DannyBressler

Karma: 410

[Link] Vox Article on Engineered Pathogens/ Global Catastrophic Biorisks

DannyBressler6 Dec 2018 22:46 UTC

23 points

5 comments1 min readEA link

DannyBressler 7 Dec 2018 1:13 UTC
1 point
0 ∶ 0
in reply to: Michael_S’s comment on: [Link] Vox Article on Engineered Pathogens/ Global Catastrophic Biorisks
Glad to hear!

DannyBressler 11 Dec 2018 0:47 UTC
4 points
0 ∶ 0
in reply to: Ward’s comment on: [Link] Vox Article on Engineered Pathogens/ Global Catastrophic Biorisks
I don’t think there is much publicly available on this topic besides Koblentz’s work (also check out his 2003 article in International Security). The “strategy of conflict” as it pertains to bioweapons is something we thought about, but we don’t discuss it much in our paper. Some thoughts:
Historically bioweapons research has focused on diseases that are not transmissible person to person like Tularemia, Anthrax, Q Fever, and Botulism. If you dump a bunch of anthrax spores from an airplane over a city, you would kill a lot of people (I recall seeing a study where they estimated that if you dumped anthrax over a large city you would kill ~200,000 people) even though it’s not transmissible person to person.
Japanese Unit 731 used Plague, which is transmissible person to person, but used it well behind enemy lines on enemy cities to limit collateral damage. This made this sort of weapon more of a poor man’s strategic bombing campaign that could wreak havoc on civilian populations by dumping swarms of plague infested fleas on enemy territory. There is a lot of uncertainty on the actual numbers, but Unit 731 may have killed more civilians in China through these sorts of attacks than the US killed Japanese civilians in Japan from the nuclear bombs and firebombings (the exact numbers are hard to know in large part because it’s hard to attribute civilian deaths directly to the released bioweapons because the weapon is meant to present itself as a natural epidemic, as we mention in the paper). There is evidence that the Japanese did sustain some collateral damage from their plague attacks against China during the war: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1200679/.
Starting a pandemic transmissible Person to Person in the enemy’s country is probably a bad idea because it could turn into a global pandemic and there is significant collateral damage to your own country. Though, it should be noted that using other WMDs like nuclear weapons also has significant, and possibly similar scale, collateral damage. One of the dangers of future development in biotechnology is that it could make biological weapons more attractive as a weapon.
Determining strategic behavior and implications of using weapons that impose significant collateral damage to the country using them and to non-combatant countries is actually an active research topic of mine.

How Many People Will Climate Change Kill? [Video]

DannyBressler19 Jul 2019 20:11 UTC

36 points

4 comments1 min readEA link

DannyBressler 19 Jul 2019 21:30 UTC
3 points
0 ∶ 0
in reply to: Kirsten’s comment on: How Many People Will Climate Change Kill? [Video]
I answer these questions and go over the methodology in detail in the video. A working paper will be coming soon, but for now all of the details are in the video.

DannyBressler 10 Sep 2019 16:55 UTC
22 points
0 ∶ 0
on: [updated] Global development interventions are generally more effective than Climate change interventions
Below is one important point that I think is extremely difficult to know without being an active researcher in the field. Hauke hints at it in his footnote 6, but I want to expand on it since I think it is important to understand where the social cost of carbon estimates are coming from:
Ricke et al. 2018 (https://www.nature.com/articles/s41558-018-0282-y) are using a climate damage function that predicts much higher damages than the damage function that is used in the main integrated assessment models (IAMs) that predict the social cost of carbon (DICE, FUND, and PAGE). (I’ve included a note with links on this below for those who are interested). This results in an important point:
Most of the difference in the social cost of carbon between Ricke et al. 2018 and the main IAMs is because they are using different damage functions, not because they are accounting for greater marginal utility of consumption to individuals with lower consumption levels.
The more appropriate control would be to compare Ricke et al. 2018 to the gro-DICE model developed by Diaz & Moore 2017 ( https://www.nature.com/articles/nclimate2481 ), which uses a damage function that is more similar to Ricke et al. 2018. gro-DICE projects a social cost of carbon of $220, compared to Ricke et al.’s $415. However, the gro-DICE damage function is still less damaging than Ricke et al’s damage function. Ideally, we would want to do a comparison of the social cost of carbon using the same damage function (so we could isolate just the effect of differences in marginal utility), but unfortunately we can’t readily do this because these papers are all using different damage functions. Given that Ricke et al. are using the most damaging damage function, we do know that the effect would be less.

Note on climate damage functions: Ricke et al. 2018 use a damage function based off of Burke, Hsiang, and Miguel 2015 ( https://www.nature.com/articles/nature15725 ). This is the “most damaging” of the damage functions in the literature. Diaz & More 2017 uses a damage function based on Dell, Jones, and Olken 2012 ( https://www.aeaweb.org/articles?id=10.1257/mac.4.3.66), which is more damaging than the damage functions used in traditional IAMs, but not as damaging as the Burke, Hsiang, and Miguel 2015 damage function used in Ricke. et al. 2018.
These analyses predict much higher climate damages than the analysis that make up the DICE-2016 damage function (the DICE-2016 damage function is derived here: https://cowles.yale.edu/sites/default/files/files/pub/d20/d2096.pdf ). The reason for this is differences in econometric strategy, which is often called the “levels vs. growth debate.” See Auffhamer 2018 ( https://www.aeaweb.org/articles?id=10.1257/jep.32.4.33 ) for a nice discussion of the reason why these vary. In general, this is an active debate in the field and there is not consensus on the appropriate way to predict economic damages from climate. 2018 Nobel winner William Nordhaus, for instance, would fall in the “levels” camp, and young superstar researchers Solomon Hsiang from Berkeley and Marshall Burke from Stanford would fall in the “growth” camp.
What links here?
- [updated] Global development interventions are generally more effective than climate change interventions by Hauke Hillebrandt (2 Oct 2019 8:36 UTC; 119 points)

DannyBressler 17 Aug 2020 6:06 UTC
10 points
0 ∶ 0
in reply to: jackva’s comment on: [Linkpost] Global death rate from rising temperatures to exceed all infectious diseases combined in 2100
1) This hasn’t been through peer review yet, but it’s a project they’ve been working on for years, and this is at least the third iteration (first two iterations: https://epic.uchicago.edu/wp-content/uploads/2019/07/Working-Paper-2.pdf https://bfi.uchicago.edu/wp-content/uploads/BFI_WP_201851.pdf). They’ve presented this paper at many academic conferences where they get criticism and feedback from other experts (including one I’ve been to). Unfortunately, publication timelines are very long in economics, so NBER working papers are where much of the new interesting research is presented. By the time a paper ultimately comes out in an economics journal, it’s oftentimes old news. I’d expect this to publish in a good journal, and I would be surprised if the results change much.
2) They run projections for different emissions scenarios. Figure 9 shows RCP 8.5 and RCP 4.5. You can also go on their website and use their Impact Map to look at different scenarios: http://www.impactlab.org/map/#usmeas=absolute&usyear=2080-2099&gmeas=change-from-hist&gyear=2020-2039&tab=global&gvar=mortality
3) They account for the effects of both income growth and having experience living in a certain climate (what they call adaptation) on mitigating the mortality risk from climate change. Income growth substantially mitigates the mortality effect of climate change as you can see in figure 9a. Their main result of a ⁷³⁄_100,000 increase in the mortality rate in 2100 in RCP 8.5 accounts for the mitigating effect from income. Without higher incomes, it would be ~200/100,000 as figure 9a shows.
4) They use a reduced-form econometric strategy that exploits historical variations in temperatures on an annual basis to find a relationship between mortality and temperatures. Their approach allows them to account for climate-mortality effects that are driven by direct changes in the short-run distribution of temperatures such as the net mortality effect of more hot days and fewer cold days, the mortality effect of increased surface ozone formation, and even the effect of hot days on murders and suicides. However, their approach arguably does not fully capture climate-mortality channels that are driven in part by longer-term pathways that are not econometrically identified from shorter-term temperature fluctuations such as some diseases (like Malaria), flooding, and some causes of undernutrition.
What links here?
- EA Forum Prize: Winners for August 2020 by Aaron Gertler (5 Nov 2020 6:22 UTC; 17 points)

