I don’t think your listed points are the crux of the difference. Though maybe AI (self-)interpretability is an important one. My personal feeling is that what is important is that humans are not coherent agents with goals, we just do things, often sphexing and being random or, conversely, routine, not acting to advance any of the stated goals.
This is a great point. I don’t expect that the first AGI will be a coherent agent either, though.
As far as I can tell from my research, being a coherent agent is not an intrinsic property you can build into an AI, or at least not if you want it to have a reasonably effective ability to learn. It seems more like being coherent is a property that each agent has to continuously work on.
The reason for this is basically that every time we discover new things about the way reality works, the new knowledge might contradict some of the assumptions on which our goals are grounded. If this happens, we need a way to reconfigure and catch ourselves.
Example: A child does not have the capacity to understand ethics, yet. So it is told “hurting people is bad”, and that is good enough to keep it from doing terrible things until it is old enough to learn more complex ethics. Trying to teach it about utilitarian ethics before it has an understanding of probability theory would be counterproductive.
I agree that even an AGI would have shifting goals. But at least at every single instance of time one assumes that there is a goal it optimizes for. Or a set of rules it follows. Or a set of acceptable behaviors. Or maybe some combination of those. Humans are not like that. There is no inner coherence ever, we just do stuff we are compelled to do in the moment.
Contemporary AI agents that are based on neural networks are exactly like that. They do stuff they feel compelled to in the moment. If anything, they have less coherence than humans, and no capacity for introspection at all. I doubt that AI will magically go from this current, very sad state to a coherent agent. It might modify itself into being coherent some time after becoming super intelligent, but it won’t be coherent out of the box.
Interesting. I know very little about the ML field, and my impression from reading what the ML and AI alignment experts write on this site is that they model an AI as an agent to some degree, not just “do something incoherent at any given moment”.
I mean “do something incoherent at any given moment” is also perfectly agent-y behavior. Babies are agents, too.
I think the problem is modelling incoherent AI is even harder than modelling coherent AI, so most alignment researchers just hope that AI researchers will be able to build coherence in before there is a takeoff, so that they can base their own theories on the assumption that the AI is already coherent.
I find that view overly optimistic. I expect that AI is going to remain incoherent until long after it has become superintelligent.
I don’t think your listed points are the crux of the difference. Though maybe AI (self-)interpretability is an important one. My personal feeling is that what is important is that humans are not coherent agents with goals, we just do things, often sphexing and being random or, conversely, routine, not acting to advance any of the stated goals.
This is a great point. I don’t expect that the first AGI will be a coherent agent either, though.
As far as I can tell from my research, being a coherent agent is not an intrinsic property you can build into an AI, or at least not if you want it to have a reasonably effective ability to learn. It seems more like being coherent is a property that each agent has to continuously work on.
The reason for this is basically that every time we discover new things about the way reality works, the new knowledge might contradict some of the assumptions on which our goals are grounded. If this happens, we need a way to reconfigure and catch ourselves.
Example: A child does not have the capacity to understand ethics, yet. So it is told “hurting people is bad”, and that is good enough to keep it from doing terrible things until it is old enough to learn more complex ethics. Trying to teach it about utilitarian ethics before it has an understanding of probability theory would be counterproductive.
I agree that even an AGI would have shifting goals. But at least at every single instance of time one assumes that there is a goal it optimizes for. Or a set of rules it follows. Or a set of acceptable behaviors. Or maybe some combination of those. Humans are not like that. There is no inner coherence ever, we just do stuff we are compelled to do in the moment.
Contemporary AI agents that are based on neural networks are exactly like that. They do stuff they feel compelled to in the moment. If anything, they have less coherence than humans, and no capacity for introspection at all. I doubt that AI will magically go from this current, very sad state to a coherent agent. It might modify itself into being coherent some time after becoming super intelligent, but it won’t be coherent out of the box.
Interesting. I know very little about the ML field, and my impression from reading what the ML and AI alignment experts write on this site is that they model an AI as an agent to some degree, not just “do something incoherent at any given moment”.
I mean “do something incoherent at any given moment” is also perfectly agent-y behavior. Babies are agents, too.
I think the problem is modelling incoherent AI is even harder than modelling coherent AI, so most alignment researchers just hope that AI researchers will be able to build coherence in before there is a takeoff, so that they can base their own theories on the assumption that the AI is already coherent.
I find that view overly optimistic. I expect that AI is going to remain incoherent until long after it has become superintelligent.