Multiheaded comments on Muehlhauser-Wang Dialogue - Less Wrong
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Comments (284)
First, thank you for publishing this illuminating exchange.
I must say that Pei Wang sounds way more convincing to an uninitiated, but curious and mildly intelligent lay person (that would be me). Does not mean he is right, but he sure does make sense.
When Luke goes on to make a point, I often get lost in a jargon ("manifest convergent instrumental goals") or have to look up a paper that Pei (or other AGI researchers) does not hold in high regard. When Pei Wang makes an argument, it is intuitively clear and does not require going through a complex chain of reasoning outlined in the works of one Eliezer Yudkowsky and not vetted by the AI community at large. This is, of course, not a guarantee of its validity, but it sure is easier to follow.
Some of the statements are quite damning, actually: "The “friendly AI” approach advocated by Eliezer Yudkowsky has several serious conceptual and theoretical problems, and is not accepted by most AGI researchers. The AGI community has ignored it, not because it is indisputable, but because people have not bothered to criticize it." If one were to replace AI with physics, I would tend to dismiss EY as a crank just based on this statement, assuming it is accurate.
What makes me trust Pei Wang more than Luke is the common-sense statements like "to make AGI safe, to control their experience will probably be the main approach (which is what “education” is all about), but even that cannot guarantee safety." and "unless you get a right idea about what AGI is and how it can be built, it is very unlikely for you to know how to make it safe". Similarly, the SIAI position of “accelerate AI safety research and decelerate AI capabilities research so that we develop safe superhuman AGI first, rather than arbitrary superhuman AGI” rubs me the wrong way. While it does not necessarily mean it is wrong, the inability to convince outside experts that it is right is not a good sign.
This might be my confirmation bias, but I would be hard pressed to disagree with "To develop a non-trivial education theory of AGI requires a good understanding about how the system works, so if we don’t know how to build an AGI, there is no chance for us to know how to make it safe. I don’t think a good education theory can be “proved” in advance, pure theoretically. Rather, we’ll learn most of it by interacting with baby AGIs, just like how many of us learn how to educate children."
As a side point, I cannot help but wonder if the outcome of this discussion would have been different were it EY and not LM involved in it.
This sort of "common sense" can be highly misleading! For example, here Wang is drawing parallels between a nascent AI and a human child to argue about nature vs nurture. But if we compare a human and a different social animal, we'll see that most of the differences in their behavior are innate and the gap can't be covered by any amount of "education": e.g. humans can't really become as altruistic and self-sacrificing as worker ants because they'll still retain some self-preservation instinct, no matter how you brainwash them.
What makes Wang think that this sort of fixed attitude - which can be made more hard-wired than the instincts of biological organisms - cannot manifest itself in an AGI?
(I'm certain that a serious AI thinker, or just someone with good logic and clear thinking, could find a lot more holes in such "common sense" talk.)
Presumably the argument is something like:
You can't build an AI that is intelligent from the moment you switch it on: you have to train it.
We know how to train intelligence into humans, its called education
An AI that lacked human-style instincts and learning abilities at switch-on wouldn't be trainable by us, we just wouldn't know how, so it would never reach intelligence.