Hi there! I’m a physician living in Brazil. I’m currently enrolled in an online MicroMasters in Statistics and Data Science at MITx.
Diego Oliveira
Karma: 43
Thanks a lot for this carefully compiled information! May all sentient beings benefit from the actions that you folks are organizing there!
Thank you, Ian, for asking the question that was in the back of my mind while I was reading this well-written and accessible post by ryancbriggs. I think it would be nice if the OP could add this caveat (that the evidence concerns a specific type of aid), since I assume some of the people reading this post in the EA forum will possibly update unjustly against aid recommended by, for instance, GiveWell.
Thank you very, very much for your input, Lorenzo! Very helpful as always. Keep up the good work!
Hi! I have some basic questions that I believe there are well-documented resources I could be linked to. As far as I know, there are currently four EA-aligned meta-charities, i.e., charities that evaluate and recommend other charities based on EA’s core values: GiveWell, Animal Charity Evaluators, Giving What We Can, and The Life You Can Save. I have the following questions:
(1) Did I miss any other EA-aligned meta-charity?
(2) What are the differences in their evaluation process? I get that GiveWell deals mainly with global health in developing countries, and Animal Charity Evaluators works in the Animal Welfare domain. Apart from that, what are the other differences? Maybe another way to put the question is: Why don’t they have a single list of recommendations?
(3) A simple Google Search returns some meta-charities that are not EA-aligned, like Charity Navigator and Charity Watch. How exactly do these meta-charities differ from the EA-aligned ones?
Hi, Lorenzo! Thank you, once again, for your kindness!
Hi! Does anybody know where the figure for cataract surgery ($1,000/severe visual impairment reversed) comes from? Is it one eye, or both eyes? I’m making a presentation and I’d like to be assured that the figures are as correct as possible.
For instance, this 2011 article (https://bmchealthservres.biomedcentral.com/articles/10.1186/1472-6963-13-480) provides the following information:
“The average cost of cataract surgery [in Southern Ethiopia] in 2010 was US$141.6 (Range: US$37.6–312.6)”.
Thanks for clarifying this! I really had interpreted it as a threat from funders.
Based on the readings in previous chapters, which global problems do you think are most pressing and why? (Remember, experts are quite uncertain about this question!)
Biorisks: Whether through a bioweapon, a lab leak, or a naturally occurring pandemic, I believe that dangerous microorganisms that spread globally and cause immense amounts of suffering and deaths are very plausible (since it has already happened and we’re increasing the potential for bioweapons and lab leaks as technology progresses)
Nuclear War: Given the constant tension in international relations that seems to permeate History and the fact that these nuclear warheads already exist and can easily be deployed, it would not be a surprise if a full nuclear war between two nations would eventually unfold and lead to hundreds of millions of deaths, and many more injured people (let alone a potentially catastrophic Nuclear Winter).Global poverty: Over 4,000,000,000 people (±50% of the world population) have to survive daily on less resources than $6.7 dollars can buy in the US (for comparison, the US poverty line is below $37.23). Poverty seems to be strongly correlated with a lower quality of life in all relevant domains (child mortality, life expectancy, access to healthcare, education, learning outcomes, life satisfaction). Just to connect to the other two problems above, global poverty would be worsened both in cases of pandemics or nuclear war that negatively impacts the world economy.
Battery-caged hens: Billions of chickens are living possibly net negative lives every year, and their situation can be improved considerably by abolishing the use of battery cages, which seems a feasible intervention, given that many companies have already done it.
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What are your 3-5 biggest uncertainties about the above?
Uncertainties about nuclear war: What is the chance that we’ll have a nuclear war that poses existential risk? What can be done to lower the risk? Some people have argued that the existence of nuclear weapons is part of the cause for why the world has been more peaceful in the last decades, compared to before. If this is true, then how does that change our relationship to the existence of nuclear weapons?Uncertainties about global poverty: Would it be solved just by redistributing the world’s wealth, or would that not be enough? What is the risk that, by making people richer, the environmental destruction increases to a point of no return?
Uncertainties about battery-caged hens: How much better are their lives outside the cage? If still net negative, what’s the chance that the abolition of cages would lead to “moral licensing”, i.e., society feeling that we don’t need to abolish factory-farmed hens, because they are already cage-free?
