This rise is attributable, in part, to the ease of writing applications with artificial-intelligence tools.
This is definitely one of the better uses of AI. Billions are wasted every year on utterly pointless grant application writing. I have long been in favour of laws severely restricting the maximum length of scientific grant applications, but now technology has made that unnecessary. In many cases scientists simply chose not to apply for grants they might have a chance of getting because the process is so cumbersome and bureaucratic, now they can just have an LLM write it so they can get back to their actual job.
I’ve never seen an application without limits. The NIH set limits in the 90s and then further reduced them in the 00s.
There are limits, but they are still too large and preparing an ERC grant application takes weeks of fulltime work.
Months is usually closer to the thuth, many institutions also have dedicated offices to help out with the process. This really has a huge impact on who gets the funding and reduces the chances of getting ERC grants on small institutions.
I think ironically enough, the AI might actually be the tipping point that forces grant application to put tighter limits on length. Im a part of evaluating compute grant applications, and we are now getting extremely large applications regurgitating completely irrelevant information (some of which i recognized, because i helped author some best practice guides in the field). Its straining our process because we can’t ethically offload evaluating the applications to LLMs. I suspect this will be a continuous theme of time; that LLMs will highly strain all human processes that for any reason cannot be offloaded to LLMs.
I think you can ethically, if not bureaucratically, toss all the grant applications in the garbage and just look at the resumes and publication records, and you’d probably get better results in terms of ensuring the best scientists obtain funding.