DannyBressler 17 Aug 2020 20:04 UTC
8 points
0 ∶ 0
in reply to: John G. Halstead’s comment on: [Linkpost] Global death rate from rising temperatures to exceed all infectious diseases combined in 2100
The copy you have is their 2019 version of the paper. The figure 9 I am referring to is their most recent 2020 NBER Working Paper version of the paper linked in the original post.
I agree that the RCPs, which were made in 2011, are outdated at this point. This is in large part because of the strong performance of renewable energy over the last decade. The RCPs at this point are still the standard emissions scenarios that are used in scientific papers, although I expect them to be updated in the near future when the next IPCC report comes out. Somewhere between RCP 6.0 (~3.2 degrees C in 2100) and RCP 8.5 (~4.8 degrees C) is probably what you can call a baseline emissions scenario (source: http://live.magicc.org/). The baseline emissions scenario in DICE-2016 for instance—which involves significant reduction in emissions per unit of GDP, continued economic growth, and a small amount of carbon emissions abatement—results in 4.1 degrees C warming in 2100. Still, the Climate Impact Lab results are pretty significant in any of these scenarios as you can see in figure 9a. In RCP 8.5, you get to 3.2 degrees C in about 2065 and you get to 4.1 degrees C around 2085. At both of those dates, there are significant increases in mortality. Just eyballing it, it looks like ~1/2 and ~4/5 of the mortality increase at 4.8 degrees C in 2100 respectively.
Also, if you wanted to look at the net mortality effect of a high emissions scenario with a lot of coal burning, you would also need to consider the effect of this on particulate matter pollution in addition to the affect from changing the climate. The particulate matter effect is very large and the climate impact paper does not account for this. This paper, for instance, does: https://www.nature.com/articles/s41467-019-09499-x/tables/2.
For the mitigating effect of income on mortality, I’d emphasize that there is significant uncertainty in these projections as shown in figure 9b, in large part driven by uncertainty around adaptation. For instance, with 80% confidence, they can’t rule out the mortality effect of climate change being on net positive. Though from the perspective of decision theory, if you have a lottery across the possible outcomes in 2100 that include both sanguine and higher than expected damages and you have risk aversion (which most people do), this would cause you to want to undertake stricter climate policy than if you just look at the central estimate. I’d also emphasize that this is a very active area of research (e.g. this conference is happening next month: https://climateadaptationresearch.com/agenda/) so we will continue to get better at estimating climate impacts net of adaptation.

DannyBressler 25 Aug 2020 21:50 UTC
2 points
0 ∶ 0
on: [Linkpost] Global death rate from rising temperatures to exceed all infectious diseases combined in 2100
FYI, Michael Greenstone (one of the authors of this study, the co-director of the Climate Impact Lab, and the Milton Friedman Distinguished Service Professor in Economics at University of Chicago) testified at a hearing in Congress on the health impacts of climate change a few weeks ago: https://youtu.be/N8nCZC0_yxU His opening statement is available in written form here: http://www.impactlab.org/news-insights/michael-greenstone-testifies-on-the-health-impacts-of-climate-change/

DannyBressler 24 Sep 2020 0:32 UTC
11 points
0 ∶ 0
on: Does using the mortality cost of carbon make reducing emissions comparable with health interventions?
FYI, I gave a presentation on my Mortality Cost of Carbon paper at the UCLA Climate Adaptation conference two days ago, available here: https://event.on24.com/wcc/r/2688287/118B1E2E57B33A902FDE6CE95202DB34 This is a brief (~20 minutes) less technical overview of the paper. My presentation starts at 53:20.
Also, the other two speakers on the panel (Tamma Carleton and Ishan Nath) were both authors on the Climate Impact Lab paper that Louis had posted about earlier: https://forum.effectivealtruism.org/posts/PATHShQoxQLHoZ7rE/linkpost-global-death-rate-from-rising-temperatures-to
My Mortality Cost of Carbon working paper is here: https://ceep.columbia.edu/sites/default/files/content/papers/n11.pdf
What links here?

DannyBressler 15 Oct 2020 2:49 UTC
14 points
0 ∶ 0
on: Avoiding Munich’s Mistakes: Advice for CEA and Local Groups
By the title, I thought this was going to be a discussion of the dangers of appeasing genocidal dictators (e.g. https://www.ynetnews.com/articles/0,7340,L-3476200,00.html) … clearly I was wrong!

