I agree with the “concept as regularity” concept. You can see that in how computers use network packets to communicate with each other. They don’t define a packet as a discrete message from another computer, they just chop it up and process it according to its regularities
This leads to problems trying to point at humans in an AI motivational system though. Which you have to build yourself.… The problem is this. Starting at the level of visual and audio input signals, build a regularity parser that returns a 1 when it apprehends a human, and 0 when it sees apprehends something else. You have to do the following, future proof it so it recognises post/trans humans as humans (else if might get confused when we seem to want to wipe ourselves out). Make sure it is not fooled by pictures, mannequins, answer phones, chat bots.
Basically you have to build a system that can abstract out the computational underpinning of what it means to be human, and recognise it from physical interaction. And not just any computational underpinning, as physics is computational there is tons of physics of our brains we don’t care about, such as exactly how we get different types of brain damage from different types of blunt trauma. So you have to build a regularity processor that abstracts what humans think are important about the computational part of humans.
If you understand how it does this, you should be able to make uploads.
We develop an understanding of what it means to be human, through interactions with humans. With a motivational system that can be somewhat gamed by static images and simulations, but one we don’t trust fully. This however leads to conflicting notions about humanity. Whether uploads are humans or not, for example. So this type of process should probably not be used for something that might go foom.
I agree with the “concept as regularity” concept. You can see that in how computers use network packets to communicate with each other. They don’t define a packet as a discrete message from another computer, they just chop it up and process it according to its regularities
This leads to problems trying to point at humans in an AI motivational system though. Which you have to build yourself.… The problem is this. Starting at the level of visual and audio input signals, build a regularity parser that returns a 1 when it apprehends a human, and 0 when it sees apprehends something else. You have to do the following, future proof it so it recognises post/trans humans as humans (else if might get confused when we seem to want to wipe ourselves out). Make sure it is not fooled by pictures, mannequins, answer phones, chat bots.
Basically you have to build a system that can abstract out the computational underpinning of what it means to be human, and recognise it from physical interaction. And not just any computational underpinning, as physics is computational there is tons of physics of our brains we don’t care about, such as exactly how we get different types of brain damage from different types of blunt trauma. So you have to build a regularity processor that abstracts what humans think are important about the computational part of humans.
If you understand how it does this, you should be able to make uploads.
We develop an understanding of what it means to be human, through interactions with humans. With a motivational system that can be somewhat gamed by static images and simulations, but one we don’t trust fully. This however leads to conflicting notions about humanity. Whether uploads are humans or not, for example. So this type of process should probably not be used for something that might go foom.