How do you see what you’re doing as different from DataKind or Bayes Impact? Why a new standalone org rather than a chapter in those existing networks?
I think it is actually great that different orgs start out on the same idea. This way, they can make experiences in parallel and share their experience to later specialize, merge or simply complement each other.
P.S.: I hear of all the orgs mentioned today for the first time, maybe someone should create a doc or something so they can be found / find each other and coordinate with the other orgs.
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.
How do you see what you’re doing as different from DataKind or Bayes Impact? Why a new standalone org rather than a chapter in those existing networks?
I think it is actually great that different orgs start out on the same idea. This way, they can make experiences in parallel and share their experience to later specialize, merge or simply complement each other.
P.S.: I hear of all the orgs mentioned today for the first time, maybe someone should create a doc or something so they can be found / find each other and coordinate with the other orgs.
I think most of these orgs know each other. CorrelAid for example was founded by someone who knew Datakind it collaborates with DataCross
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.