Increase in future potential due to mitigating food shocks caused by abrupt sunlight reduction scenarios

By Vasco Grilo🔸 @ 2023-03-28T07:43 (+12)

Disclaimer: this is not a project from Alliance to Feed the Earth in Disasters (ALLFED).

Summary

Acknowledgements

Thanks to Anonymous Person.

Introduction

ASRSs involve a significant reduction in the amount of sunlight reaching the Earth’s surface. This causes temperatures to drop, so agricultural yields decrease, and so does food supply. ASRSs can be a nuclear winter, volcanic winter, or impact winter.

I estimated here the increase in future potential due to globally (and fully) or nationally (and fully) mitigating food shocks caused by ASRSs conditional on them happening. The present analysis leverages these results, and weights them by the likelihood of the various levels of severity of ASRSs. The output can be interpreted as estimates for the importance/scale of the problem resilient food solutions are trying to solve.

I encourage you to check the methods of my previous analysis, which include quite speculative assumptions, to see how much to trust the results I get here. However, I believe one should also have in mind the output of that analysis, i.e. the badness of ASRSs by level of severity, is not supposed to be very resilient. It is only meant to be an improvement on the direct guesses of that factor provided in Denkenberger 2022 (whose evaluation by The Unjournal is here), and this post from Marie Buhl.

If not accuracy, I hope my explicit modelling at least increases reasoning transparency, and therefore enables criticism to be more constructive.

Methods

I estimated the increase in future potential due to mitigating food shocks caused by ASRSs from the sum of those linked to nuclear war and volcanic eruptions. In comparison to these, the risk from asteroids and comets is negligible. Based on Toby Ord’s best guesses given in Table 6.1 of The Precipice, the existential risk between 2021 and 2120 from asteroids and comets is 1 % (= 10^-4/0.01) that from supervolcanoes, and 0.1 % (= 10^-4/0.1) that from nuclear war.

The data and calculations are in this Sheet (see tab “TOC”) and this Colab. I modelled all variables as independent distributions, and ran a Monte Carlo simulation with 100 k samples per variable to get the results[3].

Nuclear war

I estimated the increase in future potential due to mitigating food shocks caused by ASRSs linked to nuclear war between 2024 and 2100 from the product between:

Volcanic eruptions

I estimated the increase in future potential due to mitigating food shocks caused by ASRSs linked to volcanic eruptions between 2024 and 2100 from the product between:

Results

The key results are in the tables below. The full results are in the Sheet.

Key stats

Where the food shocks are mitigated

Increase in future potential due to mitigating food shocks caused by ASRSs as a fraction of the current value of the future (bp)

Mean

5th percentile

95th percentile

World

37.2

-73.1

199

Mean country

0.919

-4.29

8.03

Best country

45.2

-66.6

214

10th best country

4.14

-5.64

21.9

10th worst country

-0.976

-4.59

1.50

Worst country

-44.9

-178

66.4

Global mitigation

Each point refers to a soot interval spanning 0.1 Tg[10]. For example, that of 0.05 Tg respects the interval from 0 to 0.1 Tg.

National mitigation

Countries where the food shocks are mitigated by descending order of increase in future potential

Increase in future potential due to mitigating food shocks caused by ASRSs as a fraction of the current value of the future (bp)

