The core B/E dichotomy rang true, but the post also seemed to imply a correlated separation between autonomous and joint success/failure modes: building couples succeed/fail on one thing together, entertaining couples succeed/fail on two things separately.
I have not observed this to be true. Experientially, it seems a little like a quadrant, where the building / entertaining distinction is about the type of interaction you crave in a relationship, and autonomous / joint distinction is about how you focus your productive energies.
Examples:
Building / Joint: (as above) two individuals building a home / business / family together
Building / Autonomous: two individuals with distinct careers and interests, who both derive great meaning from helping the other achieve their goals.
Entertaining / Joint: two individuals who enjoy entertainment and focus on that pursuit together. A canonical example might be childless couples who frequently travel, host parties, etc, or the “best friends who do everything together” couple everyone knows.
Entertaining / Autonomous: (as above) individuals with separate lives who come together for conversation, sex, etc.
I might be extra sensitive to this, my last relationship failed because my partner wanted an “EJ” relationship while I wanted a “BA” relationship, neither of which followed cleanly from the post.
Here be cynical opinions with little data to back them.
It’s important to point out that “AI Safety” in an academic context usually means something slightly different from typical LW fare. For starters, as most AI work descended from computer science, its pretty hard [1] to get anything published in a serious AI venue (conference/journal) unless you
Demonstrate a thing works
Use theory to explain a preexisting phenomenon
Both PhD students and their advisors want to publish things in established venues, so by default one should expect academic AI Safety research to have a near-term prioritization and be less focused on AGI/ex-risk. That isn’t to say research can’t accomplish both things at once, but its worth noting.
Because AI Safety in the academic sense hasn’t traditionally meant safety from AGI ruin, there is a long history of EA aligned people not really being aware of or caring about safety research. Safety has been getting funding for a long time, but it looked less like MIRI and more like the University of York’s safe autonomy lab [2] or the DARPA Assured Autonomy program [3]. With these dynamics in mind, I fully expect the majority of new AI safety funding to go to one of the following areas:
Aligning current gen AI with the explicit intentions of its trainers in adversarial environments, e.g. make my chatbot not tell users how to make bombs when users ask, reduce the risk of my car hitting pedestrians.
Blurring the line between “responsible use” and “safety” (which is a sort of alignment problem), e.g. make my chatbot less xyz-ist, protecting training data privacy, ethics of AI use.
Old school hazard analysis and mitigation. This is like the hazard analysis a plane goes through before the FAA lets it fly, but now the planes have AI components.
The thing that probably won’t get funding is aligning a fully autonomous agent with the implicit interests of all humans (not just trainers), which generalizes to the ex-risk problem. Perhaps I lack imagination, but with the way things are I can’t really imagine how you get enough published in the usual venues about this to build a dissertation out of it.
[1] Yeah, of course you can get it published, but I think most would agree that its harder to get a pure theory ex-risk paper published in a traditional CS/AI venue than other types of papers. Perhaps this will change as new tracks open up, but I’m not sure.
[2] https://www.york.ac.uk/safe-autonomy/research/assurance/
[3] https://www.darpa.mil/program/assured-autonomy