Learning process must be accompanied with enough space for an individual to realistically challenge himself to actually acquire that knowledge with foreseeable success of doing it. A person must believe s/he can really learn something. But in this status quo of AI hypeism (believing that knowing refined set of know-hows would be enough) people gradually begin losing that optimistic "a priori" belief to learn things.

But another side effect of this process is if people stop believing in the accrual of the knowledge which will lead them to nowhere (use cases for those information becoming irrelevant by the time you start using it), justifying this mentally exhausting practice becomes really hard. And I don't mean this on learning static information but also on how to define and build a meta-cognitive framework to systemically learn things.

I don't quite get the "lifelong learning" approach, since lifelong learning must usually be accompanied with organic evolution of the information space. Employers wont pay you because you are a lifelong learner, they'll pay you to actually fix a problem you provide a solution for. And that solution isn't guaranteed by the knowledge you possess and doesn't usually qualify the marginal cost of being a lifelong learner.

One could brain storm on these issues by critiquing the premise of this book: https://www.amazon.com/100-Year-Life-Living-Working-Longevit...