I expect that Ryan means to say one of the these things:
There isn’t enough funding for MATS grads to do useful work in the research directions they are working on, that have already been vouched for by senior alignment researchers (especially their mentors) to be valuable. (Potential examples: infrabayesianism)
There isn’t (yet) institutional infrastructure to support MATS grads to do useful work together as part of a team focused on the same (or very similar) research agendas, and that this is the case for multiple nascent and established research agendas. They are forced to go to academia and disperse across the world instead of being able to work together in one location. (Potential examples: selection theorems, multi-agent alignment (of the sort that Caspar Oesterheld and company work on))
There aren’t enough research managers in existing established alignment research organizations or frontier labs to enable MATS grads to work on the research directions they consider extremely high value, and would benefit from multiple people working together on (Potential examples: activation steering)
I’m pretty sure that Ryan does not mean to say that MATS grads cannot do useful work on their own. The point is that we don’t yet have the institutional infrastructure to absorb, enable, and scale new researchers the way our civilization has for existing STEM fields via, say, PhD programs or yearlong fellowships at OpenAI/MSR/DeepMind (which are also pretty rare). AFAICT, the most valuable part of such infrastructure in general is the ability to co-locate researchers working on the same or similar research problems—this is standard for academic and industry research groups, for example, and from experience I know that being able to do so is invaluable. Another extremely valuable facet of institutional infrastructure that enables researchers is the ability to delegate operations and logistics problems—particularly the difficulty of finding grant funding, interfacing with other organizations, getting paperwork handled, etc.
I keep getting more and more convinced, as time passes, that it would be more valuable for me to work on building the infrastructure to enable valuable teams and projects, than to simply do alignment research while disregarding such bottlenecks to this research ecosystem.
@Elizabeth, Mesa nails it above. I would also add that I am conceptualizing impactful AI safety research as the product of multiple reagents, including talent, ideas, infrastructure, and funding. In my bullet point, I was pointing to an abundance of talent and ideas relative to infrastructure and funding. I’m still mostly working on talent development at MATS, but I’m also helping with infrastructure and funding (e.g., founding LISA, advising Catalyze Impact, regranting via Manifund) and I want to do much more for these limiting reagents.
Also note that historically many individuals entering AI safety seem to have been pursuing the “Connector” path, when most jobs now (and probably in the future) are “Iterator”-shaped, and larger AI safety projects are also principally bottlenecked by “Amplifiers”. The historical focus on recruiting and training Connectors to the detriment of Iterators and Amplifiers has likely contributed to this relative talent shortage. A caveat: Connectors are also critical for founding new research agendas and organizations, though many self-styled Connectors would likely substantially benefit as founders by improving some Amplifier-shaped soft skills, including leadership, collaboration, networking, and fundraising.
I expect that Ryan means to say one of the these things:
There isn’t enough funding for MATS grads to do useful work in the research directions they are working on, that have already been vouched for by senior alignment researchers (especially their mentors) to be valuable. (Potential examples: infrabayesianism)
There isn’t (yet) institutional infrastructure to support MATS grads to do useful work together as part of a team focused on the same (or very similar) research agendas, and that this is the case for multiple nascent and established research agendas. They are forced to go to academia and disperse across the world instead of being able to work together in one location. (Potential examples: selection theorems, multi-agent alignment (of the sort that Caspar Oesterheld and company work on))
There aren’t enough research managers in existing established alignment research organizations or frontier labs to enable MATS grads to work on the research directions they consider extremely high value, and would benefit from multiple people working together on (Potential examples: activation steering)
I’m pretty sure that Ryan does not mean to say that MATS grads cannot do useful work on their own. The point is that we don’t yet have the institutional infrastructure to absorb, enable, and scale new researchers the way our civilization has for existing STEM fields via, say, PhD programs or yearlong fellowships at OpenAI/MSR/DeepMind (which are also pretty rare). AFAICT, the most valuable part of such infrastructure in general is the ability to co-locate researchers working on the same or similar research problems—this is standard for academic and industry research groups, for example, and from experience I know that being able to do so is invaluable. Another extremely valuable facet of institutional infrastructure that enables researchers is the ability to delegate operations and logistics problems—particularly the difficulty of finding grant funding, interfacing with other organizations, getting paperwork handled, etc.
I keep getting more and more convinced, as time passes, that it would be more valuable for me to work on building the infrastructure to enable valuable teams and projects, than to simply do alignment research while disregarding such bottlenecks to this research ecosystem.
@Elizabeth, Mesa nails it above. I would also add that I am conceptualizing impactful AI safety research as the product of multiple reagents, including talent, ideas, infrastructure, and funding. In my bullet point, I was pointing to an abundance of talent and ideas relative to infrastructure and funding. I’m still mostly working on talent development at MATS, but I’m also helping with infrastructure and funding (e.g., founding LISA, advising Catalyze Impact, regranting via Manifund) and I want to do much more for these limiting reagents.
Also note that historically many individuals entering AI safety seem to have been pursuing the “Connector” path, when most jobs now (and probably in the future) are “Iterator”-shaped, and larger AI safety projects are also principally bottlenecked by “Amplifiers”. The historical focus on recruiting and training Connectors to the detriment of Iterators and Amplifiers has likely contributed to this relative talent shortage. A caveat: Connectors are also critical for founding new research agendas and organizations, though many self-styled Connectors would likely substantially benefit as founders by improving some Amplifier-shaped soft skills, including leadership, collaboration, networking, and fundraising.