Director of Research at CEARCH: https://exploratory-altruism.org/
I construct cost-effectiveness analyses of various cause areas, identifying the most promising opportunities for impactful work.
Previously a teacher in London, UK.
Stan Pinsent
Karma: 803
Using PDF rather than CDF to compare the cost-effectiveness of preventing events of different magnitudes here seems off.
You show that preventing (say) all potential wars next year with a death toll of 100 is 1000^1.6 = 63,000 times better in expectation than preventing all potential wars with a death toll of 100k.
More realistically, intervention A might decrease the probability of wars of magnitude 10-100 deaths and intervention B might decrease the probability of wars of magnitude 100,000 to 1,000,000 deaths. Suppose they decrease the probability of such wars over the next n years by the same amount. Which intervention is more valuable? We would use the same methodology as you did except we would use the CDF instead of the PDF. Intervention A would be only 1000^0.6 = 63 times as valuable.
As an intuition pump we might look at the distribution of military deaths in the 20th century. Should the League of Nations/UN have spent more effort preventing small wars and less effort preventing large ones?
The data actually makes me think that even the 63x from above is too high. I would say that in the 20th century, great-power conflict > interstate conflict > intrastate conflict should have been the order of priorities (if we wish to reduce military deaths). When it comes to things that could be even deadlier than WWII, like nuclear war or a pandemic, it’s obvious to me that the uncertainty about the death toll of such events increases at least linearly with the expected toll, and hence the “100-1000 vs 100k-1M” framing is superior to the PDF approach.
By incentives do you mean incentives for taking one job over another, like pay, benefits, type of work, etc.?
I welcome this idea! More love would be a good thing, and we would rather make this change earlier in the life course.
I think implementation is hard. This is a big “if”:
if we could come up with a healthy, inclusive (but respectful of differing opinions), curriculum that -encourages/rewards- love but does not impose it
As Joseph said, it is difficult to assess educational interventions. When it comes to knowledge transfer we can be generally confident that education is helping—calculus classes increase students’ aptitude for calculus. But love?
Recent research suggests that mindfulness interventions in schools were much less impactful than hoped. I suspect that something like mindfulness works well if you opt in—and is much less useful if you didn’t ask for it.
To explore this idea further, I recommend looking for comparable values-based educational experiments that have been tried in the past (maybe something about attitudes to sexuality, or religious tolerance, or positive thinking, or even campaigns to instil hate). Did they succeed in changing values? If they failed, why did they fail? If they succeeded, what can we learn from them?
Can anyone convince me that this is a robustly good move for donkey welfare? Working donkeys seem to have quite bad lives, so a falling population because people are deciding to sell donkeys for slaughter might be a good thing.
my guess is [...] you could counterfactually save 1-5 more lives per day by volunteering and being great at your job.
I’m skeptical. That would mean that your average hotline volunteer is speaking to 1-5 new people per day who subsequently take their lives, but would not have if the call were handled better. This seems implausible purely on the basis that most suicide attempts fail (5-11% of people who ever attempt end up ever succeeding). Added to this, I suspect that some (most?) people who call are thinking about suicide but not literally about to do it, some (most?) are making multiple calls to the hotline, and that some of the worst cases may be possible to save today but will take their lives in a few months’ time. Basically, I suspect that each call that a volunteer successfully handles would be worth more like 0.001 or 0.01 of an averted suicide.
I did (non-suicide) helpline training once and was struck by how formalised it is. Volunteers were supposed to be listeners, reflecting the callers’ thoughts back to them and avoiding giving advice. This is likely a strategy to minimise the harm caused by layperson volunteers interacting with very vulnerable people. I would suspect that suicide hotlines have fairly rigid guidelines on how to handle calls, probably with more specific training on how to help the caller de-escalate their suicidal thoughts in the moment. My concern would be that this leaves little wiggle room for being “great at your job”, and anyone trying to be significantly more effective may actually do damage by going off-script.
Would love to hear from someone with direct experience!
I think you could build a very compelling case for this. Even if official data sources do underestimate key numbers like overdose deaths, they are still a stirring call to action.
Drug problems have got considerably worse in the past decade. This CDC source implies that overdose rates have more than doubled since 2015. Much of the increase came during the pandemic, which could add a little narrative spice to your argument.
