I believe that research is comparably efficient to much of industry, and that many of the things that look like inefficiencies are actually trading off small local gains for large global gains.
I understand “trade small local gains for large global gains” as a prescriptive principle, but does it work as a descriptive hypothesis? Why expect academics to be so much better than philanthropists at cause neutrality? When I speak to academics who aren’t also EAs, they are basically never cause neutral, and they even joke about how ridiculously non-cause-neutral everybody in academia is, and how accidental everyone’s choice of focus is, including their own.
I’m not talking about cause neutrality. My point is that even once the general problem has been decided, there are many possible approaches, and academics often do things that seem inefficient but are actually exploring the space of possible approaches (possibly by trying to better understand the objects they are studying).
What level of “general problem” do you have in mind? To a large degree I’m thinking about things like “Gosh, it took (unnecessary) centuries or decades for researchers to launch subfields to study normative uncertainty and intelligence explosion”, and that could be a “lack of cause neutrality” problem. And maybe you’re thinking instead on a smaller scale, and want to say something like “Given that people decide to work on X, they’re relatively efficient in working on X, and exploring the space within X, even if they’re completely missing normative uncertainty and intelligence explosion.”
I understand “trade small local gains for large global gains” as a prescriptive principle, but does it work as a descriptive hypothesis? Why expect academics to be so much better than philanthropists at cause neutrality? When I speak to academics who aren’t also EAs, they are basically never cause neutral, and they even joke about how ridiculously non-cause-neutral everybody in academia is, and how accidental everyone’s choice of focus is, including their own.
I’m not talking about cause neutrality. My point is that even once the general problem has been decided, there are many possible approaches, and academics often do things that seem inefficient but are actually exploring the space of possible approaches (possibly by trying to better understand the objects they are studying).
What level of “general problem” do you have in mind? To a large degree I’m thinking about things like “Gosh, it took (unnecessary) centuries or decades for researchers to launch subfields to study normative uncertainty and intelligence explosion”, and that could be a “lack of cause neutrality” problem. And maybe you’re thinking instead on a smaller scale, and want to say something like “Given that people decide to work on X, they’re relatively efficient in working on X, and exploring the space within X, even if they’re completely missing normative uncertainty and intelligence explosion.”