JaimeRV

114Joined Aug 2021

Comments
28

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

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