This is really great. I found myself most often understanding and agreeing with your rationale for eliminating and ranking interventions. Very excited to see what comes of this.
I find it somewhat interesting that a few interventions seem to have been eliminated due to the complications associated with creating behavior change, and yet two of the four highest rated are in behavior change. What distinguishes those two from the others that were rejected?
In your summary spreadsheet image, I don’t see a category for neglectedness. Is that incorporated into ‘other factors’? I have a weak, non-evidence based impression that there’s been a lot of movement on malnutrition recently and was looking to check that with your findings.
How do you plan on implementation? Is there a write-up somewhere? Reading about it being your first times in a developing country makes me naturally skeptical of your ability to implement in the field.
How much time/effort is Charity Science focusing on this? Just wondering how it ranks with other priorities and if there was specific donor interest / influx that allowed for greater resourcing to add this to your priorities.
I encourage you to explore outside of India. Poverty looks and feels very different in every place I’ve experienced and interacted with it, and I feel like I learn more each time. Some places with extreme poverty are much easier to live in than India too, and so you may not experience the productivity losses you felt there.
Complexity of behavior changes was a negative point on something, but if something was sufficiently cost effective, flexible, etc, it could still end up as one of our top interventions
We did originally have a separate section for neglectedness but we combined it into
scalability part way through our research. We found many areas that had many orgs working in an area (thus low neglectedness) but the problem was so large or wide spread there was still plenty of room for effective charities. We found that combining the total amount of unfilled room into a counterfactual scalability score ended up being more intuitive for us.
Implementation will vary alot depending on the area we end up working in, but in all cases we will be hiring and partnering with locals and domain experts to run an effective charity. I think being skeptical of charities until they prove themselves is a good and rare epistemic habit, although I did not find developing world experience correlated particularly well with the high impact charities I interviewed.
Charity Science is basically a separate organization from Charity Entrepreneurship, although they are both under the broader brand (a bit like GWWC and 80k). They both have their own dedicated staff and budgets, although I spend some hours on both. We have had pretty good donor interest in both projects. I would say the big thing that allowed CE to happen was our senior staff deciding it was the highest value thing they could put time into.
I definitely believe that there is a lot of range in poverty. We saw huge differences in different cities in India. I imagine that we could keep learning almost indefinitely from different places. We do plan on getting a better sense of the developing world once we have a specific location picked where we think it would be highest impact to run the pilot for our charity.
I would be really interested to hear what countries you think would have more mild productivity losses and in what ways they differ from India.
Thanks for all of the clarifications / explanations. This definitely helps provide more context and understanding to the story of how this originated and is progressing.
“I would be really interested to hear what countries you think would have more mild productivity losses and in what ways they differ from India.”
Southeast Asia (Thailand, Laos, Vietnam) is probably the ‘easiest’ place to work that is relevant to the interventions we often look at. Very strong internet, low costs, easy to travel, usually clean, and usually very high accessibility to high quality, safe, and tasty food. (Some of this likely applies to parts of Malaysia, Philippines, and Indonesia as well, but I’m not sure).
My (limited) experiences in East Africa had both positives and negatives in terms of productivity v. India. It was very difficult to find strong internet, but the ease of life, cleanliness, and quality of food (esp. Ethiopia) exceeded what I most often found in India.
This is really great. I found myself most often understanding and agreeing with your rationale for eliminating and ranking interventions. Very excited to see what comes of this.
I find it somewhat interesting that a few interventions seem to have been eliminated due to the complications associated with creating behavior change, and yet two of the four highest rated are in behavior change. What distinguishes those two from the others that were rejected?
In your summary spreadsheet image, I don’t see a category for neglectedness. Is that incorporated into ‘other factors’? I have a weak, non-evidence based impression that there’s been a lot of movement on malnutrition recently and was looking to check that with your findings.
How do you plan on implementation? Is there a write-up somewhere? Reading about it being your first times in a developing country makes me naturally skeptical of your ability to implement in the field.
How much time/effort is Charity Science focusing on this? Just wondering how it ranks with other priorities and if there was specific donor interest / influx that allowed for greater resourcing to add this to your priorities.
I encourage you to explore outside of India. Poverty looks and feels very different in every place I’ve experienced and interacted with it, and I feel like I learn more each time. Some places with extreme poverty are much easier to live in than India too, and so you may not experience the productivity losses you felt there.
Complexity of behavior changes was a negative point on something, but if something was sufficiently cost effective, flexible, etc, it could still end up as one of our top interventions
We did originally have a separate section for neglectedness but we combined it into scalability part way through our research. We found many areas that had many orgs working in an area (thus low neglectedness) but the problem was so large or wide spread there was still plenty of room for effective charities. We found that combining the total amount of unfilled room into a counterfactual scalability score ended up being more intuitive for us.
Implementation will vary alot depending on the area we end up working in, but in all cases we will be hiring and partnering with locals and domain experts to run an effective charity. I think being skeptical of charities until they prove themselves is a good and rare epistemic habit, although I did not find developing world experience correlated particularly well with the high impact charities I interviewed.
Charity Science is basically a separate organization from Charity Entrepreneurship, although they are both under the broader brand (a bit like GWWC and 80k). They both have their own dedicated staff and budgets, although I spend some hours on both. We have had pretty good donor interest in both projects. I would say the big thing that allowed CE to happen was our senior staff deciding it was the highest value thing they could put time into.
I definitely believe that there is a lot of range in poverty. We saw huge differences in different cities in India. I imagine that we could keep learning almost indefinitely from different places. We do plan on getting a better sense of the developing world once we have a specific location picked where we think it would be highest impact to run the pilot for our charity.
I would be really interested to hear what countries you think would have more mild productivity losses and in what ways they differ from India.
Thanks for all of the clarifications / explanations. This definitely helps provide more context and understanding to the story of how this originated and is progressing.
“I would be really interested to hear what countries you think would have more mild productivity losses and in what ways they differ from India.”
Southeast Asia (Thailand, Laos, Vietnam) is probably the ‘easiest’ place to work that is relevant to the interventions we often look at. Very strong internet, low costs, easy to travel, usually clean, and usually very high accessibility to high quality, safe, and tasty food. (Some of this likely applies to parts of Malaysia, Philippines, and Indonesia as well, but I’m not sure).
My (limited) experiences in East Africa had both positives and negatives in terms of productivity v. India. It was very difficult to find strong internet, but the ease of life, cleanliness, and quality of food (esp. Ethiopia) exceeded what I most often found in India.