michael_nielsen

That is: there is no strong growth model or notion of competitive displacement for scientific institutions. And this means stasis and homogeneity and monoculture, a lack of organizational change and learning. This is terrible for science.

Indeed, it creates a sense that science _must_ be done this way. We must have PIs, a group is composed in such-and-such a way, scientists have a particular career path, are of a particular age, have a certain type of mentoring, produce a certain kind of output, etc.

But we could change each (or every!) one of these in radical ways.

Furthermore, it produces apathy. Every scientist has ideas for how to do things differently at the institutional level. But without a growth model for the best ideas, it's easy to feel it's not worth it, that things are forever stuck.

If you start a better grant agency, it's not going to displace the NIH. But perhaps it should.

A few ideas I like (no implied endorsement by Patrick, or originality on my part). Very telegraphic & incomplete - lots of nuance missing, and obvious problems that need to be addressed.

Figure out how new fields are produced. At the moment there's a _lot_ of inhibitory forces that slow the rate of production of new fields. Can we programmatically 2x or 10x or 100x the rate of new field production?

Tenure insurance. For a relatively small additional piece of the benefits package, tenure-track faculty are guaranteed a large payout should they fail to get tenure. It's a cheap way to de-risk the tenure process, and to encourage more risk-taking.

Almost every funder talks about supporting high-risk research. But that is often just talk. A genuinely high-risk program would evaluate failure rates for past grants, and if the failure rate was _too low_ (below 60%, say), the program officer's job would be on the line.

Finally, technology: What’s going to be the impact of AI on science? Of intelligence augmentation? Of ideas like open science? Might one or more of these dramatically speed up scientific progress?

Of course, these are just a few ideas. I believe humanity has barely begun to explore the space of possible approaches to doing science. What are the high-order bits in how we do science? What new approaches can we take to discovery?