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What could you do over the next few weeks to explore those uncertainties?
Do more reading! :-)================================================
What aptitudes are you most interested in exploring or using next? You might want to think about what you’re unusually good at, what activities make you feel energized, and what skills seem especially useful for addressing the problems you listed above.
I’m particularly interested in mathematical modeling and statistics, which seem very useful tools for evaluating scientific evidence, which, in turn, helps to shed light on most of these questions and uncertainties.================================================
How could you begin to test out those aptitudes over the next few weeks?
I’ll continue my studies of mathematics and statistics, as planned :-)================================================
While you’re figuring out your uncertainties, are there any actions to improve the world that you want to do now?
Yes! I plan to create a one-hour presentation about some of the world’s biggest problems and how to address them to some friends of mine (I plan to do one-on-one meetings) who have the resources and the desire to have a positive impact on the world, but might not have thought about it.
I also plan to contact the one-on-one 80,000 Hours mentorship some time this year.================================================
Thank you all for striving to make the world a better place!
I’m going to share my answers. Please keep in mind that they might have been already tackled by other people elsewhere. In any case, those are the critiques I have so far.
Superficial references problem:
The handbook almost never recommends books on the subjects (except those written by MacAskill, Ord, Singer, etc), but instead they tend to recommend blog posts, Wikipedia, other EA-aligned webpages, or, at best, philosophy papers. In my opinion, there could be recommendations of textbooks on cost-effectiveness analysis, cause prioritization, economics, ethics, statistics, cognitive biases, etc. Since webpages and standalone papers are not nearly as good as textbooks to learn a subject, I believe recommendations of books are definitely warranted, otherwise we can get the impression that all the theoretical background that EAs have are those shallow references.The neglectedness problem:
First, it’s not clear how to distinguish between these two scenarios: (1) The cause is unfairly neglected, that is, much more neglected than it ought to be, considering its scale and tractability; and (2) The cause is neglected because it’s really a bad cause to work for (due, for instance, to low scale or low tractability), in which case it being neglected is actually a sign that we shouldn’t work on it. In order to help us sort out what’s the underlying scenario, I think we should see whether other institutions/researchers have attempted to work on the issue in the past, and not just look at the absolute numbers of funding/researchers that are going to that cause in the present. I don’t remember seeing this historical analysis being done. And maybe we should employ other strategies besides this historical analysis to sort things out.
Second, there’s another shortcoming of just assessing neglectedness by looking at the amount of dollars being poured into a cause. People might be working to solve a problem and pouring lots of money into it using an inefficient method. For instance, suppose that we lived in a world where hundreds of billions of dollars were being spent on leafletting about the animal cause, and suppose that it is the case that leafletting is a very inefficient method to promote concrete changes to animal well-being. Then even though there are hundreds of billions of dollars being put into the Animal Cause, there would still be a low-hanging fruit, if we assume that, for instance, corporate campaigns are a hundred times more efficient than leafletting. So just looking at the sheer number of donated dollars to the Animal Welfare cause could be very misleading because even though it’s not “numerically” neglected, we’re not making use of the most effective methods.
Third, I’m not convinced that the curve of improvement as a function of funding/researching has a log shape (or any curve that implies diminishing marginal returns)
Fourth, even if it has a log shape, in order to infer that an additional person/dollar of funding would have a greater impact on cause A compared to cause B, we would need to know the parameters of the log curve for cause A and cause B, which we don’t. For example, check www.desmos.com/calculator/ohwiagg7zi. Here we have two causes with a log curve, but with different parameters (hence, different shapes), and we can see that even though cause red is receiving more funding than cause green, the marginal return of cause red is still higher than the marginal return of cause B, which makes comparisons between different cause with regards to neglectedness very hard, if not impossible.Blindspots: By “blindspots”, I mean arguments that I’ve never seen being raised in the given discussions, though they seem to be crucial.
