Relevance Realization as Human Comparative Advantage

It's weird that AI agents are still so poor at communicating complex information to humans; that their mathematical proofs are correct yet gobbledygook, that their software dashboards overwhelm with irrelevant true information, and that their writing buries the lede. Somehow, there's still alpha in the right prompts, the right context, and, ultimately, in a human pointing the way. What's the missing skill? I'd like to offer a cognitive science term, "relevance realization" [1] as fitting the bill. It means, roughly: "the ability to identify the information most useful for improving your understanding of the world" [2] . AIs tend to be poor at this, particularly when communicating with humans. AIs' propensity to apply more dakka isn't enough; the possibility space of the world is so vast that even millions of tokens of brilliant polymath reasoning can't narrow it alone. In contrast, Humans are still comparatively good at locating useful hypotheses by aggressively cutting down the possibility space on priors. We have a well-developed sense for what's relevant, especially what's most relevant for other Humans like ourselves. Great skill in this area lets an Einstein hunt down a theory