When asking about resources, a good practice might be to mention resources you’ve already come across and why those sources weren’t helpful (if you found any), so that people don’t need to recommend the most common resources multiple times.
Also, once we have an EA-relevant search engine, it would be useful to refer people to that even before they ask a question in case that question has been asked or that resource already exists.
The primary goal of both suggestions would be to make questions more specific, in-depth and hopefully either expanding movement knowledge or identifying gaps in knowledge. The secondary goal would be to save time!
The day before Giving Tuesday, I made a donation to a EA Facebook charity that had seen no donations in a few weeks. After I donated to about 3 other people donated within the next 2 hours (well before the Giving Tuesday start time). From what I remember, the total amount increased by more than the minimum amount and the individuals appeared not to be affiliated with EA, so it seems possible that this fundraiser might have somehow been raised to their attention. (Of course it’s possible that with Giving Tuesday approaching they would have donated anyway.)
However, it made think that regularly donating to fundraisers could keep them on people’s feeds inspire them to donate, and that this could be a pretty low-cost experiment to run. Since you can’t see amounts, you could donate the minimum amount on a regular basis (say every month or so—about $60 USD per year). The actual design of the experiment would be fairly straight forward as well: use the previous year as a baseline of activity for a group of EA organisations and then experiment with who donates, when they donate, and different donation amounts. If you want to get more in-depth you could also look at other factors of the individual who donates (i.e. how many FB friends they have).
Using EA Giving Tuesday’s had 28 charities that people could donate to. Of that, you could select 10 charities as your controls, and 10 similar charities (i.e. similar cause, intervention, size) as your experimental group, and recruit 5 volunteer donors per charity to donate once a month on a randomly selected day. They would make the donation without adding any explanation or endorsement.
Then you could use both the previous year’s data and the current year’s controlled charities to compare the effects. You would want to track whether non-volunteer donations or traffic was gained after the volunteer donations.
Caveats: This would be limited to countries where Facebook Fundraising is set up.
How valuable is building a high-quality (for-profit) event app for future EA conferences?
There are 6 eag(x) conferences a year. this number will probably increase over time and more conferences will come up as EA grows- I’d expect somewhere between 80-200 EA-related conferences and related events in the next 10 years. This includes cause-area specific conferences, like Catalyst and other large events.
A typical 2.5 day conference with on average ~300 attendees spending 30 hours = 9,000 man-hours would be a range of 720,000-1,800,000 man hours over 10 years. Of this time, I’d expect 90% to be taken up doing meetings, attending events, eating etc. Of the remaining 10%, so 7,200-18,000 saving 1% of this time is in the range of 7,200- 18,000 hours or roughly seems pretty useful!
For reference, 1 year of work (a 40 hours work-week for 50 weeks) = 2000 hours.
I brainstormed a list of questions that might help evaluate how promising climate change adaptation efforts would be.
Would anyone have any additions/feedback or answers to these questions?