I'm not a scientist at all, but I am often involved in hand-holding scientists when it comes to dealing with computers. My impression so far is that science is

I'm not a scientist at all, but I am often involved in hand-holding scientists when it comes to dealing with computers. My impression so far is that science is plagued with deliberate and accidental fraud when it comes to data collection and cataloguing. Also, this is a spectrum, not two distinct things. I often see researchers simply unwilling to do the right thing to verify that the data collected are correct and meaningful as soon as "workable" results can be produced from the data. Some will go further and mess with the data to make results more "workable" though... Second problem is understanding the data. Often times it happens that people who end up doing research don't quite understand the subject matter of the research. This is especially popular with medicine, where it's overwhelmingly common for eg. research into various imaging modalities to be done by computer scientists who couldn't find a liver cancer the size of a coconut in the sharpest textbook abdominal image. My impression is also that by far these two problems outweigh the problems that could potentially be solved by adding AI into the mix. These are the systemic organization problems of perverse incentives and vicious practices, and no amount of AI is going to do anything about it... because it's about people. People's salaries, careers, friendships etc.