N-95 For All: A Covid-19 Policy Proposal

DannyBressler28 Oct 2020 6:43 UTC

21 points

8 comments15 min readEA link

DannyBressler 28 Oct 2020 21:58 UTC
1 point
0 ∶ 0
in reply to: John G. Halstead’s comment on: N-95 For All: A Covid-19 Policy Proposal
Thanks, John! I really like your distinction between the type (1) and type (2) “pernicious moral hazard.”
Yes I agree that the moral hazard I mention here would not be large enough to outweigh the benefits of the policy, putting it in the category of (1). My goal in that “potential issues” section was to think about the universe of potential issues that people could raise about the policy and address them. As you can tell, I don’t currently think any of the issues are significant enough to make the policy not worth it.

DannyBressler 28 Oct 2020 22:20 UTC
1 point
0 ∶ 0
in reply to: Ofer’s comment on: N-95 For All: A Covid-19 Policy Proposal
What I had in mind with this policy was that the government would contract directly with producers (using the defense production act where necessary) to procure enough N-95 respirators for everyone in the country, and the government would then distribute them to everyone. There would be some agreed upon price of procurement between the government and manufacturers that would be negotiated at the start of the process. If manufacturers want to produce more respirators than what they contracted for, they are welcome to do that and to sell it at a price they choose.
What I mean by cannot buy is that N-95s are unavailable to nearly all people who may want to purchase them https://twitter.com/davidrliu/status/1319980228765274112?s=20. I’ve looked online throughout the pandemic, and they are usually unavailable for purchase. Sometimes, you can add them to your cart, but then you can’t check out because you get a warning that they are being prioritized for frontline workers (that screenshot above is me doing exactly that). Sometimes, you can buy more heavy duty P100 respirators that have traditionally been used for doing something like spray painting, but a lot of people prefer not to wear those regularly because they are more bulky.

DannyBressler 28 Oct 2020 23:28 UTC
1 point
0 ∶ 0
in reply to: Tsunayoshi’s comment on: N-95 For All: A Covid-19 Policy Proposal
This is a really good point!
I think you’re right that the magnitude of the benefit from the program depends heavily on how many people end up choosing to use the mask, especially in situations where they are more likely to contract the disease. Individuals will ultimately make a personal decision based on trade-offs between the probability of contracting the virus, comfort, convenience, and even fashion.
I also think there is significant heterogeneity in terms of how people weigh these factors. I do think that there are a significant number of people who, net of these factors, would decide that the benefits of wearing a medical-grade respirator in situations where they are more likely to contract the virus outweighs the costs. These could be seniors, people with preexisting conditions, people who don’t find the respirator uncomfortable, or people who are just risk averse.
I also think that there are currently significant numbers of people who would like to wear medical-grade respirators, but who are not currently able to get them. I have friends that are teachers that are required to teach in person that want a medical-grade respirator, but are not able to get one. As I noted above, there is still a shortage of respirators even for frontline medical workers (see https://www.washingtonpost.com/business/scarcity-of-raw-material-still-squeezes-n95-mask-makers/2020/09/10/94586834-f31e-11ea-8025-5d3489768ac8_story.html). I think there are probably enough people in this category, that you could make some dent in the infection rate with this policy, though how much depends on people’s behavior.
Also, one of the general takeaways is that, even if the benefits end up being modest (e.g. you reduce the infection rate, but not below 1 in all areas), the relative cost is so cheap that I think it’s worth it to give it a shot.
A few other points:
-As part of the program, it would be great to do randomized control trials with different types of respirators (e.g. different designs that meet the N-95 standard, enhanced N-99 or N-100 designs). There may be some sort of trade-off between comfort and protection (granted that the N-95 threshold is met), and perhaps going more on the side of comfort is optimal because the benefit from higher compliance outweighs the slightly lower protection. There may also be an N-95 design that is already produced (or gets produced for the program) that is just more comfortable and gets higher compliance, and we’d be able to figure that out. That face shield you mentioned is really cool! You could also pilot something like that as part of this program, and perhaps that wins out.
-Along these lines, I also considered adding another point, which would be creating a program called the “N-95 for all Studio,” where fashion designers or people like that could add designs to the respirators to make them look cool. You could imagine charging someone $2 or something to get the “New York Yankees N-95″ or the “Tom Ford N-95” or whatever.
-Also as winter comes in the Northern Hemisphere and as more activity moves inside and the ability to ventilate rooms goes down, there will likely be more spaces with a higher concentration of aerosols. The benefit of wearing a respirator vs. cloth mask or surgical mask goes up in this situation, so this would affect people’s behavior.
-I’d also emphasize the benefits of this policy for preparing for future pandemics. It so happens that SARS-COV-2 has a case fatality rate ~1%, and this is quite heterogeneous depending on your age and existing health. If there is a respiratory-transmitted pandemic that has a 30% case fatality rate, then the benefits of wearing a respirator will be way higher versus the costs from inconvenience, discomfort, etc.

