There's a variant of attitude (1) which I think is worth pointing out:
b) Progress studies is good and we should put resources into it, because it is a good way to reduce X-risk on the margin.
Some arguments for (1b):
Progress studies helps us understand how tech progress is made, which is useful for predicting X-risk.
The more wealthy and stable we are as a civilization, the less likely we are to end up in arms-race type dynamics.
Some technologies help us deal with X-risk (e.g. mRNA for pandemic risks, or intelligence augmentation for all risks). This argument only works if PS accelerates the 'good' types of progress more than the 'bad' ones, which seems possible.
Another thing to keep in mind that even the best studies on rapid antigen tests usually compare against PCR tests; that is, if they agree with PCR tests in all cases, the sensitivity is reported as 100%. However, the sensitivity of PCR tests is (as far as I can tell) not 100%, and can vary a lot based on factors such as how the sample is collected and transported.
Whether a SARS-CoV-2 test detects clinical disease depends on biologic factors, pre-analytic factors, and analytic performance. Someone with a large amount of virus in their nose/throat will have a positive test with a nose/throat swab. However, someone with little to no virus in their nose or throat may have a negative test even if they have virus somewhere else (like the lungs). [...] If no virus is present at the site of collection, the collection fails to get virus in the sample, or the sample is severely degraded from storage or transport (for example baking in the sun on a car dash) then the test will be negative no matter how sensitive the test is.
Then there's studies like Kucirka et al, which is summarized in a later paper via this graph of false negative rates in PCR tests:
The study concludes
If clinical suspicion is high, infection should not be ruled out on the basis of RT-PCR alone, and the clinical and epidemiologic situation should be carefully considered.
I don't know how trustworthy the Kucirka et al study is, since the false negative rates reported are a lot worse than any I've seen elsewhere. But I think the upshot is that even "gold-standard" PCR testing is messy, and we shouldn't trust studies that estimate antigen-test sensitivity by comparison to PCR (or at least adjust for low PCR sensitivity).
A different conclusion that I think is reasonable is that RT-PCR tests are a good baseline given competent administration and possibly re-testing. I don't know enough about the mechanics of testing to evaluate whether a given study does well on this or not.
Comment by atlas on [deleted post]
I don't have this impression.
In the sentence you quoted, you literally state that 80k tracks the # of calls and # of career plan changes, but doesn't track the long-run impacts of their advisees.
Comment by atlas on [deleted post]
I also downvoted for the same reason. I've looked at 80k's reports pretty closely (bc I was basing our local EA group's metrics on them) and it seemed pretty obvious to me that the counterfactual impact their advisees have is in fact the main thing they try to track & that they use for decisionmaking.
I haven't looked into the other orgs as deeply, but your statement about 80k makes me disinclined to believe the rest of the list.
Where do you get the impression that they focus mainly on # of calls?
So here's a framing that I found useful, maybe someone else will too.
Given some problem area, let's say I is the importance of the problem, defined as the total value we gain from solving the whole thing, and write p(r)∈[0,1] for the proportion of the problem solved depending on the total resources r invested (this is the graph in the post).
Now let's say R is the amount of resources that are currently being used to combat the problem. We want to estimate the current marginal value of additional resources, which is given by I⋅dpdr(R).
The ITN framework splits the second factor into tractability and neglectedness. If we write r′=rR for resources normalized by the current investment R, then
The factors on the right-hand side represent tractability T=dpdr′ and neglectedness N=1R. So we've recovered the familiar I⋅T⋅N = marginal value of additional resources.
But this feels like a kinda clumsy way to do it―it's not clear what we gain from introducing r′. Instead, we should just try to estimate dpdr(R) directly (this is the main argument I think OP is making).
Thanks for pointing that out! I should have read more carefully. I might still be reading you wrong here (if so, sorry) but it feels like this doesn't directly engage with the point.
The paragraph argues that since foundations are currently sanctioned by governments, Reich and other critics ought to respect that decision because it's democratic. I think this is a strawman of their argument; you're assuming an abstract notion of 'democraticness' that infuses everything the government does, whereas the critics don't care whether it's a democratic government that's making a bad decision―it's still a bad decision that leaves individuals with outsized power.
(And note that you can simultaneously believe that government makes some bad legislative decisions and that we would be better off by substituting private spending with gov spending).
I agree with the general point that large foundations are a force for good on net. But I also feel like you haven't engaged with the main point of critics like Rob Reich, which (as I understand it) is that philanthropic foundations are a powerful lever that wealthy people can use to build influence―a lever that can be weakened by regulating foundations.
To defend (not that they're in need of much defending) billionaire philanthropy I think you need to argue that foundations provide enough value that having them is worth empowering the wealthy. (fwiw I think this is very likely true)