Key writings and resources
Sept-Nov. 2022: GiveWell 'change our mind' contest
Perhaps motivated by critiques, suggestions, and further analysis like those in this gitbook and the writings below... In Sept. 2022 GiveWell announced a 'change our mind' contest, with $35k in total prize.
A great deal of additional writing and work has been posted in response to this, much of which engages the issues discussed here, including Incorporating uncertainty, transparent and organized data and calculation 'pipelines', and user input of moral and other parameters. We plan to outline this work below (to do).
Tanae Rao's work, focusing on AMF
Squiggle notebook:
EA Forum brief on this here
Froolow's discussion & ex. 'refactoring'
Discussion of the approaches to uncertainty and GiveWell's processes
See also Froolow's more general discussion/critique of GiveWell's processes here
Sam Nolan's (Quri) work, focusing on GiveDirectly
Cole_haus (earlier) work
Uncertainty and sensitivity analyses of GiveWell's cost-effectiveness analyses ... by cole_haus using Python code (full model on Github here
Adjacent: Pedant/Hazelfire
Further Background and explanations
I think this 'explainer' is a step in the right direction in some ways.
The general case
Douglas Hubbard, strong 'business/layman' arguments for explicitly stating modeling uncertainty and better calibrating one's own beliefs
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