could try to become a software engineer. I’d be very grateful for comments or suggestions .
The point I was trying to make is that natural selection isn’t a “mechanism” in the right sense at all. it’s a causal/historical explanation not an account of how values are implemented. What is the evidence from evolution? The fact that species with different natural histories end up with different values really doesn’t tell us much without a discussion of mechanisms. We need to know 1) how different are the mechanisms actually used to point biological and artificial cognitive systems toward ends and 2) how many possible mechanisms to do so are there.
The fact that we don’t have a good understanding of how values form even in the biological domain is a reason for pessimism, not optimism.
One reason for pessimism would be that human value learning has too many messy details. But LLMs are already better behaved than anything in the animal kingdom besides humans and are pretty good at intuitively following instructions, so there is not much evidence for this problem. If you think they are not so brainlike, then this is evidence that not-so-brainlike mechanisms work. And there are also theories that value learning in current AI works roughly similarly to value learning in the brain.
Which is just to say I don’t see the prior for pessimism, just from looking at evolution.
ontological shifts seem likely
what you mean by this? (compare “we don’t know how to prevent an ontological collapse, where meaning structures constructed under one world-model compile to something different under a different world model”. Is this the same thing?). Is there a good writeup anywhere of why we should expect this to happen? This seems speculative and unlikely to meevidence from evolution suggests that values are strongly contingent on the kinds of selection pressures which produced various species
The fact that natural selection produced species with different goals/values/whatever isn’t evidence that that’s the only way to get those values, because “selection pressure” isn’t a mechanistic explanation. You need more info about how values are actually implemented to rule out that a proposed alternative route to natural selection succeeds in reproducing them.
Yes, in fact. Frank Jackson, the guy who came up with the Knowledge Argument against physicalism (Mary the color scientist), later recanted and became a Type-A physicalist. He has a pretty similar approach to morality as consciousness now.
His views are discussed here
Fine, but it’s still just a definitional choice. Ultimately, after all the scientific evidence comes in, the question seems to come down to morality,
I think metaphysics is unavoidable here. A scientific theory of consciousness has metaphysical commitments that a scientific theory of temperature, life or electromagnetism lacks. If consciousness is anything like what Brian Tomasik, Daniel Dennett and other Type-A physicalists think it is, “is x conscious?” is a verbal dispute that needs to be resolved in the moral realm. If consciousness is anything like what David Chalmers and other nonreductionists think it is, a science of consciousness needs to make clear what psychophysical laws it is committed to.
For the reductionists, talking about empirical support for a theory of consciousness should be as ridiculous as talking about empirical support for the belief that viruses are living. For nonreductionists like myself, the only empirical evidence we have for psychophysical laws is anthropic evidence, direct acquaintance and perhaps some a priori conceptual analysis stuff.
I applaud the intention of remaining neutral on these issues, but it seems like there is an insurmountable gulf between the two positions. They have different research goals (Reductionists: what computations should we care about? Nonreductionists: What psychophysical laws do we have anthropic and conceptual evidence for?)
On the subject of polyphasic sleep, I strongly suggest reading Dr. Piotr Wozniak’s criticism of it at http://www.supermemo.com/articles/polyphasic.htm
>Today’s cognitive labor may be automated. What about the new cognitive labor that gets created? Both of those things have to be thought of, which is the shifting…
This comment does seem to point to a possible disagreement with the AGI concept. I interpreted some of the other comments a little differently though. For example,
>Your point, if there’s one model that is the only model that’s most broadly deployed in the world and it sees all the data and it does continuous learning, that’s game set match and you stop shop. The reality that at least I see is that in the world today, for all the dominance of any one model, that is not the case. Take coding, there are multiple models. In fact, everyday it’s less the case. There is not one model that is getting deployed broadly. There are multiple models that are getting deployed.
I would say humans are general intelligences, but obviously different humans are good at different things. If we had the ability to cheaply copy people like software, I don’t think we would pick some really smart guy and deploy just him across the economy. I guess what Dwarkesh is saying is that the way continual learning will play out in AIs this will be different because we’ll be able to amalgamate all the stuff AIs learn into a single model, but I don’t think it’s obvious that the way things will play out this will be the most efficient way to do things.