Thank you for engaging with the EA community and carefully articulating your position and where you think EA is missing out on potential ways to do good. I highly appreciate it, and I really hope to learn more from your viewpoint. I didn’t read yet any previous discussion, or the linked article.
If you could take the time, I’d like to gauge how much you agree with the following points, which I thought throughout reading this post that you are likely to agree with but I’m not certain of it.
Strict “quantitative” analysis makes it harder to keep an open mind for new ideas which may be highly effective, but only subject to quantitative analysis after the fact.
When possible, the analysis of an intervention’s effectiveness should be a process that includes the beneficiaries and the grantees.
Furthermore, we should take the beliefs of both the grantees and the beneficiaries about the worthwhileness of the intervention as a strong indicator of the intervention’s effectiveness.
When using academic/quantitative analysis to consider solutions to global problems, the resulting solutions are wrongly biased to those that are more amenable to analysis (such as changing mechanisms and incentive systems).
You currently believe that advocating for wealth holders to be more responsible about the negative impacts of their financial actions, as written in the second section, is the best way to address “capitalism of the irresponsible kind” (which is itself a major root cause of social problems).
You believe that a better long-term path to introduce EA to potential donors is by first increasing understanding of their role in negative externalities, then act to remove or offset these externalities, and only then consider how to do the most good “EA-style”. That is, this is a better path in the sense it is more likely to eventually cause the EA-ish goal of maximizing good with proper analysis to be a dominant framework.
Using the EA/scientific methodology for addressing the problem of “capitalism of the irresponsible kind” is not likely to produce good enough results.
In particular, you think that EA as it currently stands is not likely to recommend your suggested plan to address that problem as an effective intervention.
The best ways of going forward with alternative proteins are by investing in start-up companies or similar for-profit efforts in the field.
Also, I’d love for some examples of “warm data” that you think are important and not easily subject to more scientific methodologies.
Thank you for engaging with the EA community and carefully articulating your position and where you think EA is missing out on potential ways to do good. I highly appreciate it, and I really hope to learn more from your viewpoint. I didn’t read yet any previous discussion, or the linked article.
If you could take the time, I’d like to gauge how much you agree with the following points, which I thought throughout reading this post that you are likely to agree with but I’m not certain of it.
Strict “quantitative” analysis makes it harder to keep an open mind for new ideas which may be highly effective, but only subject to quantitative analysis after the fact.
When possible, the analysis of an intervention’s effectiveness should be a process that includes the beneficiaries and the grantees.
Furthermore, we should take the beliefs of both the grantees and the beneficiaries about the worthwhileness of the intervention as a strong indicator of the intervention’s effectiveness.
When using academic/quantitative analysis to consider solutions to global problems, the resulting solutions are wrongly biased to those that are more amenable to analysis (such as changing mechanisms and incentive systems).
You currently believe that advocating for wealth holders to be more responsible about the negative impacts of their financial actions, as written in the second section, is the best way to address “capitalism of the irresponsible kind” (which is itself a major root cause of social problems).
You believe that a better long-term path to introduce EA to potential donors is by first increasing understanding of their role in negative externalities, then act to remove or offset these externalities, and only then consider how to do the most good “EA-style”. That is, this is a better path in the sense it is more likely to eventually cause the EA-ish goal of maximizing good with proper analysis to be a dominant framework.
Using the EA/scientific methodology for addressing the problem of “capitalism of the irresponsible kind” is not likely to produce good enough results.
In particular, you think that EA as it currently stands is not likely to recommend your suggested plan to address that problem as an effective intervention.
The best ways of going forward with alternative proteins are by investing in start-up companies or similar for-profit efforts in the field.
Also, I’d love for some examples of “warm data” that you think are important and not easily subject to more scientific methodologies.