A couple of chess observations related to epistemology and alignment.
Take the starting chess position. Remove the black queen.
rnb1kbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1
https://lichess.org/analysis/rnb1kbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR_w_KQkq_-_0_1
It's overwhelmingly likely that White is winning.
But just how sure should we be of that, epistemically? We don't have a mathematical proof yet.
Even more absurd question: how sure should we be that Black is not winning? There's no mathematical proof of that either.
I claim that every educated chess player should believe that White is winning, (almost) as certainly as if they had a mathematical proof. Like, I mean that it should be much more certain than mathematicians' consensus on P vs. NP or Goldbach's conjecture or the twin prime conjecture etc.
Reasons to believe:
Basically, I'm saying our knowledge of chess positions is "exhaustive" on the level of approximation of being up/down an entire queen. There's not enough place to squeeze enough uncertainty that Black could survive, let alone win.
Conclusion: there's an intersection between statistical reasoning and logic; informal reasoning has structure which can be studied.
Consider the following heuristic:
"Material advantage often leads to winning a game (X)"
Now, consider a combination of heuristics:
"Material advantage often leads to winning a game (X), because it often allows to win more material by overwhelming the defences (Y) and certain amount of material advantage guarantees a win under normal conditions (Z)"
Y and Z are additional heuristics (mixed with logic) which help to evaluate how much X is true in a specific situation. I.e. if you notice that your material advantage doesn't help to win more material, it's a sign that X is not true in your situation (probably because the opponent has built a fortress).
Conclusion: informal reasoning has structure which might look like "try to fill the gaps between a heuristic (X) and certain knowledge with auxiliary heuristics (which describe assumptions about the way X works)".
Though that requires your goal to be well-defined (like "give checkmate") and heuristics defined over a shared ontology and knowing how to find good auxiliary heuristics.