I think ‘Situational Awareness’ can quite sensibly be further divided up into ‘Observation’ and ‘Understanding’.
The classic control loop of ‘observe’, ‘understand’, ‘decide’, ‘act’[1], is consistent with this discussion, where ‘observe’+‘understand’ here are combined as ‘situational awareness’, and you’re pulling out ‘goals’ and ‘planning capacity’ as separable aspects of ‘decide’.
Are there some difficulties with factoring?
Certain kinds of situational awareness are more or less fit for certain goals. And further, the important ‘really agenty’ thing of making plans to improve situational awareness does mean that ‘situational awareness’ is quite coupled to ‘goals’ and to ‘implementation capacity’ for many advanced systems. Doesn’t mean those parts need to reside in the same subsystem, but it does mean we should expect arbitrary mix and match to work less well than co-adapted components—hard to say how much less (I think this is borne out by observations of bureaucracies and some AI applications to date).
Terminology varies a lot; this is RL-ish terminology. Classic analogues might be ‘feedback’, ‘process model’/‘inference’, ‘control algorithm’, ‘actuate’/‘affect’…
Interesting! I think one of the biggest things we gloss over in the piece in how perception fits into the picture, and this seems like a pretty relevant point. In general the space of ‘things that give situational awareness’ seems pretty broad and ripe for analysis.
I also wonder how much efficiency gets lost by decoupling observation and understanding—at least in humans, it seems like we have a kind of hierarchical perception where our subjective experience of ‘looking at’ something has already gone through a few layers of interpretation, giving us basically no unadulterated visual observation, presumably because this is more efficient (maybe in particular faster?).
I like this decomposition!
I think ‘Situational Awareness’ can quite sensibly be further divided up into ‘Observation’ and ‘Understanding’.
The classic control loop of ‘observe’, ‘understand’, ‘decide’, ‘act’[1], is consistent with this discussion, where ‘observe’+‘understand’ here are combined as ‘situational awareness’, and you’re pulling out ‘goals’ and ‘planning capacity’ as separable aspects of ‘decide’.
Are there some difficulties with factoring?
Certain kinds of situational awareness are more or less fit for certain goals. And further, the important ‘really agenty’ thing of making plans to improve situational awareness does mean that ‘situational awareness’ is quite coupled to ‘goals’ and to ‘implementation capacity’ for many advanced systems. Doesn’t mean those parts need to reside in the same subsystem, but it does mean we should expect arbitrary mix and match to work less well than co-adapted components—hard to say how much less (I think this is borne out by observations of bureaucracies and some AI applications to date).
Terminology varies a lot; this is RL-ish terminology. Classic analogues might be ‘feedback’, ‘process model’/‘inference’, ‘control algorithm’, ‘actuate’/‘affect’…
Interesting! I think one of the biggest things we gloss over in the piece in how perception fits into the picture, and this seems like a pretty relevant point. In general the space of ‘things that give situational awareness’ seems pretty broad and ripe for analysis.
I also wonder how much efficiency gets lost by decoupling observation and understanding—at least in humans, it seems like we have a kind of hierarchical perception where our subjective experience of ‘looking at’ something has already gone through a few layers of interpretation, giving us basically no unadulterated visual observation, presumably because this is more efficient (maybe in particular faster?).