The donation equivalent aspect is pretty interesting. A study probably would not allow a participant not to take a donation, so in practice it might just be however much money from the study one chooses to donate to effective causes (minus taxes; trial income is usually treated as taxable income, which is probably bad policy). I might be misunderstanding your point, though.
I’ll reiterate (this probably should’ve been worded clearer in the post), one of the arguments we make here is that assuming all participants who make it into the study are about equally useful, we think EAs are more likely to be effective as pre-participants as well. This is because the study is still under consideration: there are decisions about the study’s design that may make it go faster, and informed advocacy from earnest pre-participants could be very persuasive for regulators and ethicists who might otherwise reject certain study design decisions on paternalistic grounds. The community and shared worldview of EA makes us think EAs will, on average, be more engaged when it comes to voicing their views on study design.
This interactive model app based on the paper we mention in footnote 4 lets you tinker with a bunch of variables related to challenge model development and vaccine deployment. Based on that, and after a conversation with the lead author, we get about 200 years of life saved for every day sooner the model is developed. (The app isn’t that granular/to the day yet but it is supposed to be updated soon.) So pushing for stud decisions that condense things even by a month or two could be huge.
Thanks for reading!
The donation equivalent aspect is pretty interesting. A study probably would not allow a participant not to take a donation, so in practice it might just be however much money from the study one chooses to donate to effective causes (minus taxes; trial income is usually treated as taxable income, which is probably bad policy). I might be misunderstanding your point, though.
I’ll reiterate (this probably should’ve been worded clearer in the post), one of the arguments we make here is that assuming all participants who make it into the study are about equally useful, we think EAs are more likely to be effective as pre-participants as well. This is because the study is still under consideration: there are decisions about the study’s design that may make it go faster, and informed advocacy from earnest pre-participants could be very persuasive for regulators and ethicists who might otherwise reject certain study design decisions on paternalistic grounds. The community and shared worldview of EA makes us think EAs will, on average, be more engaged when it comes to voicing their views on study design.
This interactive model app based on the paper we mention in footnote 4 lets you tinker with a bunch of variables related to challenge model development and vaccine deployment. Based on that, and after a conversation with the lead author, we get about 200 years of life saved for every day sooner the model is developed. (The app isn’t that granular/to the day yet but it is supposed to be updated soon.) So pushing for stud decisions that condense things even by a month or two could be huge.