Dr. David Denkenberger co-founded and directs the Alliance to Feed the Earth in Disasters (ALLFED.info) and donates half his income to it. He received his B.S. from Penn State in Engineering Science, his masters from Princeton in Mechanical and Aerospace Engineering, and his Ph.D. from the University of Colorado at Boulder in the Building Systems Program. His dissertation was on an expanded microchannel heat exchanger, which he patented. He is an associate professor at the University of Canterbury in mechanical engineering. He received the National Merit Scholarship, the Barry Goldwater Scholarship, the National Science Foundation Graduate Research Fellowship, is a Penn State distinguished alumnus, and is a registered professional engineer. He has authored or co-authored 143 publications (>4800 citations, >50,000 downloads, h-index = 36, second most prolific author in the existential/āglobal catastrophic risk field), including the book Feeding Everyone no Matter What: Managing Food Security after Global Catastrophe. His food work has been featured in over 25 countries, over 300 articles, including Science, Vox, Business Insider, Wikipedia, Deutchlandfunk (German Public Radio online), Discovery Channel Online News, Gizmodo, Phys.org, and Science Daily. He has given interviews on 80,000 Hours podcast (here and here) and Estonian Public Radio, WGBH Radio, Boston, and WCAI Radio on Cape Cod, USA. He has given over 80 external presentations, including ones on food at Harvard University, MIT, Princeton University, University of Cambridge, University of Oxford, Cornell University, University of California Los Angeles, Lawrence Berkeley National Lab, Sandia National Labs, Los Alamos National Lab, Imperial College, and University College London.
Denkenbergeršø
ALLFEDās 2023 Highlights
Thanks for all you have done!
Finally, EAs have treated EtG as increasingly more weird, especially offline, defeating the original argument for engaging.
This is very disappointing, especially because, if you disregard āstill decidingā, EtG was the second most popular route to impact among EAs in the 2022 survey.
(leading aādare I sayāsuccessful effective nonprofit)
Sureāgo ahead and dare. :)
My day job is associate professor of mechanical engineering at University of Canterbury in New Zealand, and I volunteer for ALLFED. Nearly 100% of my donations are to ALLFED. I think that ALLFED is the most cost-effective way of improving the long run future at the margin (see here and here, though Iām not quite as bullish as the mean survey/āpoll results in those papers), but there are orders of magnitude of uncertainty, and I think more total money should be put into AGI safety.
As one who donates 50%, it doesnāt seem like it should be that uncommon. One way I think about it is earning like upper-middle-class, living like middle-class, and donating like upper-class. Tens of percent of people work for tens of percent less money in sectors like nonprofits and governments. And Iāve heard of quite a few non-EAs who have taken jobs for half the money. And yet most people think about donating that large of a percent very differently than taking a job that pays less. Iām still not sure whyāother than that it is uncommon or āweird.ā
I agree that most academic research is a bad ROI but I find that a lot of this sort of ānobody reads researchā commentary is equating reads with citations which seems completely wrong. By that metric most forum posts would also not be read by anyone.
I agree-for one, the studies Iāve seen saying that the median publication is not cited are including conference papers, so if one is talking about the peer-reviewed literature, citations are significantly greater. Iāve estimated the average number of citations per paper is around 30 for the peer-reviewed literature. Furthermore, from what Iāve seen, the number of reads on places like ResearchGate and Academia.edu tend to be one to two orders of magnitude greater than the number of citations. So I think a reasonable expectation for a peer-reviewed paper is hundreds or thousands of reads.
The government could internalize this positive externality by providing incentives, like this.
I was assuming 50 % reduction in international trade, and 50 % of that reduction being caused by climatic effects, so only 25 % (= 0.5^2) caused by climatic effects. I have changed ā50 % of itā to ā50 % of this lossā in my original reply to clarify.
That makes sense. Thanks for putting the figure in!
I guess famine deaths due to the climatic effects are described by a logistic function, which is a strictly increasing function, so I agree with the above. However, I guess the increase will be pretty small for low levels of soot.
If it were linear starting at 10.5 Tg and going to 22.1 Tg, versus linear starting at 0 Tg and going to 22 Tg, then I think the integral (impact) would be about four times as much. But I agree if you are going linear from 10.4 Tg versus logistic from 0 Tg, the difference would not be as large. But it still could be a factor of two or three, so I think itās good to run a sensitivity case.
Very interesting!
Space colonies. Fertility is low in wealthy countries with large unsettled territories (Canada, Australia), even though they are far more hospitable than other planets. There is no reason to think that space colonies alone will reverse the fertility decline.
