The Talent Liquidity Paradox
In light of the recent popularity of fast grants, I think an important concept to keep in mind when thinking about funding academic research is what I have started to call "Talent Liquidity." I.e., if we get into a regime where funders can rapidly dispense money to academic labs (within ~weeks), is the supply of talent in academia sufficiently liquid that the funded academics can respond to the funding on a similar timescale? My thesis is that talent liquidity is primarily a feature of large, well-funded labs, that already have significant flexibility in their resource allocation. I.e., the labs that are most likely to be able to execute on fast grants are also those that are the least likely to need the additional funding.
Why is this? When you get a new grant, there are two ways to staff it. You can either put an existing PhD student or postdoc on the grant, or you can staff it by hiring someone. Your ability to hire a new PhD student or postdoc depends on how well-known you are in the community: better-known labs get more applicants. A new PI might take 6 months on average to find a high quality candidate; established, well-funded PIs might take only one month. Thus, the new PI is less likely to be able to execute on their fast grant project on a "fast" timescale.
The second way is to put an existing PhD student or postdoc on it. But again, this is much easier for well-established, well-funded PIs than it is for new or poorly funded labs. Simply put, poorly funded labs have relatively few grants, and thus there is typically a very clear, one-to-one correspondence between projects in those labs and individual grants. More established PIs tend to have access to more unrestricted funding sources, and tend to have many overlapping grants, so individuals can often move relatively seamlessly between grants. (I.e., some students or postdocs might be executing on two closely-related projects, while another student or postdoc is not executing on any.) PhD students and postdocs in less well-funded labs are therefore unlikely to be able to pivot onto a new project at a moment's notice, even if you give them the funding to do so.
This is a major challenge, because small grants to well-funded labs have less impact (and are probably less likely to achieve their goals) than the same grant to a poorly-funded lab. So, what is the solution to this? I'm not sure, and I'd be very interested for any feedback with thoughts about how to measure talent liquidity or validate these ideas. But as the "fast grant" idea takes hold, overcoming the talent liquidity challenge will, I think, be a key factor in determining whether fast grants actually enable new science that would not be funded otherwise, or whether they simply increase the pool of funding available in the top labs.
And here is a picture of a lighthouse: