Funny, I am trying to use LW knowledge for IT related troubleshooting (ERP software) and usually fail, so far. I am trying to use the Solomonoff induction, to generate hypotheses and compare them to data. But data is very hard to mine. I could either investigate the whole database, as theoretically the whole could affect any routine, or try to see what routines ran and which branches of them, which IF statements were fulfilled true and which false, and this gets me to "aha the user forgot to check checkmark X in form Y". But that also takes a huge amount of time. Often only 1% of a posting codeunit runs at all, finding that is a hell. And I simply don't know where to generate hypotheses from. "Anything could fail" is not a hypothesis. We have user errors, we have bugs, and we have heck-knows-what cases.

Maybe I should try the Bayesian branch, not the Solomonoff branch. As data, evidence, is very hard to mine in this case, maybe I should look for the most frequent causes of errors, instead of trying to find evidence for the current one. This means I should keep a log, what the problem was, and what caused it.

Thank you for the concept https://en.wikipedia.org/wiki/Base_rate_fallacy I think I will spread this in the ERP community and see what happens.