Thanks for this Gideon. Having read this and your comments on my climate report, I am still not completely sure what the crux of the disagreement is between us. I get that you disagree with my risk estimates, but I don’t really understand why. Perhaps we could discuss on here, if you were up for it
I obviously think we need more time to flesh out real cruxes but I think our differences are cruxes are probably a few fold:
I think I am considerably less confident than you in the capacity of the research we have done thus far to confidently suggest climate’s contribute to existential risk. To some degree, I think the sort of evidence your happier relying on to make negative claims (ie not a major contributor to existential risk) I am much less happy with doing, as I think they often (and maybe always will) fail to account for plausible major contributors to the complexity of a system. This is both an advantage of the simple approach as Toby lays out earlier, but I’m more skeptical at its usage to make negative rather than positive claims.
I think you are looking for much better thought out pathways to catastrophe than I think is appropriate. I see climate acting as something acting to promote serious instability in a large number of aspects of a complex system, which should give us serious reasons to worry. This probably means my priors on climate are higher than yours immediately, as I’m of the impression you don’t hold this “risk emerges from an inherently interconnected world” ontology. This is why I’ve often put our differences down to our ontology and how we view risk in the real world
Because of my ontology and epistemology, I think I’m happier to put more credence on things like past precedent (collapses trigger by climate change, mass extinctions etc.), and decently formulated theory (planetary boundaries for GCR (although I recognise their real inherent flaws!), the sort of stuff laid out in Avin et al 2018, whats laid out in Beard et al 2021 and Kemp et al 2022). I’m also happier to take on board a broader range of evidence, and look more at things like how risk spreads, vulnerabilities/exposures, feedbacks, responses (and the plausible negatives therin) etc, which I don’t find your report convincing deals with, partially because they are really hard to deal with and partially because, particularly for the heavy tails of warming and other factors, there is a very small amount of research as Kemp et al lays out. Correct me if I’m wrong, but you see the world as a bit more understandable than I do, so simpler, quantitative, more rational models are seen as more important to be able to make any positive epistemic claim, and so you would somewhat reject the sort of analysis that I’m citing.
I’m also exceptionally skeptical of your claim that if direct risks are lower than indirect risks are lower; although I would reject the use of that language full stop
I also think its important to note that I make these claims in (mostly) the context of X-Risk. I think in “normal” scenarios, I would fall much closer to you than to disagreeing with you on a lot of things. But I think I have both a different ontology of existential risk (emerging mostly out of complex systems, so more like whats laid out in Beard et al 2021 and Kemp et al 2022) and perhaps more importantly a more pessimistic epistemology. As (partially) laid out when I discuss Existential Risk, Creativity and Well Adapted Science in the talk, I think that with Existential Risk negative statements (this won’t do this) actually have a higher evidentiary burden than positive statements of a certain flavour (it is plausible that this could happen). Perhaps this is because my priors of existential risk from most things are pretty low (owing I think in part to my pessimistic epistemology) that it just does take much more evidence to cause me to update downwards than to be like “huh, this could be a contributor to risk actually!”
Does this answer our cruxes? I know this doesn’t go into object level aspects of your report, but I think this may do a better job at explaining why we disagree, even when I do think your analysis is top-notch, albeit with a methodology that I disagree with on existential risk.
I also think its important that you know that I’m still not quite sure if I’m using the right language to explain myself here, and that my answer here is why I find your analysis unconvincing, rather than it being wrong. Perhaps as my views evolve I will look back and think differently. Anyway, I really would like to talk to you more about this at some point in the future.
Thanks yes that is helpful. Perhaps we can now get into the substance.
It is noteworthy how different your estimates of the x-risk of climate change are to all other published attempts to quantify the aggregate costs of climate change. All climate-economy models imply not just that climate change won’t cause an existential catastrophe, but that average living standards will be higher in the future despite climate change. When people try to actually quantify and add up the effect on things like agriculture, sea level rise and so on, they don’t get anywhere near to civilisational collapse, but instead get a counterfactual reduction in GDP on the order of 1-5% relative to a world with no climate change (not relative to today).
I don’t think past precedent can take us very far here, since there are no precedents of climate change causing human extinction, though anthropics is obviously an issue here. In the report, I also discuss how in the last 160 million years, climate change has not been associated with elevated rates of species loss. Humans also survive and thrive in very diverse environmental niches at the moment, with an annual average temperature of 10ºC in the UK, but closer to 25ºC in South Asia. Within this annual average, there is also substantial diurnal and seasonal variation. It’s around 5ºC in the UK now but will reach 20ºC in the summer. Humans have survived dramatic climate change over the last 300,000 years, and our hominid ancestors also survived when the world was about 4ºC warmer. It’s hard to see why climate change of 2-4ºC would make such a massive difference, so as to constitute an existential catastrophe
I disagree about planetary boundaries for reasons I discuss in the report. I have examined several of the boundaries in depth and they just seem to be completely made up.
It is not true that there is a small amount of research on the tails of warming. Business as usual is now agreed to be 2.5ºC with something like a 1-5% chance of 4ºC. The impacts literature has in fact been heavily criticised for focusing too much on the impacts of RCP8.5, which implies 5ºC by 2100.
The approach that you advocate for seems to me to establish not just that climate change is a much bigger risk than commonly recognised but also that many other problems are as well. Other problems also have similar or larger effects to climate change when calculated in the usual way used in economic analysis. This includes things like mispricing of water, immigration restrictions, antimicrobial resistance, underinvestment in vaccines, a lot of things that affect the media, the prohibition of GM food, underinvestment in R&D, bad monetary policy, economists focusing on RCTs, housing regulation, the drug war etc. If climate change is a cascading risk on the order of 0.01pp to 1pp, then these problems should be as well. But if they are as well, then total existential risk from non-AI and non-bio sources is way way higher than commonly recognised and doom is almost certain. The reasoning suggests that the world is so fragile that it is unlikely that we could even have got to the current level of technological development.
I would view a lot of my report as assessing cascading risk. I discuss pathways such as climate change ⇒ civil conflict ⇒ political instability ⇒ interstate war. I also discuss effects on migration and the spillover effects this might have. What difference would a cascading risk approach take here? Related to this, I don’t view causal chains like this as very understandable and I say so in the report. But we still have ideas about how big effects some things have. The causes of war between the US and China or Russia and China
I think its important to note that much of the literature looking at those estimates for extreme scenarios (not just extreme levels of warming, but other facets of the extremes as well), has suggested that current techniques for calculating climate damage aren’t great at the extremes, and tend to function well only when close to status quo. So we should expect that these models don’t act appropriately under the conditions we are interested in when exploring GCR/X-Risk. This has pretty commonly been discussed in the literature on these things (Beard et al 2021, Kemp et al 2022, Wagner &Weitzmann 2015, Weaver et al 2010 etc.)
I still think past events can give us useful information. Firstly, climate change has been a contributing factor to A LOT of societal collapses; whilst these aren’t perfect analagies and do show a tremendous capacity of humanity to adapt and survive, they do show the capacity of climate change to contribute to major socio-political-technological crises, which may act as a useful proxy for what we are trying to look for. Moreover, whilst a collapse isn’t an extinction, if we care about existential risk, we might indeed be pretty worried about collapse if it makes certain lock-in more or less likely, but to be honest thats a discussion for another time. Moreover, whilst I think your paleoclimatic argument is somewhat reasonable, given the limited data here (and your reliance on a few data points + a large reliance on a single study of plant diversity (which is fine by the way, we have limited data in general!)), I don’t find it hugely comforting. Particularly because climate change seems to have been a major factor in all of the big 5 mass extinction events, and the trends that Song et al 2021 note in their analysis of temperature change and mass extinction over the Phraneozoic. They mostly use marine animals. When dealing with pass processes, explainations are obviously difficult to disentangle, so there are reasons to be sceptical of the causal explanatory power of Song’s analysis, although obvious such similar uncertainty should be applied to your analysis, particularly with the claims of this fundamental step change 145 million years ago.
Whilst planetary boundaries do have their flaws and to some degree where they are set is quasi-arbitary, as discussed in the talk, something like this may be necessary when acting under such deep uncertainty; don’t walk out into the dark forest and all that. Moreover, I think your report fails to argue convincingly against the BRIHN framework that Baum et al 2014 developed, in part in response to the Nordhaus criticisms which you cite.
Extreme climate change is not just RCP 8.5/ SSP5-8.5, its much broader than that. Kemp et al 2022′s response to Burgess et al’s comment lays out this argument decently well, as does Climate Endgame itself.
I don’t really understand this point, particularly in response to my talk. I explicitly suggest in my talk I think systemic risk, which those could all contribute to, are very important. The call for more complex risk assessment (the core point of the talk alongside a call for pluralism) is that there are likely significant limits to conventional economic analysis in analysing complex risk. The disagreement on this entire point seems to be explained reasonably well by the difference between the simple/complex approach.
I think your causal pathways are too simple and defined (ie they are those 1st and 2nd order indirect impacts), and probably don’t account for the ways in which climate could contribute to cascading risk. Whilst of course this is still under explored, some of the concepts in Beard et al 2021 and Richards et al 2021 are a useful starting place, and I don’t really see how your report refutes the concepts around cascades they bring up. I’d also like to agree these cascades are really hard to understand, but I struggle to see how that fact acts in the favour of your approach and conclusions?
I hope this has helped show some of our disagreements! :-)
I agree that climate-economy models aren’t good at some types of extremes, but I think there are different versions of this argument, some of which have become weaker over the years. One of Weitzman’s points was that there was a decidedly non-negligible chance of more than 6ºC and our economic models weren’t good at capturing how bad this would be and so tended to underestimate climate risk. I think this was basically right at the time he was writing. But since 5ºC now looks less and less likely, this critique has less and less bite. Because there is such a huge literature on the impact of 5ºC, the models now in principle have a much firmer foundation for damage estimates. eg the Takakura 2019 paper that I go on about in the report uses up to date literature on a wide range of impact channels, but still only gets like a 5% counterfactual reduction in welfare-equivalent of GDP by 2100, and so probably higher average living standards than today.
Another version of this is that the models aren’t good at capturing tipping points. I agree with this, but I also find it difficult to see how this would make a dramatic difference to the damage estimates if you actually drill down into the literature on the impact of different tipping points. Tipping points that might cause different levels of warming are not relevant to damage estimates, so the main ones that seem relevant are ice sheet collapse, regional precipitation and temperature changes, such as changes in monsoons, which might be caused eg by collapse of the AMOC. For the impacts discussed in the literature, it is difficult to see how you get anywhere close to an existential catastrophe if any of these things happen.
Aside from that, it is noteworthy that some economic models actually try to capture the literature on the impact of warming of 5ºC on things like agriculture, sea level rise, temperature-related deaths, lost productivity from heat etc. There is a group of scientists who say that 3ºC/4ºC is catastrophic on the basis of what the scientific literature says about these impacts. The models strongly suggest that they are wrong, and it is not clear what their response is.
All this being said, I am sympathetic to some critiques of the economic models, eg a lot of the Nordhaus stuff. When I was writing the report, I had thought about putting no weight on them at all, but after digging a bit I changed my mind. I think some of the models make a decent stab at quantifying aggregate costs.
I agree that climate changes have contributed at least to some civilisational trauma throughout history. The literature on this suggests that climate change has been correlated with local civilisational trauma. But: (a) local collapse is a far cry from global collapse; (b) most of the time this was due to cooling rather than warming; (c) the mechanism was usually damage to agricultural output, but there is now far more slack in the system, and we have massively better technology to deal with any disruption; (d) we in general have far more advanced technology, and whereas in the past >90% of the workforce would have been employed in agriculture, now <20% is (or whatever); (e) the relationship between climate change and civilisational turmoil breaks down by the industrial revolution, which provides some support for point (c).
The paleoclimate point doesn’t rely on one datapoint: it’s data from 160 million years of climatic and evolutionary history. Massive climate change over that period didn’t cause species extinctions, as some might have expect it to have done.
As you say, with climate change, the extinctions usually happened among marine life, due to ocean anoxia and ocean acidification, and it’s hard to see the mechanism by which CO2 pollution would cause land-based extinctions, unless something else weird happens at the time, such as a volcanic eruption puncturing though salt deposits as happened at the Permian.
For the level of warming that now looks likely of 2-4ºC, it’s really hard to see why it would cause similar damage eg to the Permian, given that the effect is an order of magnitude smaller.
I don’t think they are quasi-arbitrary, they are totally arbitrary. eg they propose a planetary boundary for biodiversity intactness which by their own admission is made up. The boundary also can’t be real since various countries across Eurasia completely destroyed their pre-modern ecosystems after the agricultural revolution without causing anything like civilisational collapse.