Ranking

Country

Mean

5th percentile

95th percentile

1

United States

45.2

-66.6

214

2

Japan

20.3

-29.9

95.9

3

Germany

19.1

-29.9

99.5

4

United Kingdom

12.9

-21.4

68.9

5

France

10.3

-15.0

59.1

6

Canada

9.58

-13.2

42.4

7

South Korea

9.28

-13.9

44.2

8

Italy

8.07

-12.3

46.8

9

Netherlands

5.01

-7.74

26.5

10

Poland

4.14

-5.64

21.9

136

Kazakhstan

-0.976

-4.59

1.50

137

United Arab Emirates

-1.09

-4.41

1.52

138

Pakistan

-1.33

-7.70

1.88

139

Saudi Arabia

-1.33

-9.26

1.55

140

Turkey

-1.43

-7.82

1.90

141

India

-1.78

-9.07

2.86

142

Vietnam

-1.78

-11.0

2.70

143

Iran

-3.52

-18.8

5.37

144

Russian

-5.42

-23.4

9.24

145

China

-44.9

-178

66.4

Discussion

Global mitigation

According to my results, globally mitigating food shocks caused by ASRSs between 2024 and 2100 leads to an increase in future potential of 37.2 bp (5th to 95th percentile, -73.1 to 199). This is 4.83 (-9.50 to 25.9) times Toby Ord’s best guess of 7.70 bp (= 1 - (1 - 0.1 %)^(77/100)) for the existential risk from nuclear war for the same period assuming constant annual risk. Nevertheless, it is unclear whether my estimate is directly comparable to Toby Ord’s guess:

If the value of the future were binary, a change in it would be directly proportional to the probability of an existential catastrophe, in which case my estimate would be directly comparable to Toby Ord’s guess.

I find mitigating food shocks has both positive and negative heavy tails, as is illustrated in the 1st graph for the case of global mitigation[11]. This is essentially because, in my model, I assume a 25 % chance the future would be worse for higher socioeconomic indices (details here).

Arguments for the existence of a counterproductive heavy tail are described in Kokotajlo 2020 (whose EA Forum crosspost is here):

We canvass arguments EAs have given for the existence of a positive (or “right”) heavy tail and argue that they can also apply in support of a negative (or “left”) heavy tail where counterproductive interventions do orders of magnitude more harm than ineffective or moderately harmful ones.

The 2nd and 3rd graphs show the increase in future potential due to globally mitigating food shocks is not driven by very severe ASRSs[12]. 5 %, 50 % and 95 % of the increase come from ASRSs whose soot ejection into the stratosphere is smaller than 5.90, 31.4 and 66.7 Tg. Larger soot ejections lead to greater drops in food production, but they are rare, so their expected harm ends up playing a minor role in my model.

National mitigation

The increase in future potential due to nationally mitigating food shocks varies greatly across countries. It is:

These estimates illustrate the presence of both left and right tails. Furthermore, nationally mitigating food shocks is harmful not only in pessimistic cases, but also in expectation in 40.7 % (= 59/145) of the countries I analysed. The reasons are (see discussion here):

Is it possible that nationally mitigating food shocks robustly increases real GDP in the nearterm, but accidentally leads to a worse future if it decreases global socioeconomic indices weighted by influence? Is this even a real trade-off? Would it be better to use socioeconomic indices multiplied, instead of weighted, by real GDP as a proxy for future potential, such that greater real GDP would always be good? I am uncertain about the answers.

Cost-effectiveness

The cost-effectiveness of an intervention to mitigate food shocks can be obtained from the ratio between the increase in future potential it causes, and its cost. The former can be calculated by inputting a relative increase in food supply in this model, and then running the present analysis with the updated quantile functions for the increase in future potential by ejection of soot into the stratosphere.

Here I got a (marginal) cost-effectiveness of 3.95 bp/G$ for the area of longtermism and catastrophic risk prevention. To meet that bar, an intervention costing 10 M$ would have to cause an increase in future potential equal to 0.106 % (= 3.95*0.01/37.2) of that of global full mitigation.

The (longterm) cost-effectiveness of resilient food solutions is estimated in Denkenberger 2022 (whose evaluation by The Unjournal is here), and this post from Marie Buhl. I may estimate it too in the future.

  1. ^

     Value of the future, which I think about as expected total hedonistic utility.

  2. ^

     1 Tg corresponds to 1 Mt.

  3. ^

     For me, the running time is 7 min.

  4. ^

     This corresponds to an annual probability of 0.249 % (= 1 - (1 - 0.175)^(1/(2100 - 2024 + 1))).

  5. ^

     The mean of this distribution is 33.4 Tg, which is 1.13 (= 33.4/30) times that of Luisa.

  6. ^

     The mean of this adjustment factor is 84.4 %.

