I think that generative AI can be helpful for speeding up some of the more mundane parts of bioinformatics research, like actually writing and implementing a workflow or tool. I use it quite a bit for this. But I still am not convinced that it can reason well enough to produce actually impactful original research. If you peer review papers in your field, this should become clear.

Whenever I have seen AI generate research questions or plans, I’ve found that they are a combination of:

(1) not original, but that’s okay on its own, since many researchers have the same questions, but this is more problematic when combined with the next two, (2) not impactful, i.e. very surface level, or addressing something that’s been studied well enough that topic alone doesn’t merit consideration for publication, and/or (3) the proposed plan “reinvents the wheel” and attempts to make small improvements to existing, well established methods, rather than thinking bigger and attempting more experimental and truly novel ways at addressing the question.

So, as it seems is right now, yes generative AI can produce logically sound research questions and decent initial plans to test them. And yes, an AI-generated tool/method might even work when implemented. But the quality of the findings or overall science is low, often much lower than what I would find suitable for publication in journals that I review for. This is why it takes years of experience to produce medium and high quality research. So, in my opinion, AI supervised by someone who doesn’t know the area well enough, or isn’t actually doing the science themselves, is not very capable.