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Guys, I think I’ve found the source of the Adderall shortage.
You’re very attached to this idea that GPT can’t model systems, that it has a gestalt of “things a human would do” and pulls out the most common one, conditioned on its current situation. @DaseindustriesLtd has some good reasons why that may not be the case. But you’re missing the forest for the trees.
What does AI need in order to be dangerous?
It gets speed for free. It gets durability, or at least redundancy, so long as anyone can instantiate it. It can capably mimic a human in familiar situations, and because lots of the training data includes humans encountering unfamiliar situations, it can ape our behavior there, too. Does it really matter if it we meatbags can extract an internal conceptual model?
No, the bottleneck is I/O. Hook up current AI to a speech parser, who cares. Hook it up to the early-warning radar and you start to add risk. Hang the global financial system on it, and there will be trouble. We make tools because they are useful to humans. That will also make them useful to an AI which credibly imitates a human.
Sophistry over whether the AI really “knows” what it’s doing will be cold comfort indeed.
"Dangerous" in the sense that aviation or being out on open water is dangerous? Or dangerous in the sense that rationalist usually mean when they talk about the so-called "AI alignment problem"?
Yes.
In the case of the former, nothing. Not only are we already there, We've been here for a century. Computer glitches and poorly designed/understood control functions have been getting people killed as long as there have been computers.
In the case of the latter, agency, and the physical/perceptual capabilities of a kindergartener strike me as the bare minimum.
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