In most worlds where we fail to produce value, I think we fail before we spend a hundred researcher-years. So I’m also going to include possibilities for wasting 30 researcher-years in this answer.
Here’s some reasons we might have failed to produce useful research:
We failed to execute well on research. For example, maybe we were incompetent at organizing research projects, or maybe our infrastructure was forever bad, or maybe we couldn’t hire a certain type of person who was required to make the work go well.
We executed well on research, but failed on our projects anyway. For example, perhaps we tried to implement imitative generalization, but then it turned out to be really hard and we failed to do it. I’m unsure whether to count this as a failure or not, since null results can be helpful. This seems most like a failure if the reason that the project failed was knowable ahead of time.
We succeeded on our projects, but they turned out not to be useful. Perhaps we were confused about how to think about the alignment problem. This feels like a big risk to me.
Some of the value of Redwood comes from building capacity to do more good research in the future (including building up this capacity for other orgs, eg by them being able to poach our employees). So you also have to imagine that this also didn’t work out.
It’s 2027, and Redwood has failed to be useful while spending hundreds of person-years of researcher time. What happened?
In most worlds where we fail to produce value, I think we fail before we spend a hundred researcher-years. So I’m also going to include possibilities for wasting 30 researcher-years in this answer.
Here’s some reasons we might have failed to produce useful research:
We failed to execute well on research. For example, maybe we were incompetent at organizing research projects, or maybe our infrastructure was forever bad, or maybe we couldn’t hire a certain type of person who was required to make the work go well.
We executed well on research, but failed on our projects anyway. For example, perhaps we tried to implement imitative generalization, but then it turned out to be really hard and we failed to do it. I’m unsure whether to count this as a failure or not, since null results can be helpful. This seems most like a failure if the reason that the project failed was knowable ahead of time.
We succeeded on our projects, but they turned out not to be useful. Perhaps we were confused about how to think about the alignment problem. This feels like a big risk to me.
Some of the value of Redwood comes from building capacity to do more good research in the future (including building up this capacity for other orgs, eg by them being able to poach our employees). So you also have to imagine that this also didn’t work out.