I don’t see how mechanistic and modular are different, and it’s only clear (upon reading your last point) that your analogy might be flipped. If a car breaks-down, you need to troubleshoot, which means checking that different parts are working correctly. Interpretability (which I think fails as a term because it’s very specific to math/xNN’s, and not high-level behaviors) happens at that level. Specific to the argument, though, is that these are not two different concepts. Going back to the car analogy, a spark plug and fuel injector are roughly the same size, and we can assume represent an equivalent number of neurons to function. ML fails by being focused on the per-neuron activity; and thus, AGI will be based on the larger structures. We would also ask what is wrong, in terms or elephant psychology, in trying to troubleshoot an elephants mind (how something “lights up” in a region of the brain from a scan is only a hint as to the mechanisms we need to focus on, though maybe the problem is that another area didn’t light up, etc).
“Solving” AGI is about knowing enough about the modules of the brain, and then building from scratch. ML research is about sub-module activity, while safety seems to be above module activity. None of these things are compatible with each other.
I don’t see how mechanistic and modular are different, and it’s only clear (upon reading your last point) that your analogy might be flipped. If a car breaks-down, you need to troubleshoot, which means checking that different parts are working correctly. Interpretability (which I think fails as a term because it’s very specific to math/xNN’s, and not high-level behaviors) happens at that level. Specific to the argument, though, is that these are not two different concepts. Going back to the car analogy, a spark plug and fuel injector are roughly the same size, and we can assume represent an equivalent number of neurons to function. ML fails by being focused on the per-neuron activity; and thus, AGI will be based on the larger structures. We would also ask what is wrong, in terms or elephant psychology, in trying to troubleshoot an elephants mind (how something “lights up” in a region of the brain from a scan is only a hint as to the mechanisms we need to focus on, though maybe the problem is that another area didn’t light up, etc).
“Solving” AGI is about knowing enough about the modules of the brain, and then building from scratch. ML research is about sub-module activity, while safety seems to be above module activity. None of these things are compatible with each other.