2. Other “similar” problems are not getting worse. Other “despair” indicators like suicide and depression appear to be stable. Road accidents and violence have fallen. On one hand it’s a bit sneaky to pick and choose comparisons like this, but it could be argued that they are all societal problems that often cause (very) early death. They’re tragic.
3. Vaccines/ other pharma interventions may offer an unusually tractable and scalable solution. Addiction and all of the other problems in the chart above are very difficult problems to fight. At best, interventions usually take a chunk out of the burden but offer no hope of big change. Drug interventions can be controversial, with effects of uncertain sign. If you can show that your ideas are significantly better, you are doing well.
I expect that a major difficulty is that your solutions involve developing new vaccines/drugs, which is of course an expensive, unknown and long process. Will pharma companies see potential for a profit? Is there scientific grounding for optimism on these new drugs being possible?
Unfortunately I don’t have the spare capacity to volunteer much time. I’d be interested in giving feedback on any future work. Good luck!
Thank you!
Also, do you have any recommendations for estimating the disvalue of a policy that curtails people’s freedom (eg. by increasing the price of a good they value)?
Interesting! Can you link to any (reasonably simple) example CEAs where this process is applied?
Thanks for the recommendation! I came across something similar recently: Action for Happiness, which is recommended by Founders’ Pledge. I think the theory of change is that people can meaningfully improve their wellbeing by applying some evidence-based changes to their lives. Most who start will probably drop out, but those who persevere will likely benefit. Costs could be kept low by relying on centralised resources, voluntary donations and possibly volunteer labour.
Unfortunately my report didn’t explore this avenue for change as I only looked at preventing and mitigating mental illness (+ pain + suicide), but I wish I had done more on simply improving wellbeing.
I would say that although self-help is, on the face of it, basically free, the cost of reaching new people through marketing is likely to be a huge determinant of how cost-effective it is.
I don’t know why they say it is a problem. I’d be more concerned about trapped water taking up more space in garbage trucks, landfill, etc. Even then, the extra cost may be small.
My take is that (1) the preciousness of water depends heavily on location and (2) a small number of activities represent the vast majority of water use.
In some places there is loads of rainfall and if shortages happen, they could maybe just be solved by improving infrastructure (more reservoirs and treatment plants). Places with a large population for the amount of water available (possibly including Texas, I don’t know) need to be more sparing with their water. Often most water, especially in arid places, tends to go to plant cultivation. That includes crops (for human or animal consumption), parks & golf courses, back yards etc. If you want to save water, that is where most of the gains can be made. Turning off the tap/faucet while you brush your teeth is nice but it won’t do much.
Thanks for your comment, Derek. This has been really useful.
Some changes I have made in response:
Changed “death” to “being dead” in my explanation of the DALY scale
Now say that DALYs likely underweight pain, but QALYs may not:
DALYs appear to weight pain very lightly. For example, terminal illness with constant, untreated pain has a disability (DALY) weight of 0.569, which is only 0.029 more than the weight for the same condition with pain medication. QALYs are better at capturing pain: physical pain is the dimension given the highest weight in the EQ-5D, and instrument used to measure quality of life.
Mention that even sufferers may underestimate the badness of depression [with a link to your comment]
A question:
I see from the summary you linked that IHME have used sequelae to identify ailments that are present in multiple health conditions. That seems sensible. I guess the kind of problem I often face is “What will be reduction in someone’s disability weight if they are—protected from getting diabetes / cured of depression / etc. ?”
In the diabetes example, it seems fair to count DALYs averted by not having diabetes and DALYs averted by depression-caused-by-diabetes. Maybe not fair to count, say, obesity, since the increased risk of obesity associated with diabetes is likely to be correlational, not causal. Am I thinking along the right lines?
If we go with the depression example, it seems fair to count both prevented suicide and prevented depression (but not prevented depression-while-dead-by-suicide)
Taking a couple of litres of water out of the cycle is not a big problem. If everyone on earth sequestered 100 litres of water in this way, that would remove enough water to reduce the level of Lake Superior by 1cm.