The NPT: Learning from a Longtermist Success [Links!]

DannyBressler20 May 2021 0:39 UTC

66 points

6 comments2 min readEA link

DannyBressler 20 May 2021 16:17 UTC
7 points
0 ∶ 0
on: The NPT: Learning from a Longtermist Success [Links!]
One other reason why I think that understanding the NPT is important for longtermists: As the world decarbonizes to address climate change (my other big area of research), nuclear electricity generation may increase substantially into more countries, and in particular to countries with lower levels of development/technology. It’s crucial to know if the existing nonproliferation regime can ensure that this doesn’t cause proliferation, and what sorts of investments must be made to ensure that nonproliferation regime continues to work.

DannyBressler 24 May 2021 0:35 UTC
4 points
0 ∶ 0
in reply to: MichaelA’s comment on: The NPT: Learning from a Longtermist Success [Links!]
1. One piece of info related to the NPT that might be helpful: The NPT does contain an article (article VI) in which the the P5 (the 5 current permanent members of the UN Security Council, who at the time the NPT was made were the only countries who had successfully tested nuclear weapons) as well as all of the parties agree to participate in good-faith negotiations to pursue nuclear disarmament, but it does not specify a time-table and the language is deliberately vague. I think the NPT has done a good job of doing what its main goal is and what its name implies: limiting nuclear proliferation. It has clearly not been able to get existing nuclear powers to get rid of all of their nuclear weapons (although it’s hard to know if the NPT has not played a significant role in reducing the arsenals of the nuclear powers relative to a counterfactual world in which there was no NPT… perhaps in a counterfactual world without the NPT, the US and USSR would not feel compelled to engage in the SALT and START negotiations without officially committing in Article VI of the NPT). Luisa has done a lot more thinking about the Nuclear Ban treaty, so I’ll defer to her on that.
2. Jeffrey Ohl is going to look into this question as part of a summer project for the Stanford Existential Risk Initiative, and I’ll be mentoring him. We literally just started talking about the project last week, so more to come on that! For now, I’ll say the characteristics of the technology itself that you are trying to regulate (e.g. fissile material vs. inputs to the creating of AGI for instance) is very important in terms of how a successful treaty could be constructed. This aspect is important in terms of the mechanisms that must be put in place to verify compliance with the treaty. I co-wrote an article with Chris Bakerlee on engineered pathogens for Vox a few years ago that discusses, among other things, some of the challenges around regulating biotechnology that make verifying compliance with the Biological Weapons Convention difficult https://www.vox.com/future-perfect/2018/12/6/18127430/superbugs-biotech-pathogens-biorisk-pandemic
3. What time range are you looking at when it comes to forecasts, and what sort of things do you have in mind? I recall when I read Superforecasting a few years ago that forecasts aren’t particularly reliable beyond a few years even for Superforecasters (though correct me if I’m wrong/maybe views on that are different now than they were then?). These treaties operate on pretty long time-scales… e.g. the NPT was conceived of in the mid 1960s, it was signed in 1968, it went into force in 1970, and then countries joined over the course of a few decades. https://en.wikipedia.org/wiki/List_of_parties_to_the_Treaty_on_the_Non-Proliferation_of_Nuclear_Weapons

DannyBressler 28 May 2021 23:18 UTC
1 point
0 ∶ 0
in reply to: simonfriederich’s comment on: The NPT: Learning from a Longtermist Success [Links!]
Yes, I think it is. There is a literature on whether nuclear assistance and technology sharing for peaceful uses tends to promote or hinder nuclear proliferation, that I mention and cite a bit in my second CSIS piece.

