There is a lot of momentum in academic AI publishing to try to stop some of the worst of the BS that the author identifies. It's becoming normalized to publish code in a demo form available on a place like huggingface, which is massively improving reproducibility. Websites like paperswithcode have done similar to improve things.
But neither of these are enough to combat the plethora of issues that the author identifies and it makes me so sad, particularly once you get into publishing and see how insane peer review is from every corner of it (paper author, reviewer, conference chair). Academia truly feels like a cartel at times.
Unfortunately AI academic publishing is not representative or the general academic publishing. Luckily, AI academics are heavily influenced by the open source culture of software engineering. It's going to be hard to see the same movement in areas like drug discovery or material science
In some areas you can upload the code to github (but very few people does that anyway).
In others you need a hardware like a microscope X with a lens Y and a light Z, and use cells of W cultivated with nutrients V by the graduate student U that is the only one that can keep the cells happy. You can't just git clone & config & make it.
But neither of these are enough to combat the plethora of issues that the author identifies and it makes me so sad, particularly once you get into publishing and see how insane peer review is from every corner of it (paper author, reviewer, conference chair). Academia truly feels like a cartel at times.