[8*10^9 people. Lake superior has an area of 8*10^10sqm. The volume of a sqm of water with depth 1cm is 10 litres. Hence 8*10^11 litres divided between 8*10^9 people, which gives 100 litres each.]
Thank you for the kind words, Nick!
Completely agree that if the participants know they are receiving a special treatment they are likely to show more response bias. By “well-conducted RCT” I was thinking of studies with an active control like Nakimuli-Mpungu et al. (2020) in which patients “were randomly assigned to deliver either [group support psychotherapy] or group HIV education”. If done well, the participants won’t know which treatment the scientists “want” to perform better and so response bias will be constant.
I’ve added a few comments :)
Thanks for sharing this! You’ve convinced me that policy advocacy in the US could be really cost-effective, simply by leveraging the huge resources at stake. My main objection is to the ballpark 2-3 QALY gain for each person who receives food aid or health insurance. I understand that these are just simple calculations for illustration, but I think that added complexities will tend to make this estimate go down a lot:
I’d be surprised if, among Americans, food security alone is worth this much per person. Health outcomes in the US are horrendously unequal because of a nexus of strongly-correlated factors that also include poverty, unhealthy lifestyles, healthcare, drugs, etc. Removing a single one may not do much.
You’re assuming that any improvements in benefit-claiming lasts a long time (many years of food aid are required to ensure a child is never food insecure). In reality, counterfactual effects will decay over time. Less so for structural changes that make it easier for people to claim benefits.
Another point is that diverting public funds comes at a counterfactual cost. What would have happened to that MediCal money that would have gone unclaimed until your expansion advocacy? Maybe something less cost-effective (like schools, which form a third of CA’s budget), but with a non-negligible impact that should be subtracted from the effect of MediCal expansion.
One possibility to come up with additional funds would be to pass a tax on the wealthiest to pay for this expansion. Eg, a property tax on homes valued at more than $5M, or a capital gains tax on Retirement portfolios over $5M. Lower wealth limits will introduce more opposition from voters.
Agree that this would be great and agree that it would face opposition.
The report is now public: https://forum.effectivealtruism.org/s/ykdScawzq59ntw9N3
So glad you’re looking into this.
Interesting to see that you didn’t use IHME’s DALY weights for mild, moderate and severe depression, which are derived from surveys of ordinary people making pairwise comparisons (GBD, 2019).
[Figure from WHO (2020).]
In my report on mental health interventions (
coming soon!) I took data from Pyne et al. (2009) which asked sufferers, ex-sufferers and never-sufferers of depression to rate the badness of different levels of depression. My analysis of the data suggests that sufferers rate depression to be approximately 20% worse than a typical person would. Interestingly, this phenomenon of rating your own condition worse than others would does not seem to hold for most health conditions (see Pyne et al., 2009).I also tried to model the DALY burden that comes from the additional suicide risk associated with depression, and reached an estimate of 0.066 DALYs for each year of depression. This is contingent on some dodgy data on the effect of depression on suicide rates, and ought to vary a lot by gender and nationality.
Putting it all together, I got an estimated weighting of 0.392 for an average case of depression. My central estimate is 0.145 DALYs per SD of depression symptoms, so about 22% lower than yours.
Thanks for the detailed response, Vasco! Apologies in advance that this reply is slightly rushed and scattershot.
I agree that you are right with the maths—it is 251x, not 63,000x.
OK, I did not really get this!
In your example on wars you say
Can you give an example of what might count as “spending to save lives in wars 1k times as deadly” in this context?
I am guessing it is spending money now on things that would save lives in very deadly wars. Something like building a nuclear bunker vs making a bullet proof vest? Thinking about the amounts we might be willing to spend on interventions that save lives in 100-death wars vs 100k-death wars, it intuitively feels like 251x is a way better multiplier than 63,000. So where am I going wrong?
When you are thinking about the PDF of PiPf, are you forgetting that ∇PiPf is not proportional to ∇Pf?
To give a toy example: suppose Pi=100.
Then if 90<pf<100 we have 1<PiPf<1.11
If 10<pf<20 we have 5<PiPf<10
The “height of the PDF graph” will not capture these differences in width. This won’t matter much for questions of 100 vs 100k deaths, but it might be relevant for near-existential mortality levels.