Yes, something along those lines. As of now, I am pretty clueless about the effects of global health and development interventions on terrestrial arthropods in the near term, and I am also quite unsure about their longterm effects.
This is a little hard for me too. Obviously, I feel a strong intuitive pull towards preventing deaths from malaria and malnutrition. In the past, I donated to GiveWell’s top charities, and wrote articles in the online newspaper of my university applauding them (here and here; you can right click, and translate to English).
If you really have that much uncertainty along that line of thinking, I’m not sure there’s too much benefit in an analysis like this
My hope was that the data about the donations could still be useful.
Just wondering how it is possible to be so unsure about the impact of global health interventions but still have „enough“ certainty regarding the positive impact of orgs like FLI? I mean there is still lots of stuff that can go wrong based on FLI interventions. Maybe that’s just the work that tipps us into an astronomical suffering scenario?
It seems rather arbitrary how you make those decisions. Imo, for this to have any value beyond being personal speculation, you should at least start to make explicit your reasoning process in more detail and also express the range of uncertainty you see. Maybe using conditionals as well to cover different scenarios.
Valuing Bill Gates philanthropy at 0 value outright without justification does not seem to be plausible or rigorous to me.
I mean there is still lots of stuff that can go wrong based on FLI interventions. Maybe that’s just the work that tipps us into an astronomical suffering scenario?
I agree longtermist interventions are quite uncertain too. Moreover, I actually think they have wider confidence intervals for reasons like the one you pointed to. However, since they explicitly try to ensure the longterm effects are positive, and I believe most of the expected effects of interventions tend to be in the future, I guess the expected value of longtermist interventions is more likely to be positive than that of neartermist ones.
Imo, for this to have any value beyond being personal speculation, you should at least start to make explicit your reasoning process in more detail and also express the range of uncertainty you see.
I explained my process:
I only spent about 5 s setting the cost-effectiveness of each donation, guessing it based solely on the name of the recipient.
I agree it is not rigorous. This was supposed to be represented by elements like the title including “very shallow analysis” and the point in the summary saying (emphasis added only here, not in the summary):
Hi Nick,
Yes, something along those lines. As of now, I am pretty clueless about the effects of global health and development interventions on terrestrial arthropods in the near term, and I am also quite unsure about their longterm effects.
This is a little hard for me too. Obviously, I feel a strong intuitive pull towards preventing deaths from malaria and malnutrition. In the past, I donated to GiveWell’s top charities, and wrote articles in the online newspaper of my university applauding them (here and here; you can right click, and translate to English).
My hope was that the data about the donations could still be useful.
Just wondering how it is possible to be so unsure about the impact of global health interventions but still have „enough“ certainty regarding the positive impact of orgs like FLI? I mean there is still lots of stuff that can go wrong based on FLI interventions. Maybe that’s just the work that tipps us into an astronomical suffering scenario?
It seems rather arbitrary how you make those decisions. Imo, for this to have any value beyond being personal speculation, you should at least start to make explicit your reasoning process in more detail and also express the range of uncertainty you see. Maybe using conditionals as well to cover different scenarios.
Valuing Bill Gates philanthropy at 0 value outright without justification does not seem to be plausible or rigorous to me.
Hi Alexander,
I agree longtermist interventions are quite uncertain too. Moreover, I actually think they have wider confidence intervals for reasons like the one you pointed to. However, since they explicitly try to ensure the longterm effects are positive, and I believe most of the expected effects of interventions tend to be in the future, I guess the expected value of longtermist interventions is more likely to be positive than that of neartermist ones.
I explained my process:
I agree it is not rigorous. This was supposed to be represented by elements like the title including “very shallow analysis” and the point in the summary saying (emphasis added only here, not in the summary):