8.7 Is Cognitive Synergy Tricky? 159 cognitive synergy hypothesis becomes complex, but here we’re only aiming for a qualitative argument. So for illustrative purposes, we'll stick with the "10 components" example, just for communicative simplicity. Next, let’s suppose that for any given task, there are ways to achieve this task using a system that is much simpler than any subset of size 6 drawn from the set of 10 components needed for human-level AGI, but works much better for the task than this subset of 6 components (assuming the latter are used as a set of only 6 components, without the other 4 components). Note that this supposition is a good bit stronger than mere cognitive synergy. For lack of a better name, we'll call it tricky cognitive synergy. The tricky cognitive synergy hypothesis would be true if, for example, the following possibilities were true: ® creating components to serve as parts of a synergetic AGI is harder than creating compo- nents intended to serve as parts of simpler AI systems without synergetic dynamics ® components capable of serving as parts of a synergetic AGI are necessarily more complicated than components intended to serve as parts of simpler AGI systems. These certainly seem reasonable possibilities, since to serve as a component of a synergetic AGI system, a component must have the internal flexibility to usefully handle interactions with a lot of other components as well as to solve the problems that come its way. In a CogPrime context, these possibilities ring true, in the sense that tailoring an AI process for tight integration with other AI processes within CogPrime, tends to require more work than preparing a conceptually similar AT process for use on its own or in a more task-specific narrow AI system. It seems fairly obvious that, if tricky cognitive synergy really holds up as a property of human-level general intelligence, the difficulty of formulating tests for intermediate progress toward human-level AGI follows as