@Brendon_Wong the website of Unize looks interesting. Do you have a demo? It would be great to see one, once it is available
JaimeRV
Karma: 322
Thinking About Propensity Evaluations
A Taxonomy Of AI System Evaluations
List of projects that seem impactful for AI Governance
The supply gap of EA org service providers
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.
Introducing EASE, a managed directory of EA Organization Service Providers
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.
Free Cloud Automation for your EA Org
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
Announcing the Longtermism Fellowship of EA Munich—Apply!
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.
Are there any lessons learned from running this program?
And/or why did it stop?