the problem is two-fold in my opinion.
firstly, there are basically no legal repercussions for scientific misconduct (e.g. falsifying data, fake images, etc.). most individuals who are caught doing this get either 1) a slap on the wrist if they are too big to fail or in the employ of those who are too big to fail or 2) disbarred, banned, and lose their jobs. i don't see why you can go to jail for lying to investors about the number of users in your app but don't go to jail for lying to the public, government, and members of the scientific community about your results.
secondly, due to the over production of PhD's and limited number of professorship slots competition has become so incredibly intense that in order to even be considered for these jobs you must have Nature, Cell, and Science papers (or the field equivalent). for those desperate for the job their academic career is over either way if they caught falsifying data or if they don't get the professorship. so if your project is not going the way you want it to then...
sad state of things all around. i've personally witnessed enough misconduct that i have made the decision to leave the field entirely and go do something else.
every few months i like to ask chatgpt to do the "thinking" part of my job (scientist) and see how the responses stack up.
at the beginning 2022 it was useless because the output was garbage (hallucinations and fake data).
nowadays its still useless, but for different reasons. it just regurgitates things already known and published and is unable to come up with novel hypotheses and mechanisms and how to test them. which makes sense, for how i understand LLMs operate.
i am very glad to see others (presumably non-scientists) in this thread dunking on the false paradigm that "peer review = true". anyone who peddles this notion is naive or a moron.
while the author is correct that the for-profit publishing is definitely a negative externality, i can't help but feel they are missing the forest for the trees when it comes to all the other worse issues in academia.
a full explanation of which would be much too onerous for a hn comment, but in no particular order: rampant scientific fraud, waste of tax payer dollars, wage suppression via "students" and visa-dependent laborers (J1 visa abuse), publish or perish evaluation criteria, lack of management training, blatant and rampant racism, etc. etc. etc.
the whole system needs to burn down and be rebuilt from the ground up.