I’m fairly new to EA, greatly enjoying the 80,000 hours podcasts on 10 global problems. I have been pondering on the EA philosophy of using resources to do the most good and therefore having the greatest impact numerically.
So I’m wondering—taken to it’s logical conclusion, is this not effectively a well intentioned version of survival of the fittest? What if your cause or issue is niche or that the people affected are low in numbers? How is their validity built in to the model? How does EA value diversity of issues?
So to give a concrete example: less than 1% of the population worldwide have type 1 diabetes. Maybe your money would be better spent on type 2 diabetes, with 8% of the world’s population having that. Does this mean those with type 1 are unimportant or unworthy of funding?
Within EA would the solution be looking for the most impactful way to ‘solve’ type 1 (be that through advocacy for affordable insulin and supplies or via a cure), or would you simply focus on the larger population (type 2) and fund that for greater impact?
The lack of scope for diversity of smaller causes in the model troubles me, but I’m here to learn and very interested to hear views!
Type 1 diabetic and long time EA here.
Generally when I have donated to help people directly (most of my recent donations have not been of this form, to be clear, in recent years my donations have been focused on research or on helping animals) I am not really thinking about how big the problem is. I am thinking “what will the consequence of this donation be?” If I am donating less than millions of dollars, I’m not likely to solve the whole issue, so the question of if the issue is big or small in a global sense just isn’t very important.
For type 1 diabetes, what can a donation of $5k do? I’m not sure, but the baseline for what I can do with $5k in the global health space is “prevent a child from dying of malaria”, so I would want to find something I thought was better than that before doing so.
That last bit is the key to the EA mindset to me—given a fixed donation budget, every time we choose to give to something, we are choosing not to give that money to everything else. So we ought to triage, and give to where we think the money or effort can do the most good.
For someone who knows of a really high leverage way to impact the affordability or availability of insulin (or for a researcher with a chance of discovering a cure or improved treatment), it might be that the best place for them to focus their efforts is on that. There are millions of type 1 diabetics, so any one person who could make a meaningful impact there could have enormous impact. But it’s still good for them to ask the question and be aware of what other avenue to impact they might have, if their goal is to do the most good.
Great answer, thank you!
I think this is a good question. To me, EA is pretty ruthless in how it assesses effectiveness, and that leads to many causes feeling left out (especially when those causes are close to you personally).
Taken to an extreme, if all charitable acts/giving was done through an EA lens, it would feel pretty brutalist to any cause not included in its scope. Though from an EA lens, this would be a *more effective* charitable sector and ultimately reduce suffering/increase overall wellbeing.
But the simple reality is EA is small relative to the universe of charitable acts. And I think having a portion of charitable acts approached with an EA lens is a good thing. And I think the actual % is significantly lower than the optimal %.
Thanks for joining in and that’s an interesting question. I’m sure different people within EA will have different opinions on this too,
Personally I don’t think the size of the problem is a deal breaker in working on an issue. I would happily work on a small issue if it was tractable (solvable) and neglected. If a small-ish problem could be solved cost-effectively, then why not go ahead and do it?
Type 1 diabetes especially is an interesting problem, in that there is some potential for it to be permanently “solved” and eradicated, somewhat like smallpox is. For example we could transplant pancreatic iselet cells into diabetics, effectively curing the disease meaning that diabetics wouldn’t need insulin and they could live normal lives. This kind of intervention could be extremely cost-effective due to the enormous effect it would have not only saving current lives (like mosquito nets do), but also future lives.
As a side in my opinion both diabetes type 1 and 2 would both fall in the category of pretty large scope problems.
Nice question.
First it’s worth noting that “size” is only one contributing factor in cost-effectiveness. But I acknowledge that there are some issues (rare genetic diseases, for example) that are so small that we could never justify spending lots of resources on them.
You ask how EA values diversity of issues. Clearly EA works on a number of issues, and I’d argue this is because:
there is disagreement/uncertainty about what the most cost-effective intervention is (due to lack of data and philosophical disagreements)
as you spend more on a cause, you pick the lowest hanging fruit, and the work becomes less cost-effective. Eventually you can move on to something else.
Yet clearly EA does not work on everything. Some things are just not plausibly among the most cost-effective things we can do. This does mean admitting that we are not going to “solve” type 1 diabetes in the foreseeable future.
Responding to your diabetes example, it really is sometimes better to turn down the opportunity to “solve” a problem in order to have impact elsewhere. Doctors in the 1960′s already had a way of saving ~100% of cholera sufferers in hospital using intravenous saline solution. But most people couldn’t make it to the hospital. Scientists developed an oral hydration that was less effective, but could be administered at home. This oral solution was, and has been, much more important and revolutionary than the hospital treatment. As one of the scientists put it, “It’s better to reach 80 percent of people with something that’s 80 percent effective than five percent of people with something that’s 100 percent effective.”
Ultimately, EA is about doing the most possible good with the resources available. The result is that if “your” niche or issue is something very ineffective (like training guide dogs, which is far less cost-effective than some ways of preventing or reversing blindness in poor countries) then you should change your niche.
Thanks so much for your answers, really interesting to hear the multiple perspectives. I don’t think I’ll be giving up on type 1 any time soon since my daughter has the condition and I volunteer with a type 1 advocacy charity (called T1International).
I think it’s great to reflect on how best to use funds though, and I think going for large scale systemic change and advocating for policy change (which we do) is in our case the right thing. Advocacy impact is non-linear and much harder to measure, but when the wins come, they tend to be big and make positive changes for lots of people.
I don’t want to give up on advocating for health equity for the type 1 population when so many people have to spend so much of their monthly income just to stay alive due to the price of insulin, but I like the idea of thinking about appropriate causes in percentage terms.
Regarding research, I would say that each research line has some probability of success and some cost and probably an optimal research portfolio would include more or less four times more expenditure for type 2 diabetes, but no zero expenditure for type 1. Choice under uncertainty imply some natural preference for diversity.
For deployment (suppose no uncertainty) you spend money in strict order or “welfare” or “additional life years” by dollar spent, so probably you would spend in an expensive cancer treatment for a young person, but the same money would not be spent in an old one.
So, yes, reality is diverse and that creates apparent diversity in expenditure even for a ruthless utilitarian with no intrinsic preference for diversity.