I had a look at The Plan and noticed something I didn’t notice before: You do not talk about people and organization in the plan. I probably wouldn’t have noticed if I hadn’t started a project too, and needed to think about it. Google seems to think that people and team function play a big role. Maybe your focus in that post wasn’t on people, but I would be interested in your thoughts on that too: What role did people and organization play in the plan and its implementation? What worked, and what should be done better next time?
What’s the specific most-important-according-to-you progress that you (or other people) have made on your agenda? New theorems, definitions, conceptual insights, …
Any changes to the high-level plan (becoming less confused about agency, then ambitious value learning)? Any changes to how you want to become less confused (e.g. are you mostly thinking about abstractions, selection theorems, something new?)
What are the major parts of remaining deconfusion work (to the extent to which you have guesses)? E.g. is it mostly about understanding abstractions better, or mostly about how to apply an understanding of abstractions to other problems (say, what it means for a program to have a “subagent”), or something else? Does the most difficult part feel more conceptual (“what even is an agent?”) or will the key challenges be more practical concerns (“finding agents currently takes exponential time”)?
Specifically for understanding abstractions, what do you see as important open problems?
I’m writing a 1-year update for The Plan. Any particular questions people would like to see me answer in there?
I had a look at The Plan and noticed something I didn’t notice before: You do not talk about people and organization in the plan. I probably wouldn’t have noticed if I hadn’t started a project too, and needed to think about it. Google seems to think that people and team function play a big role. Maybe your focus in that post wasn’t on people, but I would be interested in your thoughts on that too: What role did people and organization play in the plan and its implementation? What worked, and what should be done better next time?
What’s the specific most-important-according-to-you progress that you (or other people) have made on your agenda? New theorems, definitions, conceptual insights, …
Any changes to the high-level plan (becoming less confused about agency, then ambitious value learning)? Any changes to how you want to become less confused (e.g. are you mostly thinking about abstractions, selection theorems, something new?)
What are the major parts of remaining deconfusion work (to the extent to which you have guesses)? E.g. is it mostly about understanding abstractions better, or mostly about how to apply an understanding of abstractions to other problems (say, what it means for a program to have a “subagent”), or something else? Does the most difficult part feel more conceptual (“what even is an agent?”) or will the key challenges be more practical concerns (“finding agents currently takes exponential time”)?
Specifically for understanding abstractions, what do you see as important open problems?