DannyBressler 16 Feb 2022 17:29 UTC
19 points
0 ∶ 0
on: Cost Effectiveness of Climate Change Interventions
Thank you for this post on a very important topic! And thank you for the kind words on my Mortality Cost of Carbon paper.
I think that, at least from the perspective of using my paper, the analysis is actually much simpler than what you do above. Instead of using the 83 million cumulative 2020-2100 excess deaths, use the mortality cost of carbon itself: i.e. the number of lives saved per ton of carbon dioxide reduced, which is provided by the paper. So instead of the equation you show above, the equation now becomes:
Marginal Cost Per Life Saved = (Marginal Cost Per Ton CO_2 reduced)/(The Mortality Cost of Carbon)
@Louis_Dixon performed this analysis before in a really nice post Does using the mortality cost of carbon make reducing emissions comparable with health interventions? - EA Forum (effectivealtruism.org) and found that using carbon dioxide reduction estimates from a Founder’s Pledge report:
- Future pessimistic - $5.50 per tonne, so $23,400 to avert 4,255 tons*
- Future realistic - $0.29 per tonne, so $1,234 to avert 4,255 tons
- Future optimistic - $0.03 per tonnes, so $127 to avert 4,255 tons
The issue with your original equation above is that you are implicitly assuming linearity, i.e. assuming that the marginal cost of saving a life from marginally reducing emissions is equivalent to the average cost of saving a life if we were to reduce emissions all the way to zero. However, one of the findings of the Mortality Cost of Carbon paper is that the system is actually nonlinear and highly convex, so the number of lives saved from marginally reducing emissions is actually much greater than the average number of lives saved that you would get per ton if you were to reduce all the way to zero (see figure 4). This is all a fancy way to say that there are diminishing marginal returns in terms of saving lives from reducing carbon dioxide on a planetary scale. So to determine the marginal impact of reducing emissions, use the marginal estimates provided by the paper (the mortality cost of carbon).
And of course, as you mention above, the mortality cost of carbon is just the projected number of excess deaths from 2020-2100 caused by marginal emissions due to temperature-related mortality—i.e. the net effect of more hot days (bad for mortality) and fewer cold days (good for mortality). It leaves out potentially important climate-mortality pathways such as the effect of climate change on infectious disease, civil and interstate war, food supply, flooding, as well as the co-benefit from less air pollution. Despite these limitations, Louis was still finding that these projections were cost-competitive with Givewell’s top recommendations.
*Note that Louis was using the 2020 Working Paper version of the Mortality Cost of Carbon, which included all mortality sources from the 2014 WHO paper (one of three papers used to construct the mortality damage function, which Andrew also mentions in the post), whereas the 2021 published version of the paper in Nature Communications used just the temperature-related mortality estimates from the 2014 WHO report. This ends up leading to a slight difference in the mortality cost of carbon estimate, from ¹⁄₄₂₅₅ in the working paper version to ¹⁄₄₄₃₄ in the published paper version. Recalculating Louis’s analysis with the published paper version numbers yields:
- Future pessimistic - $5.50 per tonne, so $24,387 to avert 4,434 tons*
- Future realistic - $0.29 per tonne, so $1,286 to avert 4,434 tons
- Future optimistic - $0.03 per tonnes, so $133 to avert 4,434 tons
What links here?
- Cost Effectiveness of Climate Change Interventions by andrew_richardson (16 Feb 2022 2:58 UTC; 23 points)

DannyBressler

[Link] Vox Ar­ti­cle on Eng­ineered Pathogens/​ Global Catas­trophic Biorisks

How Many Peo­ple Will Cli­mate Change Kill? [Video]

N-95 For All: A Covid-19 Policy Proposal

The NPT: Learn­ing from a Longter­mist Suc­cess [Links!]

[Link] Vox Article on Engineered Pathogens/ Global Catastrophic Biorisks

How Many People Will Climate Change Kill? [Video]

The NPT: Learning from a Longtermist Success [Links!]