Maybe but I think these problems fall into a unique category. Those that know of the problems but don't know ML won't know how to ask or how to articulate them as ML problems. Those with ML knowledge but don't know if the problems obviously don't know they exist. Those that know the problem and ML are solving the problem themselves most of the time.

I think a list of problems is a nice idea but again I don't think those with knowledge of problems know what is a good ML problem and what isn't.

I will say I think a good blueprint for looking for these problems is to find a problem where the data for the problem is similar to a well understood problem.

For example if a problem in a niche can be framed as a seq2seq problem you can use translation models to try and solve it.

Another good one is trying to find problems that can be framed as a game. Reframing problems as games to use reinforcement learning is a good project.