Whether humans conspire to weed out wild carrots impacts whether humans
are
classified as Friendly (or, it would if the wild carrots were sentient).
Why does it matter what word we/they assign to this situation?
My vision of Friendliness places many more constraints on the behavior
towards other Friendly entities than it does on the behavior towards
non-Friendly entities. If we are classified as Friendly, there are many
more constraints on the behavior that they will adopt towards us. Or, to
make it more clear, substitute the words Enemy and Friend for Unfriendly and
Friendly. If you are a Friend, the Friendly AI is nice to you. If you are
not a Friend, the AI has a lot fewer constraints on how it deals with you.
It is in the future AGI overlords "enlightened self-interest" to be
Friendly -- so I'm going to assume that they will be.
It doesn't follow. If you think it's clearly the case, explain
decision process that leads to choosing 'friendliness'. So far it is
self-referential: if dominant structure always adopts the same
friendliness when its predecessor was friendly, then it will be safe
when taken over. But if dominant structure turns unfriendly, it can
clear the ground and redefine friendliness in its own image. What does
it leave you?
You are conflating two arguments here but both are crucial to my thesis.
The decision process that leads to Friendliness is *exactly* what we are
going through here. We have a desired result (or more accurately, we have
conditions that we desperately want to avoid). We are searching for ways to
make it happen. I am proposing one way that is (I believe) sufficient to
make it happen. I am open to other suggestions but none are currently on
the table (that I believe are feasible).
What is different in my theory is that it handles the case where "the
dominant theory turns unfriendly". The core of my thesis is that the
particular Friendliness that I/we are trying to reach is an "attractor" --
which means that if the dominant structure starts to turn unfriendly, it is
actually a self-correcting situation.
-------------------------------------------
agi
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