Speaking for myself, the main issue is that we have no idea how to do step 3, how to tell a pre-existing sovereign what to do. A task AI with limited scope can be replaced, but an optimizer has to be able to understand what is being asked of it, and if it wasn’t designed to be able to understand certain things, it won’t be possible to direct it correctly. If in 100 years the humans come up with new principles in how the AI should make decisions (philosophical progress), it may be impossible to express these principles as directions for an existing AI that was designed without the benefit of understanding these principles.
(Of course, the humans shouldn’t be physically there, or it will be too hard to say what it means to keep them safe, but making accurate uploads and packaging the 100 years as a pure computation solves this issue without any conceptual difficulty.)
A task AI with limited scope can be replaced, but an optimizer has to be able to understand what is being asked of it, and if it wasn’t designed to be able to understand certain things, it won’t be possible to direct it correctly.
It’s not clear to me why “limited scope” and “can be replaced” are related. An agent with broad scope can still be optimizing something like “what the human would want me to do today” and the human could have preferences like “now that humans believe that an alternative design would have been better, gracefully step aside.” (And an agent with narrow scope could be unwilling to step aside if so doing would interfere with accomplishing its narrow task.)
Being able to “gracefully step aside” (to be replaced) is an example of what I meant by “limited scope” (in time). Even if AI’s scope is “broad”, the crucial point is that it’s not literally everything (and by default it is). In practice it shouldn’t be more than a small part of the future, so that the rest can be optimized better, using new insights. (Also, to be able to ask what humans would want today, there should remain some humans who didn’t get “optimized” into something else.)
Speaking for myself, the main issue is that we have no idea how to do step 3, how to tell a pre-existing sovereign what to do. A task AI with limited scope can be replaced, but an optimizer has to be able to understand what is being asked of it, and if it wasn’t designed to be able to understand certain things, it won’t be possible to direct it correctly. If in 100 years the humans come up with new principles in how the AI should make decisions (philosophical progress), it may be impossible to express these principles as directions for an existing AI that was designed without the benefit of understanding these principles.
(Of course, the humans shouldn’t be physically there, or it will be too hard to say what it means to keep them safe, but making accurate uploads and packaging the 100 years as a pure computation solves this issue without any conceptual difficulty.)
It’s not clear to me why “limited scope” and “can be replaced” are related. An agent with broad scope can still be optimizing something like “what the human would want me to do today” and the human could have preferences like “now that humans believe that an alternative design would have been better, gracefully step aside.” (And an agent with narrow scope could be unwilling to step aside if so doing would interfere with accomplishing its narrow task.)
Being able to “gracefully step aside” (to be replaced) is an example of what I meant by “limited scope” (in time). Even if AI’s scope is “broad”, the crucial point is that it’s not literally everything (and by default it is). In practice it shouldn’t be more than a small part of the future, so that the rest can be optimized better, using new insights. (Also, to be able to ask what humans would want today, there should remain some humans who didn’t get “optimized” into something else.)