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AI 2040: Plan A
The AI 2027 authors published a follow-up. Scott Alexander also wrote a separate blogpost and although not in the author list contributed.
It's a very speculative and optimistic timeline of AI's future evolution. It presents five ways or "plans" the US government will intervene. Unsurprisingly, the ASI-pilled authors favor strong, global regulation to ensure alignment. Summaries:
Plan A (recommended): the US makes an international treaty with China, pauses AI training (not inference, i.e. no new models but we keep using existing ones), enforces full transparency of future research, then when alignment research advances enough carefully resumes
Plan S: the US makes an international treaty with China and pauses AI training for as long as possible
Plan B: the US regulates AI at home and demands China also regulate, but doesn't negotiate with them, probably leading to a war
Plan C: the US regulates AI and ignores China, so they overtake it and reach ASI first
Plan D: the US doesn't regulate AI, we get ASI in early 2031 and it probably kills everyone
Personally, I just don't share the optimism of these guys in either direction.
I think politicians will prioritize culture war and the failing economy over AI regulation, and at most pass some executive orders suggesting companies be more careful. But I also doubt we'll have ASI that can solve the abstract problems "take over the world" or even "keep existing world leaders in power" (they're getting old and increasingly unpopular, their parties may remain in power but only if their policies significantly shift).
What I expect from AI:
Basically solve legacy code by rewriting entire codebases, applying very niche domain knowledge, and actually finding and handling edge-cases better than humans
Greatly speedup research, leading to new discoveries and inventions. Important but background things like food preservation and medicine will improve from AI-assisted discoveries. Major advancements in math and theoretical physics
Much better and cheaper education, therapy, initial medical/legal appointments, personal repairs...maybe reducing but not eliminating human jobs, because human experts will offer these services "premium"
Won't replace human artists. Some advertisements and infographics will be AI but even some will still be human. At best it will assist them in a way where the human still fully controls the output, e.g. by generating code leading to new and improved software tools to learn, practice, and create art
Used by the vast majority as a personal assistant, but doesn't replace human relations
Maybe someone here can help me with this.
What is the bull case, beyond drawing lines on a graph, for AI achieving superhuman, or even human, performance on tasks that are not quickly verifiable?
AI is quite clearly superhuman at self-contained programming problems. I haven't tried Fable, but I suspect that superhuman open ended software engineering is not far away, though I suspect that humans will have a role in architecture and problem setting as opposed to problem solving for some time more. I expect hardware work will also quickly go down this path, at least to some extent, and really anything that can be RLVR'd. That's enough to account for a huge portion of white collar work and carries serious cyber security risks. Both of those will have serious consequences, politically and militarily.
I am not convinced that AI is improving at anything like this rate for things that can't be RLVR'd, I.e. stuff where you can't generate enormous amounts of useful training data with an answer key. Radiologists continue to do just fine for themselves despite repeated promises of doom. I'm sure someone will chime in to say that the radiologists are there for liability reasons, but it's not as if they are now just hitting thumbs up/thumbs down on AI decisions all day.
Partly this is a sample efficiency question - there simply might not be enough data for them to learn this stuff to human level, and architectural advances that improve sample efficiency may lead to huge gains in quality. But it's not clear to me why people expect this to happen.
My simplified argument, as distilled from Lesswrong (i.e. Yud) and other books.
The ceiling of capabilities for what we call 'intelligence' is extraordinarily high. Computation can be done many orders of magnitude more efficiently than you think, in the extreme case.
The floor for something 'superintelligent' (right now, I'm using the definition 'smarter than humanity itself as a collective') is substantially below that.
Human brain architecture is NOT anywhere near the most efficient way to instantiate intelligence. (This follows naturally if you accept 1.)
Humans are capable enough to build electronic hardware that can outperform their own brains in computation efficiency.
Thus, eventually, humanity might stumble into or intentionally build a coherent entity that is superintelligent, and sooner than we 'expect.'
