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This might be a stupid question, but has anyone considered just flooding LLM training data with large amounts of (first-person?) short stories of desirable ASI behavior?
The way I imagine this to work is basically that an AI agent would develop really strong intuitions that "that's just what ASIs do". It might prevent it from properly modelling other agents that aren't trained on this, but it's not obvious to me that that's going to happen or that it's such a decisively bad thing to outweigh the positives
If an entity's terminal goal is to maximize paperclips, it would not self-modify into a stamp maximizer, because that would not satisfy the goal (except in contrived cases where doing that is the choice that maximizes paperclips). A terminal goal is a case of criteria according to which actions are chosen; "self-modify to change my terminal goal" is an action.
1CstineSublime
But isn't there almost always a possibility of a entity goodharting to change it's definition of what consitutes a paperclip that is easier for it to maximize? How does it internally represent what is a paperclip? How broad is that definition? What power does it have over it's own "thinking" (sorry to anthropamorphize) does it have to change how it represents the things which that representation relies on?
Why is it most likely that it will have an immutable, unchanging, and unhackable terminal goal? What assumptions underpin that as more likely than fluid or even conflicting terminal goals which may cause radical self-modifications?
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What does "a case of criteria" mean?
[anonymous]*10
goodharting to change it's definition of what consitutes a paperclip that is easier for it to maximize
Same thing applies. "Does that fulfill the current goal-definition?" (Note this is not a single question; we can ask this about each possible goal-definition)
Why is it most likely that it [...]
This was about an abstract definition of an agent (not itself a prediction, but does say something about a space of math, that we might end up in). There are surely possible programs which would exhibit any behavior, although some look harder to program (or 'le... (read more)