[The logic of the larder] blindspot in the Animal Welfare discussion: It’s not crystal clear what is the net value of the lives of each factory-farmed species. For instance, if some species have net positive lives, then interventions that aim to reduce the number of factory-farmed animals will cause a loss of total value. Another thing to consider is that, because of the crops to sustain factory-farmed animals, they have a negative impact on the number of wild animals, and if we consider that the lives of wild animals are worse than the lives of some factory-farmed animals, then abolishing factory farms will have this other source of disvalue as well, by creating lives whose quality is even worse.
[Intelligence restart] blindspot in the Extinction Risk discussion: If only humanity goes extinct, couldn’t some other species as intelligent as (or even more intelligent than) humans eventually evolve from other animals, say, from the surviving primates?
I feel questions 1 and 2 are essentially the same, with the second having a more partitioned approach. Did I overlook some important difference between them?
Hi! Just want to point out a typo: “This chapter we’d like you (...)”. Thanks! :-)
Hi! Just want to point out that the [Future Proof report] link is broken.
Thanks for your reply. The possibility of asymmetry suggests even more that we shouldn’t predict in the whole [0%-100%] range, but rather stick to whatever half of the interval we feel more comfortable with. All we have to do is to get in the habit of flipping the “sign” of the question (i.e, taking the complement of the sample space) when needed, which usually amounts to adding the phrase “It’s not the case that” in front of the prediction. This leads to roughly double the number of samples per bin, and therefore more precise estimates of our calibration. And since we have to map an event to a set that is now half the size it was before, it seems easier for us to get better at it over time.
Do you see any reason not to change Open Philanthropy’s approach to forecasting besides the immense logistic effort this implies?
Thanks for sharing this! I’ve been forecasting myself for 5 months now (got 1005 resolved predictions so far), and I adopted a slightly different strategy to increase the number of samples: I only predict in the range [50%-100%]. After all, there doesn’t seem to be any probabilistically or cognitively relevant difference between [predicting X will happen with 20% probability] and [not-X will happen with 80% probability]
What do you folks think about this?
I think Lorenzo is right: when there is a reply to a comment, I can’t delete the comment. Here’s a screenshot of what I see (it’s the same thing when I click on the three dots in this comment I made (which starts with the words “Hmm, to my surprise”)):
Anyway, that’s no big deal! I’ll leave the comment up. Thank you folks for your kindness!
Hmm, to my surprise, I just found out that I can’t delete the comment, but only “retract” it (which amounts to striking the text through). Two questions:
Did I miss a way of really deleting the comment?
If there is no way to delete it, is there a better way to report the typos than pointing them out in the comments section?
Hi! I found a typo. I’ll delete the comment once it gets fixed:
“and explore they are so neglected by society”.
Thanks!
I think the principle I want us to abide by is something like ‘if something is an argument for caring more about entities who are widely regarded as not worthy of such care, then even if the argument sounds pretty absurd, I am supportive of some people doing research into it. And if they’re doing that research with the intent of increasing everyone’s well-being and flourishing as much as possible, then they’re part of our movement’.
That’s just beautiful. Thanks for your insight!
It’s not clear to me what it would mean to “treasure a non-living thing” in the same way that we should “treasure a living [I’d add ‘sentient’] being”. When I treasure a sentient being, what I mean by this is that:
(1) I recognize that sentient being’s capacity to feel positive and negative states of mind;
(2) I recognize that that sentient being has interests of their own; and
(3) I take the previous two facts into consideration in my decision-making so that I don’t, unnecessarily, make that sentient being feel negative states of mind, or deprive them of their interests.
However, in the case of non-living things, such as rocks, knives, toys, etc, facts (1) and (2) are absent, and therefore I cannot treasure them in the same way I treasure sentient beings.
I can, of course, decide that some non-living thing has value (such as a potato), in so far as it can, for instance, satisfy the interest of a sentient being not to be hungry, and make that sentient being not experience the negative state of mind associated with hunger, but rather experience the positive state of mind associated with satiation, and the ripple effects of nutrition that flow from this.
In your example of reducing waste, who (or what), exactly, is being treasured? The waste, or the future sentient beings who, because of an environmentally friendly disposal of the waste, will have their interests satisfied by not living in a depleted Earth?
Agreed! Sounds too good to be true, but I do hope it is! Thanks SiebeRozendal for sharing this news!