The claim is that almost any goal implies certain sub-goals — self-preservation, resource acquisition, resistance to having the goal changed. It is one of the most influential arguments in AI safety and one of the most contested, and both facts deserve to be reported.
The argument
Stephen Omohundro set it out in 2008 as the basic AI drives; Nick Bostrom developed it as the instrumental convergence thesis. The structure is simple and its simplicity is the source of both its force and its criticism.
For almost any terminal goal G, an agent pursuing G does
better on G if it also:
