DannyBressler

U.S. Reg­u­la­tory Up­dates to Benefit-Cost Anal­y­sis: High­lights and En­courage­ment to Sub­mit Public Comments

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

The In­ter­gov­ern­men­tal Panel On Global Catas­trophic Risks (IPGCR)

• DannyBressler 7 Apr 2023 3:23 UTC

  42 points

  8 ∶ 0

  on: Planned Up­dates to U.S. Reg­u­la­tory Anal­y­sis Meth­ods are Likely Rele­vant to EAs

  Thank you for sharing! For those interested in this topic, I’d highly suggest making a public comment on the new drafts of Circular A-4 and Circular A-94.
  
  I think the public commenting instructions should be up on OMB’s Federal Register page soon (it looks like tomorrow and the commenting period typically lasts 45-60 days): Federal Register :: Agencies—Management and Budget Office .

  Public comment is an important part of the regulatory process, and agencies actually do pay attention to what people say. In addition, comments that are supportive of the approach taken are equally as valuable as critical comments.

How Many Peo­ple Will Cli­mate Change Kill? [Video]

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

• 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)

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

• 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 19 May 2023 1:03 UTC

  17 points

  1 ∶ 0

  on: How much should gov­ern­ments pay to pre­vent catas­tro­phes? Longter­mism’s limited role

  I’m pretty late to the party here, but I want to say I really enjoyed the piece! Your piece came out only three weeks before the big draft overhaul to the way that the U.S. does benefit-cost analysis came out, which is in a document called Circular A-4. I think there is a lot I’d change around the choices in the analysis, particularly in light of the new draft A-4 Guidance (most of which goes in favor of putting more weight on catastrophes):

  • The old A-4′s use of a 7% discount rate on capital didn’t make sense because the 7% includes other factors outside of time preference (in particular risk aversion). The new A-4 has a much better treatment of discounting capital: which is applying a shadow price of capital adjustment, which is somewhere between a factor of 1-1.2 (so it’s not too much of an adjustment in any case). The upshot of all of this is that, based on the new A-4, you should be using a 1.7% discount rate for impacts out to 30 years, which is drastically different than the 7% discount rate that you were using and which will put more weight on the future (and appropriately so from the descriptive point of view to reflect people’s tradeoffs between money now and money in the future in capital markets).

  • For impacts beyond 30 years, standard economic theory and the new A-4 suggest that you should be using a declining discount rate to account for future interest rate uncertainty (see my brief description here). The A-4 preamble has a proposed schedule of declining discount rates, which goes down to 1% 140 years in the future. This will also place more value on the future.

  • President Biden’s Presidential Memorandum and the new A-4 are quite clear (see summary of A-4′s temporal scope of analysis section) that the interest of future generations should be taken into account when they will be impacted by important benefits and costs from some policy. In fact, the U.S. had previously been accounting for the impacts of climate change out to 500 years in BCA (in the Obama, Trump, and Biden administrations) through the use of the Social Cost of Greenhouse Gases, so impacts on future generations had been taken into account in that context, and should be taken into account in these other contexts as well, as discussed in the new draft A-4.

  • Much of your analysis seems to only look at the direct impacts on Americans. However, A-4 has a robust discussion around the conditions under which it is important for analysts to include global impacts, such as “regulating an externality on the basis of its global effects supports a cooperative international approach to the regulation of the externality by potentially inducing other countries to follow suit or maintain existing efforts.” This recognizes that global externalities/​risks like pandemics, biosecurity, climate change, etc. require international regulatory cooperation. If, e.g., a new global pandemic is caused by poor biosecurity regulatory oversight in other countries, this harms Americans. Both because Americans will get sick and die, but also because disruptions in other countries will cause significant harm to the global economy, global trade, and global stability that will in turn harm Americans. Just as poor biosecurity regulatory oversight in the U.S. causing a pandemic will cause harm in other countries for the same reasons. Note that this is also the approach that the U.S. Government has taken to account for climate change in BCA through the Social Cost of Greenhouse Gases by considering global damages from climate change and not just domestic damages. As that document states, global externalities like greenhouse gas emissions and biosecurity policy imply that the whole world enjoys the benefit of one country’s decisions to reduce the harm from the global externality, and therefore “the only way to achieve an efficient allocation of resources for emissions reduction on a global basis—and so benefit the U.S. and its citizens and residents—is for all countries to consider estimates of global marginal damages” from the externality as well as the global marginal benefits of taking actions to reduce the externality.

  • Although your post is about risks, I didn’t see mention of accounting for Risk Aversion, which is one of the most consistent features of human preferences and should be reflected in BCA. The draft A-4 instructs BCA practitioners to explicitly account for uncertainty when doing BCA as well as risk aversion across that uncertainty. This ends up placing more weight on the benefits that help to avoid catastrophes, and thus would tend to favor policies that reduce the probability of catastrophes (e.g. pandemic preparedness).

  • And finally, much of your analysis seems to hinge on probabilities for catastrophes that come from e.g. the EA community or Prediction Markets. Because you choose to account for a very limited scope of impacts across time and space at a very high discount rate, those probabilities end up having to do a lot of work for the analysis to yield net benefits. My sense is for the purposes of BCA for U.S. regulatory impact assessments, these probabilities may be viewed as too speculative (at least for anthropogenic risks) and may be challenged in getting through the various processes that BCAs for regulations must go through including public comment, OIRA review, and then ultimately litigation in court where most rules are inevitably challenged. Fortunately, A-4 has a tool that provides a way forward in this situation: Break Even Analysis. Break-even analysis provides a way forward when there is a high degree of uncertainty/​ambiguity in important parameters, and you need to determine what those parameters would need to be for the policy to still yield positive net benefits. This is particularly relevant for catastrophic events: “For example, there may be instances where you have estimates of the expected outcome of a type of catastrophic event, but assessing the change in the probability of such an event may be difficult. Your break-even analysis could demonstrate how much a regulatory alternative would need to reduce the probability of a catastrophic event occurring in order to yield positive net benefits or change which regulatory alternative is most net beneficial.”

  To Summarize, I think U.S. BCA practice actually offers a much wider variety of tools for assessing catastrophic risks, which benefits the interest and welfare of Americans, and those tools should be utilized.

• 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!

• DannyBressler 18 May 2023 23:44 UTC

  12 points

  1 ∶ 0

  in reply to: Larks’s comment on: U.S. Reg­u­la­tory Up­dates to Benefit-Cost Anal­y­sis: High­lights and En­courage­ment to Sub­mit Public Comments

  I think you’re referring to the difference between Executive Order 12866 (from the Clinton Administration in 1993) and Executive Order 12291 (From the Reagan Administration in 1981).

  The Office of Management and Budget is only asking for comment on Circular A-4 and Circular A-94, not on Executive Order 12866, so I would not suggest making comments on that.

  Also, the administration released a new Executive Order 14094 on the same day that the A-4 and A-94 updates were released, which reaffirmed executive order 12866 but made some important changes, for instance increasing the definition of significant regulatory action from $100 million to $200 million, which in my view is a reasonable/​helpful thing to do to save administrative capacity. Executive order 12291 required OIRA to look over every regulatory impact assessment regardless of the size, which in consequence meant that they were in inundated with reviewing ~2400 rules a year and therefore it was more difficult to carefully review proposed regulations. OMB is not seeking comment on Executive Order 14094, so I would not suggest making comments on that either.

  The part of Executive Order 12866 that is highlighted in the draft A-4 update is: ”...in choosing among alternative regulatory approaches, agencies should select those approaches that maximize net benefits (including potential economic, environmental, public health and safety, and other advantages; distributive impacts; and equity), unless a statute requires another regulatory approach.” So they are interested in maximizing net benefits. You’re right that there is one line in 12866 (which is a 10-page order) that says “Each agency shall assess both the costs and the benefits of the intended regulation and, recognizing that some costs and benefits are difficult to quantify, propose or adopt a regulation only upon a reasoned determination that the benefits of the intended regulation justify its costs.” My sense is that this was written because there are often important categories of benefits and costs that are difficult to place a reliable value on (or at least one that would get through OIRA review and taken seriously if the regulation is challenged in court). But it’s still important to state and discuss important unmonetized in BCA (this is covered on pages 43-47 of the new draft A-4.). Catastrophic impacts that have highly uncertain probabilities often fall in this category (see my discussion in the main post around how break-even analysis is useful in this context). 12866 is making sure that analysts have the option to account for these unmonetized benefits and costs.

  In practice, my sense is that agencies do typically want to show that monetized benefits exceed costs, because this makes it more likely that things will pass OIRA review and that the regulation will make it through the courts. I’d highly recommend this interview with OIRA chief Ricky Revesz if you’re curious on this: a typical administration has ~70% of its rules upheld when challenged in courts, and a strong benefit cost analysis supporting the rule certainly helps with that process. And in any case, 12866 and the draft A-4 does direct agencies to choose the option that maximizes net benefits. My sense is that the one line of language around benefits justifying costs was intended to address situations where important benefits or costs cannot be reasonably monetized in a way that would pass OIRA review/​make it through litigation but are still important. But even so, my sense is that it is rare for monetized costs to exceed benefits in BCAs, and that there was not some type of step-change when 12866 was passed in 1993 where a bunch of regulations were proposed with monetized costs exceeding monetized benefits.

  So to summarize, I actually think that small change in language from 12291 to 12866 thirty years ago was on net a good thing and not a bad thing, and in any case they are not asking for comment on the executive orders. But if there are things in the draft A-4/​A-94 you like (or not) I’d highly recommend writing a comment.

• 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?

  • Cost Effec­tive­ness of Cli­mate Change Interventions by andrew_richardson (16 Feb 2022 2:58 UTC; 23 points)
  • DannyBressler's comment on Cost Effec­tive­ness of Cli­mate Change Interventions by andrew_richardson (16 Feb 2022 17:29 UTC; 19 points)
  • The DICE-2023 model of the So­cial Cost of Car­bon has re­vised up the harms of cli­mate change, and down the costs. At what point does cli­mate change be­come cost com­pet­i­tive with global poverty char­i­ties? by andrew_richardson (14 Apr 2023 17:22 UTC; 19 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)

New Study in Science Suggests a Se­vere Bot­tle­neck in Hu­man Pop­u­la­tion Size 930,000 Years Ago

• 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 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 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.

• DannyBressler 2 Feb 2024 6:00 UTC

  3 points

  0 ∶ 0

  in reply to: jackva’s comment on: The In­ter­gov­ern­men­tal Panel On Global Catas­trophic Risks (IPGCR)

  Thanks for this comment! I am definitely in favor of country-level efforts to address GCRs and to produce reports like this one. The same way that the U.S. produces the National Climate Assessment despite there also being IPCC reports. In this case, I think those two efforts are more complimentary than cannibalistic. E.g., folks that work on the National Climate Assessment in the US often also work on the IPCC and doing the work of organizing/​prepping for one helps with organizing/​prepping for another. And having an international IPGCR effort may also encourage countries to undertake their own national GCR efforts.

  Also, my sense is that the IPCC tends to be more conservative in its findings/​statements compared to the National Climate Assessment because it requires a level of buy-in and sign off from its 195 member countries, whereas the National Climate Assessment is produced by a single country. My hypothesis is that a similar dynamic may end up being the case here, where the IPGCR may produce findings that are more conservative than what a single country might produce. But this is still helpful because it gives a sense of which sorts of policies may be palatable globally.

  In terms of this effort being a potential cause of political polarization on GCRs, my sense is that in the climate case, the IPCC has not been a driver of the political polarization we’ve seen. Of course, there has been a lot of political division on climate action, but my sense is that the IPCC itself has played little role in causing this. On the contrary, I’ve seen the IPCC as playing a major role in effectively establishing a set of basic knowledge (and corresponding levels of confidence, as their findings are always given with a level of confidence) around climate change, that those skeptical of climate action find it hard to argue with. There is a lot more that is less certain those those skeptical of climate action now debate over (e.g. the benefits and costs of climate action, ability to coordinate global policy to overcome free-riding, etc.), but I think the IPCC has been useful in making it difficult to credibly argue with some of the more basic climate knowledge where there is a good deal of consensus. I often here speakers that are skeptical of climate action going out of their way to emphasize that they agree with key findings of the IPCC to avoid seeming unreasonable.

  I see the IPGCR as producing reports that convey areas of consensus, disagreement, and uncertainty among experts from around the world. On a given topic, there might be a lot of uncertainty and disagreement, but there might be some areas where there is perhaps a surprising amount of consensus, and uncovering and convering that information is useful. And if other similar national reports also come to similar findings, that could be helpful in identifying productive areas where progress can be made.