Physics graduate and currently Data Analyst. Planning to enter Computational Social Science/Policy related areas.
Consider this - say the EA figured out the number of people the problem could affect negatively (i.e) the scale. Then even if there is a small probability that the EA could make a difference shouldn't they have just taken it? Also even if the EA couldn't avert the crisis despite their best attempts they still get career capital, right?
Another point to consider - IMHO, EA ideas have a certain dynamic of going against the grain. It challenged the established practices of charitable giving that existed for a long time. So an EA might be inspired by this and indeed go against the established central bank theory to work on a more neglected idea. In fact, there is at least some anecdotal evidence to believe that not enough people critique the Fed. So it is quite neglected.
"... I believe personal features (like fit and comparative advantages) would likely trump other considerations..." That is a very interesting point. Sometimes I do have a very similar feeling - the other 3 criteria are there mostly just so one doesn't base one's decision fully on personal fit but consider other things too. At the end of the day, I guess the personal fit consideration ends up weighing a lot more for a lot of people. Would love to hear from someone in 80k hours if this is wrong...
Editing to add this:
I wonder if there is a survey somewhere out there that asked people how much do they weigh each of the 4 factors. That might validate this speculation...
Thanks for linking to that OpenPhil page! It is really interesting. In fact, one of the pages that page links to talks about ABMs that rory_greig mentioned in his comment.
As someone interested in Complexity Science I find the ABM point very appealing. For those of you with a further interest in this, I would highly recommend this paper by Richard Bookstaber as a place to start. He also wrote a book on this topic and was also one of the people to foreshadow the crisis.
Also if you are interested in Complexity Science but never got a chance to interact with people from the field/learn more about it, I would recommend signing up for this event.
Sorry for digging up this old post. But it was mentioned in the Jan 2021 EA forum Prize report published today and that is how I got here.
This comment assumes that Cause Prioritization (CP) is a cause area that requires people with width(worked across different cause areas) rather than depth(worked on a single cause area) of knowledge. That is, they need to know something about several cause areas instead of deeply understanding one of them. Would love to hear from CP researchers or others who would disagree.
Maybe CP is an excellent path for some people in mid/late career. I think there could be some people in the middle of their career who have width rather than depth of knowledge. I might be wrong but it feels like the current advice for mid-career folks from 80k hours (See this 80k hours podcast episode discussion for example) seems to focus on people with skill depth alone. Further, I also think 80k hours may actually be creating people who have skill width by encouraging people to experiment with working on different cause areas until they find the best personal fit. What if we could tell them - "Experimented a lot? Have a lot of width? Try CP!"
I also feel like it would be difficult for people in their early career to rationalize working on CP. Personally, as someone in their early career, I feel like I don't fully understand even one of the cause areas of interest to EAs properly. How can I then hope to understand multiples of them, find those not yet unknown and on top of it prioritize them all!? Now, there is good reason to believe EA is a relatively young movement (majority age between 25-34) and since young people can't rationalize working on CP, we are seeing relatively lesser research on this.
Maybe as EAs grow older eventually CP research will gain steam. Maybe their depth could also give them some width. At a later stage, current EAs working on a specific cause area could feel, "Having done specialized work all these years, I am beginning to see some ways I can generalize this stuff. Maybe this generalization is the next big impactful thing I can do" and then get into CP. Maybe some EAs already realized this and have even planned their career so that they can do CP at a later stage. So this whole thing could just be a matter of time. But that doesn't mean we should not worry - what if at the stage when EAs want to generalize we don't have the structures in place for them to pursue it?
May I suggest that you also name people who strongly identify with the ideas of some of these organizations? For instance, 64,620 hourists; Glomars; Dr.Phils; The InCredibles (CrediblyGood);
Also if FHI is Bostrom's squad then they should rename their currently boringly named "Research Areas" page to Squad Goals.
Happy April Fools! :-)
Hi tamgent! Thanks for the suggestion. I have edited the post to add my thoughts on relevance to EA. I am no expert at cause prioritization, so I have tried my best to make an argument. Would love to hear your thoughts.
Nope. Its been a long time now and I had almost forgotten about it! I guess this means we should start one...
Right. I sent a message via the contact page in the EA Hub Website. Maybe I will get an update on what is going on.
Is there an Effective Altruism wiki? I found this one: http://effective-altruism.wikia.com/wiki/Effective_Altruism_Wiki but the URL that it asks you to go to doesn't take you anywhere.
I am sorta new to the EA movement. I think contributing to a wiki will help me learn more. Plus as a non-native English speaker trying to improve English writing skills, I think contributing to a Wiki can be useful to me. So where is the Wiki? If not, shouldn't we start one or improve the aforementioned wikia page?