Focus in on 4, too. What specific task do you think human brains can perform that we're MAXIMALLY efficient at, such that no electronic version can beat us?
The conceit is that there is no such task, and so its only a matter of time, and adding capabilities to existing models, until the human capabilities are exceeded on all fronts. If the resulting entity is able to do self-improvement, it by definition will do so faster and more efficiently than humanity can track.
I remain unconvinced about (1): it reads as plausible, but I don't think the existence of "superintelligence" is obvious. It seems just as likely that if intelligence is, say, predictive ability, then it could be bounded by the scale of input data with diminishing returns. As an idea, we can train a human to a decent fraction of what cutting-edge models do without needing anything near the scope of training material that the Big Kids are crunching, and with under a hundred watts for 20 years or so.
But first we'd need to iron out what intelligence is, which seems murky still beyond "I'll know it when I see it" a la the Turing test. Is it essentially connected to consciousness (what is that, too)?
I think 'intelligence' if defined in 'practical' terms is "the efficiency with which one can absorb and process the information in an environment, then utilize (or at least theorize how) the material in the local environment to achieve particular goals."
The more complex the goals one can achieve, and the more efficiently they can achieve them, the higher the intelligence.
The Von Neumann/Manhattan Project parallel I'm drawing makes this point. Given all the materials necessary to make a nuclear weapon, how quickly can a particular group of humans go from merely theorizing about the possibility to actually getting one built.
A group of humans that includes Von Neumann and other Physics PhDs, with the backing of the U.S. military, can get it done in, say, 5 years.
A similarly sized group of humans of utterly average intelligence (as measured by IQ)... probably never. Even WITH the backing of the U.S. military.
One Von Neumann and a bunch of average IQ humans... well I don't know.
A whole bunch of Von Neumans working together...
I don't think that's a terrible definition, but it still ends up bounded by the amount of information in the environment available to feed into your intelligence. A third eye would give humans "more information", but probably wouldn't improve our intelligence substantially. I'm sure there are some perfectly capable blind physicists out there.
The other question is what a bunch of Von Neumann clones could do today. IIRC the idea of an atomic bomb was at least known before the Manhattan Project started. It's hard to know in foresight what sort of advances could be made in the next five years, and which will prove intractable. It'd be awesome to solve fusion power, but it's taken well more than five years so far. I'm not sure that the geography of "the possible future" is well enough known to make great claims about what could be there: not all advances that can be seen are inherently terrible.
I expect a LOT. Assuming they could cooperate, which I think they would. This guy literally founded Game Theory among other things.
Like, the other path to superintelligence might be to clone like 10 Von Neumanns, raise them according to best practices, and get them interested in the idea of creating Friendly AI, then give them a lab with a trillion dollars in funding.
Yes yes, lets bound it to "useful," "nonredundant" information. Still, a superintelligence should be able to make use of almost all information it receives second-to-second to make accurate predictions about its future so as to better use resources for its goals.
See, lemme zero in on this for emphasis. Yes, it is indeed hard.
But the higher 'intelligence' entities, given accurate information (ensuring the information you collect is true is another aspect of intelligence!), should ALWAYS be better at making such predictions than lower intelligence ones.
High IQ humans were at least discussing Artificial Intelligence and putting forth timelines for its appearance. And I suspect realized what was happening when AlphaGo beat Sedol. If I were maybe 10 points smarter, I would have plowed money into NVDIA then and there, or at least as soon as people realized AI could run on GPUs.
Average IQ humans might now get that AI has arrived and can figure out uses for it, but would NEVER have seen it coming 5 years out, even if you showed them a complete factual article explaining the AlphaGo Sedol situation. How do I know? I TRIED VERY HARD to explain the implications back when it happened. I also tried to explain the implications when DallE first arrived on the scene. Now these folks I tried explaining to use image generators without a thought!
Low IQ humans, presumably, STILL don't really get what AI is or what it does.
This is why making falsifiable predictions and tracking their outcomes is kind of critical for smart folks to stay calibrated.
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