I think the incentive for fertility depends on the level of connection with the Earth. If it were fully independent from Earth, it would have a strong incentive to increase population because there are large economies of scale in terms of increasing the standard of living, including being able to create more living space per person, more advanced electronics, media, etc.
Both sides targeted civilians in WWII. Hopefully that is not the case now, but Iām not sure.
>Half of the impact of the total loss of international food trade would cause 2.6% to >die according to Xia 2022. So why is it not 4.43%+2.6% = 7.0% mortality?
In my BOTEC with āarguably more reasonable assumptionsā, I am assuming just a 50 % reduction in international food trade, not 100 %.
Thatās why I only attributed half of the impact of total loss of international food trade. If I attributed all the impact, it would have been 4.43%+5.2% = 9.6% mortality. I donāt see how you are getting 5.67% mortality.
My famine deaths due to the climatic effects are a piecewise linear function which is null up to a soot injection into the stratosphere of 11.3 Tg. So, if one inputs 5 Tg into the function, the output is 0 famine deaths due to the climatic effects, not negative deaths.
My understanding is that you chose this piecewise linear function to be null at 11.3 Tg because thatās where the blue and gray dotted lines crossed, meaning that it appeared that the climate impacts did not kill anyone below 11.3 Tg. But what Iām arguing is that those two lines had different assumptions about feeding food to animals and waste, so the conclusion is not correct that there was no climate mortality below 11.3 Tg. And this is supported by the fact that there are currently under nutrition deaths, and any nonzero Tg is likely to increase those deaths.
I am happy to describe what happens in a very worst case scenario, involving no adaptations, and no international food trade.
There are many ways that things could go worse than that scenario. As I have mentioned, there could be reductions in nonfood trade, such as fertilizers, pesticides, agricultural equipment, energy, etc. There could be further international conflict. There could be civil unrest in countries and a breakdown of the rule of law. If there is loss of cooperation outside of people known personally, it could mean a return to foraging, or ~99.9% mortality if we returned to the last time we were all hunter-gatherers. But it could be worse than this given the people initially would not be very good foragers, the climate would be worse, and we could cause a lot of extinctions during the collapse. The very worst case scenario is if there is insufficient food, if it were divided equally, everyone would starve to death.
I must note that, under the above assumptions, activities related to resilient food solutions would have cost-effectiveness 0, as one would be assuming no adaptations.
I certainly agree that there would be some reduction in human edible food fed to animals and food waste before there will be large-scale deployment of resilient foods. But what Iām arguing is that the baseline expected mortality without significant preparation on resilient foods could be 25% because of a combination of factors listed above. Furthermore, I think that preparation involving planning and piloting of resilient foods would make it less likely that we fall into some of the terrible situations above.
In general, I do not think it is obvious whether the cost-effectiveness of decreasing famine deaths due to the climatic effects at the margin increases/ādecreases with mortality. The cost-effectiveness of saving lives is negligible for negligible mortality and sufficiently high mortality, and my model assumes cost-effectiveness increases linearly with mortality, but I wonder what is the death rate for which cost-effectiveness is maximum.
As above, even if the baseline expectation were extinction, there could be high cost effectiveness of saving lives from resilient foods by shifting us away from that scenario, so I disagree with āThe cost-effectiveness of saving lives is negligible for ā¦ sufficiently high mortality.ā
For arguably more reasonable assumptions of 50 % loss of international food trade, and 50 % of it being caused by the climatic effects, linearly interpolating, the increase in the death rate would be 25 % (= 0.5^2). So the new death rate would be 5.67 % (= 0.0443 + (0.0940 ā 0.0443)*0.25), i.e. 1.28 (= 0.0567/ā0.0443) times my value.
Half of the impact of the total loss of international food trade would cause 2.6% to die according to Xia 2022. So why is it not 4.43%+2.6% = 7.0% mortality?
It is still the case that I would get a negative death rate inputting 5 Tg into my formula. However, I am linearly interpolating, and the formula is only supposed to work for a mean stratospheric soot until the end of year 2 between 14.6 and 24.6 Tg, which excludes 5 Tg. I am approximating the logistic function describing the famine deaths due to the climatic effects as being null up to an injection of soot into the stratosphere of 11.3 Tg.
I see how you avoid the negative death rate by not considering 5 Tg. However, this does not address the issue that your comparison is not fair, which is exposed by the fact that if you did put in 5 Tg, you would get negative death rate.
So my interpretation is that the blue line corresponds to no livestock grain fed to humans and current food waste (in 2010), but without international food trade.
I think that is a reasonable assumption, as then the mortality due to 5 Tg alone (no trade in both cases) is ~2% (not a reduction in mortality).
Ideally, instead of adjusting the top line of Figure 5b to include international food trade, I would rely on scenarios accounting for both climatic effects and no loss of international food trade, but Xia 2022 does not present results for that.
