Of course you are right, but these are the parts of papers not read or understood by journalists or ceo's or the public. This is leading to inappropriate and unsafe applications, and will lead to a backlash and damage. We should be as clear (at least) as the medics, promising lab results that may deliver in the future, until field tests we can't be sure.

Unfortunately the lab to field practice in ml is underspecified.

Yes, but this specific technical research paper doesn’t suffer these issues. So the original comment seemed wrongly placed here.

> Can you point to examples where this was problematically under-specified?

Not really. My comment was about how I interpreted joe_the_user's statement; I can't think of a ML or CV research paper I've read to which this criticism would apply, but I definitely can think of such news articles and startup landing pages/marketing material.

I agree about random news articles / startup landing pages where the term is thrown around imprecisely. Just seemed odd to see the original comment saying it about this linked Bayesian stats article, which doesn’t suffer this problem.