This whole debate makes me wonder , if we can have any certainity for AI predictions. Almost all is based on personal opinions, highly susceptible to biases. And even people with huge knowledge about these biases aren't safe. I don't think anyone can trace their prediction back to empiric data, it all comes from our minds' black boxes, to which biases have full access and which we can't examine with our conciousness.
While I find Mark's prediction far from accurate, I know it might be just because I wouldn't like it. I like to think that I would have some impact on AGI research, that some new insights are needed rather than just pumping more and more money in SIRI-like products. Developement of AI in next 10-15 years would mean that no qualitative research were needed and that all what is to be done is honing current technology. It would also mean there was time for thorough developement of friendliness and we may end up with AI catastroph.
While I guess human level AI to rise in about 2070s, I know I would LIKE if it happened in 2070s. And I base this prediction on no solid base.
Can anybody point me to any near-empiric data concerning, when AGI may be developed? Anything more solid than hunch of even most prominent AI researcher? Applying Moore's law seems a bit magical, it without doubt has some Bayesian effect, but with little certainity.
The best thing I can think of is that we all can agree, that AI is not be developed tomorrow. Or in a month. Why do we think that? It seems like coming from some very reliable empiric data. If we can identify factor, which make us near-certain AI is not be created in a span of few months from now, maybe upon closer look, it may provide us with some less shaky predictions for further future.
Honestly the best empiric data I know is Ray Kurzweil's extrapolations, which places 2045 generically as the date of the singularity, although he places human-level AI earlier around 2029 (obviously he does not lend credence to a FOOM). You have to take some care in using these predictions as individual technologies eventually hit hard limits and leave the exponential portion of the S-curve, but molecular and reversible computation shows that there is plenty of room at the bottom here.
2070 is a crazy late date. If you assume the worst case that we will be ...
Cross-posted from my blog.
Yudkowsky writes:
My own projection goes more like this:
At least one clear difference between my projection and Yudkowsky's is that I expect AI-expert performance on the problem to improve substantially as a greater fraction of elite AI scientists begin to think about the issue in Near mode rather than Far mode.
As a friend of mine suggested recently, current elite awareness of the AGI safety challenge is roughly where elite awareness of the global warming challenge was in the early 80s. Except, I expect elite acknowledgement of the AGI safety challenge to spread more slowly than it did for global warming or nuclear security, because AGI is tougher to forecast in general, and involves trickier philosophical nuances. (Nobody was ever tempted to say, "But as the nuclear chain reaction grows in power, it will necessarily become more moral!")
Still, there is a worryingly non-negligible chance that AGI explodes "out of nowhere." Sometimes important theorems are proved suddenly after decades of failed attempts by other mathematicians, and sometimes a computational procedure is sped up by 20 orders of magnitude with a single breakthrough.