Implicit cause prioritization
A lot of cause prioritization happens implicitly:
- By working in one cause area rather than another, people are implicitly prioritizing among causes.
- As the investigation of a cause area becomes more specialized, it might be difficult to tell apart from non-cause prioritization work in the area. For example, investigation of AI safety as a cause area may eventually begin to look like a synthesis of existing ideas or an examination of AI timelines (which is relevant even outside of a cause prioritization framework). Even if a researcher has cause prioritization at the back of their mind, they might not explicitly say they are doing prioritization work.1
It is important to keep the above in mind before concluding that not much progress is being made in cause prioritization.
See also
External links
Speaking for myself (Issa), I haven’t been very good about maintaining this wiki over the past few years (2016–2017). But it isn’t that I haven’t been working on cause prioritization. Rather, I’ve been exploring fields in cause-specific sites like AI Watch, Devec, Computing Data Project, and various timelines. And also in general learning to do research better and have more accurate beliefs about the world. I hope to at some point soon tie all this work back into an explicit cause prioritization, which will mean more activity on this wiki.↩
