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Whole Brain Emulation might be such an example, at least insofar as nothing in the approach itself seems to imply that it would be prone to get stuck in some local optimum before its ultimate goal (AGI) is achieved.
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Superintelligence Reading Group - Section 1: Past Developments and Present Capabilities
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However, Whole Brain Emulation is likely to be much more resource intensive than other approaches, and if so will probably be no more than a transitional form of AGI.
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What do you think of I. J. Good's argument? (p4)
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I think that the process that he describes is inevitable unless we do ourselves in through some other existential risk. Whether this will be for good or bad will largely depend on how we approach the issues of volition and motivation.
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I find it particularly important because of the example of automating research, which is probably the task I care most about.
Neither math research nor programming or debugging are being taken over by AI, so far, and none of those require any of the complicated unconscious circuitry for sensory or motor interfacing. The programming application, at least, would also have immediate and major commercial relevance. I think these activities are fairly similar to research in general, which suggests that what one would classically call the "thinking" parts remain hard to implement AI.
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Programming and debugging, although far from trivial, are the easy part of the problem. The hard part is determining what the program needs to do. I think that the coding and debugging parts will not require AGI levels of intelligence, however deciding what to do definitely needs at least human-like capacity for most non-trivial problems.
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Good points. Any thoughts on what the dangerous characteristics might be?
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The following are some attributes and capabilities which I believe are necessary for superintelligence. Depending on how these capabilities are realized, they can become anything from early warning signs of potential problems to red alerts. It is very unlikely that, on their own, they are sufficient.
- A sense of self. This includes a recognition of the existence of others.
- A sense of curiosity. The AI finds it attractive (in some sense) to investigate and try to understand the environment that it find itself in.
- A sense of motivation. The AI has attributes similar in some way to human aspirations.
- A capability to (in some way) manipulate portions of its external physical environment, including its software but also objects and beings external to its own physical infrastructure.
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I would bet heavily on the accumulation. National average IQ has been going up by about 3 points per decade for quite a few decades, so there have definitely been times when Koko's score might have been above average. Now, I'm more inclined to say that this doesn't mean great things for the IQ test overall, but I put enough trust in it to say that it's not differences in intelligence that prevented the gorillas from reaching the prominence of humans. It might have slowed them down, but given this data it shouldn't have kept them pre-Stone-Age.
Given that the most unique aspect of humans relative to other species seems to be the use of language to pass down knowledge, I don't know what else it really could be. What other major things do we have going for us that other animals don't?
I think that language plus our acquisition of the ability to make quasi-permanent records of human utterances are the biggest differentiators.