We've been informally allowing ML implementation questions, software & hardware evaluation questions, and the scope of the humanities side of the field has expanded also...
My sense is, the expansion of scope has been helpful and, in aggregate, welcomed.
- We're the general AI site, so I feel like pretty much anything we have a tag for, when it's related to AI, is within scope
For example:
terminology should definitely be on-topic and mentioned
hardware evaluation and software evaluation (libraries, frameworks, etc.) questions can be answered objectively and provide valuable information
game theory and extensions I'd personally like to see mentioned
logic seems to me to be fundamental, as does probability
The caveat is that we do want to work in conjunction with the communities with which we have overlap, and support those communities.
We feel firmly that there needs to be a Stack:AI, but we're still in the process of figuring out how to make that permanent, and so we also depend on the support of these related communities.
-----------------------
Because we also deal with the humanities, I'd want to have an explanation of what constitutes a good "soft question".
These are cases where there is not an objective answer, but answers that are sufficiently supported, ideally with citations, are legitimate.
These types of questions are a great opportunity to introduce OP's to fundamental concepts.
Data Science & AI
. $\endgroup$