Are there any lessons learned from running this program?
And/or why did it stop?
JaimeRV
Karma: 400
@Brendon_Wong the website of Unize looks interesting. Do you have a demo? It would be great to see one, once it is available
Would it be possible to organise sessions in other timezones if there is demand for it? Like Europe, India,...
@Brendon_Wong @Quinn @Coleman did anything come out from this? I would be interested in knowledge graphs for personal knowledge management as well as for KM within the EA community.
This is very helpful, thanks for doing it!
How is the maintenance of the site planned?
Is there a person in charge of periodically checking the different sources of grants and updating the page, or is there something automated?
As a possible feature it would be nice if it would show somewhere when this database was last updated :)
Thanks for the comment Simon. In principle you can automate almost everything in the cloud. Besides, we specialize in Data Science services so in the part “What are some example projects?” we emphasize to make a short meeting, because the needs of each organization are different and we can advise better knowing a little bit about the organization.
They all offer free or strongly discounted services for EA Orgs.
More professional services:
SEADS offers Data Science services to EA organizations
User-Friendly is an EA-aligned marketing agency
Anti Entropy offers services related operations for EA organizations
Together with Altruistic Agency these Agencies are working together to form an umbrella organisation but more info on this will soon be announced
Very good post! I agree with most of the points and the framing helps to see where there is room for improvement
Regarding this sentence: “In practice, it seems that many physical hubs but one virtual/intellectual hub may be best.”
Do you have any particular thoughts on how to optimize a virtual hub or Schelling point?
For example, EAGx Virtual will take place in October and there might be some things that could make it a better Schelling point.
You are right that we could have phrased it better. However, it is not about convincing people of specific conclusions but about engaging in a deeper way with the topic. Every week there will be open discussions and the last week deals explicitly with Criticisms of longtermism
I think most of these orgs know each other. CorrelAid for example was founded by someone who knew Datakind it collaborates with DataCross
I imagine most orgs have a long tail of data science projects which aren’t important enough to go through the hassle of hiring a consultant, but that would still add some value. Meanwhile, students are in constant search of important real world problems to work on for their research or clubs (I was in Cornell Data Science) but generally don’t have a good idea of what would actually be useful. Having a place where orgs can just write down such problems and students/academics can find them seems like it would potentially unlock a lot of value.
I definitely agree. Optimally SEADS will provide this list of impactful projects.
Based on feedback of pitching a similar idea at EAG, most of the value isn’t actually in the object level work, but in identifying altruistic technical talent and getting them more engaged in high impact cause areas (and eventually into the hiring pipeline). Having lots of undergrads and PhD students working on EA style data problems seems like a good way of doing this.
Hiring for EA is also on our list of “Possible directions for the future”. Working hand-in-hand with talented and motivated volunteers seems like a good way to gauge someone’s suitability for a long-term position.
“Introduction SEADS” is at the top of the post :) but you are right and with some restructuring it would have been clearer.
At the moment the main difference is that we are focused on EA projects exclusively, either coming from EA Orgs or related to infrastructure.
A couple more differences:
- The model of this organizations is rather fixed with a very strong focus on being the middle man between projects and volunteers. We would like to experiment with new approaches as mentioned under “Possible directions for the future”
- Some of these organizations tend to have also a big focus on learning, meaning including participants in their teams that are not very experienced and also taking projects that are not very impactful but fit very well the skills of some of their volunteers. Atm we aim to have a much stronger focus on impact and less on teaching people how to do data science.
Great article! Here another list from the study-buddy channel in the Virtual Programs Slack workspace. The channel is made to promote self-study of this kind of EA material. https://bit.ly/3rblLj1
Looking forward! I really think this can be as good or better than in person EAG(x)s
From the reasons to avoid engaging in interpersonal conflict ” i) isn’t going to change anyone’s actions much; ii) isn’t going to make the world a much better place, even if it does change their actions; or iii) is very hard to persuade others about”.
I think even if all of these apply it might be worth it to engage in interpersonal conflict if you can learn from it. Discussing with someone and then reflecting on the discussion and how you discussed can help you improve how you handle these conflicts. If the cost of interpersonal tension is not too high it is a price worth paying for your improvement.
Thanks for the info!
Great post! The “list of EA-aligned organizations” seems very useful. Do you know if it is linked to some more official EA source like the CEA website or 80k website? and do you know how up to date it is?
Initially it seems like core EA information that is hanging in a random Notion page but I am probably wrong
It would be amazing if one could use it with a local LM in LMStudio