  7. ^

     3,805 from the United States, 4,330 from Russia, 300 from France, and 205 from the United Kingdom.

  8. ^

     I approximated each quantile function by 1001 points corresponding to the quantiles 0, 0.001, 0.002, …, 0.999 and 1.

  9. ^

     Because there should be no change in the potential of the future if there is no soot ejected into the stratosphere.

  10. ^

     Except for the point of 150 Tg, which goes from 150 to 15 k Tg, such that there is a bump at the end of the line.

  11. ^

     The graphs for national mitigation can be obtained in tab “Increase in future potential - quantile functions”, selecting the desired country in the dropdown menu of A4.

  12. ^

     The graphs for national mitigation can be obtained in tab “Increase in future potential by soot - PDFs and CDFs”, selecting the desired country in the dropdown menu of A2.

  13. ^

     Relative to the mean across countries weighted by real gross domestic product.

  14. ^

     As a first approximation, low Varieties of Democracy’s main index (see table here).


Stan Pinsent @ 2023-03-28T11:49 (+8)

My attempt to summarize why the model predicts that preventing famine in China and other countries will have a negative effect on the future:

Or as the author puts it in a discussion linked above:

To be blunt for the sake of transparency, in this model, the future would improve if the real GDP of China, Egypt, India, Iran, and Russia dropped to 0, as long as that did not significantly affect the level of democracy and real GDP of democratic countries. However, null real GDP would imply widespread starvation, which is obviously pretty bad! I am confused about this, because I also believe worse values are associated with a worse future. For example, they arguably lead to higher chances of global totalitarianism or great power war.

I agree with the author that the conclusion is confusing. Even concerning.

I'd suggest that the conclusion is out-of-sync with how most people feel about saving lives in poor, undemocratic countries. We typically don't hesitate to tackle neglected tropical diseases on the basis that doing so boosts the populations of dictatorships.

Vasco Grilo @ 2023-03-28T14:16 (+2)

Thanks for the great summary, Stan!

I'd suggest that the conclusion is out-of-sync with how most people feel about saving lives in poor, undemocratic countries. We typically don't hesitate to tackle neglected tropical diseases on the basis that doing so boosts the populations of dictatorships.

I agree. At the same time, I do not think we can take the status quo for granted, because reality is often quite complex. For example, most people do not hesitate to eat factory-farmed animals, but the scale of their (negative) welfare may well outweight that of humans (see here).

This is not to say I am confident socioeconomic indices weighted by real GDP are a better proxy for longterm value than population:

Is it possible that nationally mitigating food shocks robustly increases real GDP in the nearterm, but accidentally leads to a worse future if it decreases global socioeconomic indices weighted by influence? Is this even a real trade-off? Would it be better to use socioeconomic indices multiplied, instead of weighted, by real GDP as a proxy for future potential, such that greater real GDP would always be good? I am uncertain about the answers.

However, do you think halving the population of the United States while doubling that of China would be good in the longterm (assuming constant socioeconomic indices)? I think it would be bad in expectation (although with high uncertainty) because the world would then have a major undemocratic superpower with 4 times as much GDP as the wealthiest democratic country.

I think saving lives would be more important in terms of longterm value if the population loss was higher, because then it would be reducing the chance of extinction. I think it is quite hard for a nuclear war to lead to extinction, so I preferred using socioeconomic indices to estimate future value.

We should also consider saving lives in low-income countries can affect their socioeconomic indices, which seems to be a neglected topic. From Kono 2009 (emphasis mine):

Although many people have argued that foreign aid props up dictators, few have claimed that it props up democrats, and no one has systematically examined whether either assertion is empirically true. We argue, and find, that aid has both effects. Over the long run, sustained aid flows promote autocratic survival because autocrats can stockpile this aid for use in times of crisis. Each disbursement of aid, however, has a larger impact on democratic survival because democrats have fewer alternative resources to fall back on.

In my model, mitigating the food shock of any given country counterfactually increases its real GDP per capita, and therefore socioeconomic indices.