I’m not convinced that academia is generally a bad place to do useful technical work. In the simplest case, you have the choice between working in academia, industry or a non-profit research org. All three have specific incentives and constraints (academia—fit to mainstream academic research taste; industry—commercial viability; non-profit research—funder fit, funding stability and hiring). Among these, academia seems uniquely well-suited to work on big problems with a long (10-20 year) time horizon, while having access to extensive expertise and collaborators (from colleagues in related fields), EA and non-EA funding, and EA and non-EA hires.
For my field of interest (longtermist biorisk), it appears that many of the key past innovations that help e.g. with COVID now come from academic research (e.g. next-generation sequencing, nanopore sequencing, PCR and rapid tests, mRNA vaccines and other platform vaccine tech). My personal tentative guess is that our split should be something like 4 : 4 : 1 between academia, industry and non-profit research (academia to drive long-term fundamental advances, industry/entrepreneurship to translate past basic science advances into defensive products, and non-profit research to do work that can’t be done elsewhere).
Crux 1 is indeed the time horizon—if you think the problem you want to work on will be solved in 20 years/it will be too late, then dropping ‘long-term fundamental advances’ in the portfolio would seem reasonable.
Crux 2 is how much academia constrains the type of work you can do (the ‘bad academic incentives’). I resonate with Adam’s comment here. I can also think of many examples of groundbreaking basic science that looks defensive and gets published very well (e.g. again sequencing innovations, vaccine tech; or, for a recent example, several papers on biocontainment published in Nature and Science).
Thanks Seb. I don’t think I have energy to fully respond here, possibly I’ll make a separate post to give this argument its full due.
One quick point relevant to Crux 2:
“I can also think of many examples of groundbreaking basic science that looks defensive and gets published very well (e.g. again sequencing innovations, vaccine tech; or, for a recent example, several papers on biocontainment published in Nature and Science).”
I think there are many-fold differences in impact/dollar between the tech you build if you are trying to actually solve the problem and the type of probably-good-on-net examples you give here.
Other ways of saying parallels of this point:
Things which are publishable in nature or science are just definitively less neglected, because you are competing against everyone who wants a C/N/S publication
The design space of possible interventions is a superset of, and many times larger than the design space of interventions which also can be published in high impact journals
We find power-laws in cost effectiveness lots of other places, and AFAIK have no counter-evidence here. Given this, even a small orthogonal component between what is incentivized by academia and what is actually good will lead to a large difference in expected impact.
I’m not convinced that academia is generally a bad place to do useful technical work. In the simplest case, you have the choice between working in academia, industry or a non-profit research org. All three have specific incentives and constraints (academia—fit to mainstream academic research taste; industry—commercial viability; non-profit research—funder fit, funding stability and hiring). Among these, academia seems uniquely well-suited to work on big problems with a long (10-20 year) time horizon, while having access to extensive expertise and collaborators (from colleagues in related fields), EA and non-EA funding, and EA and non-EA hires.
For my field of interest (longtermist biorisk), it appears that many of the key past innovations that help e.g. with COVID now come from academic research (e.g. next-generation sequencing, nanopore sequencing, PCR and rapid tests, mRNA vaccines and other platform vaccine tech). My personal tentative guess is that our split should be something like 4 : 4 : 1 between academia, industry and non-profit research (academia to drive long-term fundamental advances, industry/entrepreneurship to translate past basic science advances into defensive products, and non-profit research to do work that can’t be done elsewhere).
Crux 1 is indeed the time horizon—if you think the problem you want to work on will be solved in 20 years/it will be too late, then dropping ‘long-term fundamental advances’ in the portfolio would seem reasonable.
Crux 2 is how much academia constrains the type of work you can do (the ‘bad academic incentives’). I resonate with Adam’s comment here. I can also think of many examples of groundbreaking basic science that looks defensive and gets published very well (e.g. again sequencing innovations, vaccine tech; or, for a recent example, several papers on biocontainment published in Nature and Science).
Thanks Seb. I don’t think I have energy to fully respond here, possibly I’ll make a separate post to give this argument its full due.
One quick point relevant to Crux 2: “I can also think of many examples of groundbreaking basic science that looks defensive and gets published very well (e.g. again sequencing innovations, vaccine tech; or, for a recent example, several papers on biocontainment published in Nature and Science).”
I think there are many-fold differences in impact/dollar between the tech you build if you are trying to actually solve the problem and the type of probably-good-on-net examples you give here.
Other ways of saying parallels of this point:
Things which are publishable in nature or science are just definitively less neglected, because you are competing against everyone who wants a C/N/S publication
The design space of possible interventions is a superset of, and many times larger than the design space of interventions which also can be published in high impact journals
We find power-laws in cost effectiveness lots of other places, and AFAIK have no counter-evidence here. Given this, even a small orthogonal component between what is incentivized by academia and what is actually good will lead to a large difference in expected impact.