First, it’s not really the case that EAs use QALYs/DALYs. GWWC and GiveWell used to use them, but GWWC no longer exists as an independent entity and GiveWell now use their own metric.
This is a good point.
I think that GWWC & GiveWell’s earlier use of QALYs created a lot of path dependence, such that current EA prioritization remains influenced by the QALY framework even though no organization explicitly uses it at present.
Considering an alternate timeline can help draw out the path dependence:
Imagine a world where the DCP project started in 2019, rather than 1993. In 2019, lots of people have smartphones, so experience sampling is a viable method.
The DCP researchers decide to use experience sampling instead of retrospective surveys to determine QALY weights.
Because they’re using experience sampling, mental health disorders are more highly weighted in the DCP.
In this world, GiveWell gets started in 2026. GiveWell takes a look at the DCP research, and sees that mental health disorders are highly weighted. So, they decide to prioritize research into mental health interventions.
Even after GiveWell moves away from the DCP weightings (in 2036, or whenever), mental health interventions remain their main focus, because that’s where they have the most granular models & the strongest network.
I think that GWWC & GiveWell’s earlier use of QALYs created a lot of path dependence, such that current EA prioritization remains influenced by the QALY framework even though no organization explicitly uses it at present.
I find this to be the most plausible explanation of what has happened. Your counterfactual story is rather helpful!
This is a good point.
I think that GWWC & GiveWell’s earlier use of QALYs created a lot of path dependence, such that current EA prioritization remains influenced by the QALY framework even though no organization explicitly uses it at present.
Considering an alternate timeline can help draw out the path dependence:
I find this to be the most plausible explanation of what has happened. Your counterfactual story is rather helpful!