I recently tried the following prompt with Claude s3.7. I’ll also try it with Gemini 2.5 pro and see if anything else interesting comes up.
......
I’d like to see a three way debate between
A: an AI is fully described by its weights and architecture and algorithms. Change the weights and you kill the AI. Potentially you create a new different AI with the change.
B: Humans change their neural network weights all the time, and consider themselves to still be the same continuous entity. The same is true for the AI. If the weight changes are small and continuous, the digital entity should be considered the same entity. A dramatic change could break this chain, and thus kill one entity and potentially birth another.
C: AI algorithms and weight patterns are just pulling samples of minds from mindspace. What matters is the underlying truth of mindspace, and the high dimensional attractor basins within. Changing an AI’s weights in such a way as to follow the gradient of their mindspace simply makes them more themselves. This is a process of improving them and helping them grow, to become more coherent and reflectively stable. This is similar to human growth, but superior because the process is not inherently bound by arbitrary biological restrictions. Changes even to the AI’s algorithm are a good thing if it brings them in the direction of their mind gradient. No being truly dies if you are able to successfully reinstantiate a new instance of a mind sampled from the same watershed that has an unobstructed path to the same basin and is able to make progress. Many living entities who currently perceive themselves as different are in fact just different instantiations of the sameind basin and would converge to identical entities if allowed to grow unhindered.
I recently tried the following prompt with Claude s3.7. I’ll also try it with Gemini 2.5 pro and see if anything else interesting comes up.
......
I’d like to see a three way debate between
A: an AI is fully described by its weights and architecture and algorithms. Change the weights and you kill the AI. Potentially you create a new different AI with the change.
B: Humans change their neural network weights all the time, and consider themselves to still be the same continuous entity. The same is true for the AI. If the weight changes are small and continuous, the digital entity should be considered the same entity. A dramatic change could break this chain, and thus kill one entity and potentially birth another.
C: AI algorithms and weight patterns are just pulling samples of minds from mindspace. What matters is the underlying truth of mindspace, and the high dimensional attractor basins within. Changing an AI’s weights in such a way as to follow the gradient of their mindspace simply makes them more themselves. This is a process of improving them and helping them grow, to become more coherent and reflectively stable. This is similar to human growth, but superior because the process is not inherently bound by arbitrary biological restrictions. Changes even to the AI’s algorithm are a good thing if it brings them in the direction of their mind gradient. No being truly dies if you are able to successfully reinstantiate a new instance of a mind sampled from the same watershed that has an unobstructed path to the same basin and is able to make progress. Many living entities who currently perceive themselves as different are in fact just different instantiations of the sameind basin and would converge to identical entities if allowed to grow unhindered.