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at the risk of wading into epistemology (of which i'm certainly no expert), inferential statistics never claims to determine truth. it's a way of taking large s

at the risk of wading into epistemology (of which i'm certainly no expert), inferential statistics never claims to determine truth. it's a way of taking large sample sets and examining them mathematically to find little patterns in the data that may or may not support (but never confirm) a hypothesis. it's a powerful tool but that's all it does. it's still up to our brains to try to make that last leap between data and prediction, which is something our brains are exceedingly good at, if necessarily flawed (in a schrödinger's cat kind of way). gödel (among others) helped us find the limits of logical systems like this. i've mentioned it before (in https://news.ycombinator.com/item?id=8169025 https://news.ycombinator.com/item?id=8169025) but i'm really looking forward to the development of non-logic based math (quantum computing?) that's more akin to how our brains work and allows for multiple, conflicting "truths" to exist simultaneously. our consciousness lives in the rational world but the rest of our brains seems to be quite content with an ambiguous, entangled reality.

t__r 12y ago
What do you mean with non-logic? I think that's hard to define. There are various approaches in logic-based AI that aim to somehow be more akin to how we handle multiple conflicting truths. A popular formalism is abstract argumentation theory, which is the study of evaluating the acceptability of multiple conflicting arguments. It has been shown that this is closely related to non-monotonic logics, such as LP with negation as failure and various types of defeasible reasoning. Proof theoretically, it replaces the notion of proof with that of a successful strategy in a two-person dialogue game.