subsequent information reorders the evidence as though it were its original premises; thus memory does not report what happened, but what we need to have happened for our self-model to remain consistent.

accuracy an epistemic one—while collective memory is not the sum of individual recollections but an identity-constituting norm that selects what keeps the group as it takes itself to be. And because what follows an event is part of the event,

whereas history is an inferential construction subject to evidential scrutiny on the basis of independent evidence. The difficulty, then, is not that memory errs, but that it errs from a position of certainty—confidence is a psychological variable,

Accordingly, the standard of logic is internally grounded: its court of appeal is the laws of truth themselves, not the deliverances of psychology nor any externally imposed epistemic constraints.

If such reduction is unavailable, and the rule is not basic, logical inquiry halts at that boundary and does not feign what its nature does not license.

There is no outside to it: to imagine a life without ideology is to posit an existence stripped of structure and bereft of any horizon of sense—in short, a non-life.

What would this imply about the nature of mathematical knowledge and the requirements for understanding in mathematics?

In other words, if an advanced AI system discovers and proves new mathematical theorems that human mathematicians cannot fully comprehend, does the AI know these theorems in any meaningful sense?

If it is impossible, what justifies our confidence in science as a tool of knowledge? And if it is possible, how do we avoid sliding into idealism or relativism?