One logically consistent way of doing it would be taking the difference between the blue and dark red lines, because they are comparable scenarios. I agree that no reduction in waste or food fed to animals is too pessimistic, but maybe you could do sensitivity on the scenario? Because even though I think that particular scenario is unlikely, I do think that cascading risks including loss of much of nonfood trade could very well increase mortality to these levels.
I am very open to different views about the famine death rate due to the climatic effects of a large nuclear war. My 95th percentile is 702 times my 5th percentile.
That is true, but if you had significant probability mass on the scenarios where people react very suboptimally, then your mean mortality would be a lot higher.
In that case, I would only be overestimating the amount of soot by 10 %, which is a small factor in the context of the large uncertainty involved (my 95th percentile famine deaths due to the climatic effects is 62.3 times my best guess).
Do you mean underestimating? I agree that itās not that large of an effect.
For reference, maintaining my famine deaths due to climatic effects negligible up to an injection of soot into the stratosphere of 11.3 Tg, if I had assumed a total loss of international food trade fully caused by the climatic effects, I would have obtained a famine death rate due to the climatic effects of a large nuclear war of 5.78 % (= 1 - (0.993 + (0.902 ā 0.993)/ā(24.6 ā 14.6)*(14.5 ā 14.6))*0.948), i.e. 1.30 (= 0.0578/ā0.0443) times my value of 4.43 %. For arguably more reasonable assumptions of 50 % loss of international food trade, and 50 % of it being caused by the climatic effects, linearly interpolating, the increase in the death rate would be 25 % (= 0.5^2). So the new death rate would be 4.77 % (= 0.0443 + (0.0578 ā 0.0443)*0.25), i.e. 1.08 (= 0.0477/ā0.0443) times my value.
The total loss of international food trade would cause 5.2% of all die in Xia 2022. So it seems like attributing this all to the climactic effects would increase your death rate by 5.2 percentage points. But digging in deeper, since you are using the gray dotted line in figure 5B corresponding to no human edible food fed to animals and zero waste, if you plugged in a value of 5 Tg, you would say that that amount of soot would actually decrease mortality relative to no food trade and 0 Tg. So clearly that no trade case is not the scenario of no human edible food fed to animals and zero waste (I couldnāt find quickly what exactly their assumptions were for that case). I understand that you are picking the no human edible food fed animals and zero waste scenario because you think other factors would compensate for this optimism. But I think it is particularly inappropriate for the relatively small amounts of Tg.
I thought this was comprehensive, and it was clever how you avoided doing a Monte Carlo simulation for most of the variables. The expected amount of soot to the stratosphere was similar to my and Luisaās numbers for a large-scale nuclear war. So the main discrepancies are the expected number of fatalities and the impact on the long-term future.
From Figure 4 of Wagman 2020, the soot injected into the stratosphere for an available fuel per area of 5 g/ācm^2 is negligible[14].
At 5 g/ācm^2, Still most of soot makes it into the upper troposphere, so I think much of that would eventually go to the stratosphere. Furthermore, forest fires are typically less than 5 g/ācm^2, and they are moving front fires rather than firestorms, and yet still some of the soot makes it into the stratosphere. In addition, some counter value targets would be in cities with higher g/ācm^2. Since you found the counterforce detonations were ~4x as numerous, 1ā7 the fuel loading, and if the soot to stratosphere percent was 1/ā3x, that would be ~20% as much soot to stratosphere as the countervalue.
From Fig. 5b of Xia 2022, for the case in which there is no international food trade, all livestock grain is fed to humans, and there is no food waste (top line), adjusted to include international food trade dividing by 94.8 % food support for no international food trade nor climatic effects, there are no deaths for 10.5 Tg[39]. I guess the societal response will have an effect equivalent to assuming international food trade, all livestock grain being fed to humans, and no food waste (see next section), so I supposed the famine deaths due to the climatic effects are negligible up to the climate change induced by 10.5 Tg of soot being injected into the stratosphere in Xia 2022.ā¦
Nevertheless, I am not trying to estimate all famine deaths. I am only attempting to arrive at the famine deaths due to the climatic effects, not those resulting directly or indirectly from infrastructure destruction. I expect this will cause substantial disruptions to international food trade.
I do think there will be significant disruptions in trade due to the infrastructure destruction. But I also think perhaps the majority of the disruption to food trade in particular would be due to the climate impacts on the nontarget countries, which is the majority of the food production. Furthermore, the climate impacts make the overall catastrophe significantly worse, so I think they will increase the chances significantly of the loss of nearly all trade (not just food). This is a major reason why I expect significantly higher mortality due to climate impacts.
This is because Toon 2008:
Assumed regions were targeted in decreasing order of population [and therefore soot injected into the stratosphere] within 5.25 km of ground zero
I do not endorse this assumption.
Why do you not endorse this for countervalue targeting?
Mitigating starvation after a population loss of 50 % does not seem that different from saving a life now, and I estimate a probability of 3.29*10^-6 of such a loss due to the climatic effects of nuclear war before 2050[58].
Your model of the long-term future impact does not incorporate potential cascading impacts associated with catastrophes, which is why you find the marginal value of saving a life in a catastrophe not very different than saving a single life with mosquito bed nets. This is probably the largest crux. With the potential for collapse of nearly all trade (not just food), I think there is potential for collapse of civilization, from which we may not recover. But even if there is not collapse of civilization, I think thereās a significant chance that worse values end up in AGI.
Nonetheless, I believe it would be a surprising and suspicious convergence if broadly decreasing starvation due to the climatic effects of nuclear war was among the most cost-effective interventions to increase democracy levels, or positively shape the development of transformative artificial intelligence (TAI).I think there is a high correlation between saving lives in a catastrophe and improving the long run future. This is probably clearest in the case of reducing the probability of collapse of civilization. Though resilient foods have a longer causal chain to democracy than working directly on democracy, resilient foods are many orders of magnitude more neglected, so it seems at least plausible to me. As for TAI, resilient foods are still orders of magnitude more neglected, which is why my paper indicates they likely have higher long-term cost effectiveness compared to direct work on TAI (or competitive even if one reduced the cost effectiveness of resilient foods by 3 orders of magnitude).
See the reply to the first comment on that post. Paulās āmost humans die from AI takeoverā is 11%. There are other bad scenarios he considers, like losing control of the future, or most humans die for other reasons, but my understanding is that the 11% most closely corresponds to doom from AI.
Paul Christiano argues here that AI would only need to have āpico-pseudokindnessā (caring about humans one part in a trillion) to take over the universe but not trash Earthās environment to the point of uninhabitability, and that at least this is amount of kindness is likely.
It is good that 80k is making simple videos to explain the risks associated with EA
Do you mean ārisks associated with AIā?
Were these commenters expecting it to be much cheaper to save a life by preventing the loss of potential in an extinction, than to save a life using near-termist interventions?
I think that commenters are looking at the cost-effectiveness they could reach with current budget constraints. If we had way more money for longtermism, we could go to a higher cost per basis point. That is different than the value of reducing a basis point, which very well could be astronomical, given GiveWell costs for saving a life (though to be consistent, one should try to estimate the long-term impacts of a GiveWell intervention as well).
A nuclear war into a supervolcano is just really unlikely.
A nuclear war happening at the same time as a supervolcano is very unlikely. However, it could take a hundred thousand years to recover population, so if the frequency of supervolcanic eruptions is roughly every 30,000 years, itās quite likely there would be one before we recover.
Plus if there were 1000 people then there would be so much human canned goods left overājust go to a major city and sit in a supermarket.
The scenario Iām talking about is one where the worsening climate and loss of technology means they would not be enough food, so the stored food would be consumed quickly. Furthermore, edible wild species including fish may be eaten to extinction.
Again, Iām not saying that I think it doesnāt matter, but I think my answers are good reasons why itās less than AI
I agree that more total money should be spent on AGI safety than nuclear issues. However, resilience to sunlight reduction is much more neglected than AGI safety. Thatās why the Monte Carlo analyses found that the cost-effectiveness of resilience to loss of electricity (e.g. high-altitude detonations of nuclear weapons causing electromagnetic pulses) and resilience to nuclear winter are competitive with AGI safety.
Neglectedness in the classic sense. Although not as crowded as climate change, there are other large organizations /ā institutions that address nuclear risk and have been working in this space since the early Cold War.
I agree that the nuclear risk field as a whole is less neglected than AGI safety (and probably than engineered pandemic), but I think that resilience to nuclear winter is more neglected. Thatās why I think overall cost-effectiveness of resilience is competitive with AGI safety.
Nice post!
I think it would be helpful to see an overlay of our actual trajectory. Though the absolute values of the models are not that different for the period 2000 to 2020, the slopes are quite different. I think there was a paper analyzing the fits including the slopes. The increase of production of food since the year 2000 has been much larger than any of the models predicted. Also, I think the increase in industrial capacity is higher than any of these models. Interestingly, some people interpret this as us overshooting farther, so then we will fall more dramatically. But because we generally have not seen reduction in slopes, I donāt really see evidence for this, so I think that the optimistic interpretation is more likely to be right, basically that we have innovated around limits to growth so far.