A lot of people criticise planetary boundaries for being political advocacy. The clearest evidence for this is Steffen et al proposing a supposed planetary boundary for a ‘Hothouse earth’ at 2ºC (which happens to be the Paris target) on the basis of no argument.
When we are acting under uncertainty I think we should use expected value. Alleged boundaries might be a useful schelling point for political negotiation (like the 2ºC threshold), but it’s not a good approach for actually quantifying risk. Another downside of a boundary is that it implies that anything we do once we pass the boundary is pointless.
Kemp, Jehn and others claim that the effect of warming of more than 3ºC is ‘severely neglected’. But all of the impacts literature explores the effect of rcp8.5 by 2100, which implies 4-5ºC of warming. Jehn’s search strategy uses temperature mentions to measure neglect, but if you use RCP mentions, you don’t get the same result.
My argument here was that I think your argument proves too much—it suggests that the world is extremely fragile to eg agricultural disruption and heat waves that happen all the time. Given that the world was eg a lot poorer in 1980 and so had a lot lower adaptive capacity, why didn’t various weather disasters trigger cascading catastrophes back then? The number of people dying in weather-related disasters has declined massively over time, so we should expect the cascade to have happened in the 1920s and less so in the future?
I also don’t see why cascading risk would change the cause ranking among top causes. Why aren’t democratised bioweapons and AI also cascading risks?
What are the causal pathways that might contribute to conflict risk that you think I have missed? I don’t really get what is meant to happen that I haven’t already discussed. I talk about all of the contributors to war outlined in textbooks about war and combine that with the literature on climate impacts. It is just really a stretch to make it an important contributor to US-China dynamics.
In particular, climate economy models still do bad at the heavy tail, not just of warming, but at civilisational vulnerability etc, again presenting a pretty “middle of the road” rather than heavy tailed distribution. The sort of work from Beard et al 2021 for instance highlights something I think the models pretty profoundly miss. Similarly, I’d be really interested in research similar to Mani et al 2021 on extreme weather events and how this may change due to climate change.
I dpon’t see why the models discount the idea that there is a low but non-negligable probability of catastrophic consequences from 3-4 degrees of warming. What aspect of the models? I’m reticent to rely on things like damage functions here, as they don’t seem to engage with the possib;le heavy-tailedness of damage. Whilst I agree that the models probably are decent approximations of reality, I’m just not really very sure they are useful at telling us anything about the low probabil;ity high impact scenarios that we are worried about here.
Whilst I agree there are reasons to think our vulnerability is less, there is clear reasons to think with a growing interconnected (and potentially fragile) global network and economy, our vulnerability is increasing, meaning that whilst the past collapse data might not be prophetic, there is at least value in it; after all, we are in a very evidence poor environment, meaning that I would be reticent to dismiss it as strongly as you seem to. And whilst it is true our agricultural system is more resilient, there is still a possibility of multiple breadbasket failures etc caused by climate change, and the beard et al and richards et al both explore plausible pathways to this. Again, whilst the past collapse data is definitely not a slam dunk in my favour, I would at least argue it is an update nonetheless. I think you might argue the fact that none led to human extinction makes that data an update in yopur direction, and i think your view on this depends on whether you see collapse and GCR and extinction on a continuum or not; I broadly do, and I assume you broadly don’t?
When I said one data point, I meant really one study. The reason I say this, is as cited, studies of different species/ species groups. In your comment, you don’t seem to engage with Song et al 2021. Kaiho at al 2022 also shows a positive relationship between warming and extinction rate. Moreover, I think it takes an overly confident view of our understanding of kill mechanisms, and seems to suggest that just because we don’t have all what you speculate were the important factors that were present in past mass extinctions doesn’t make that not useful evidence. I think a position like Keller et al 2018 (PETM as the best case, KPg as the worst case) is probably useful at looking at this (only using modern evidence!). Once again, this is an attempt by me, in a low evidence situation, to make best use of the evidence available, and I don’t find your points compelling enough to make me not think that this past precident can’t be informative.
On the Planetary Boundaries, you don’t seem to be engaging with what I’m saying here, which is most alluding to the Baum et al paper on this. Moreover, even if you think we are to use EV, what are you basing the probabilities on? I assume some sort of subjective bayesianism, in which case you’ll have to tell me why I should put a decently high (>1%) prior on moving beyond certain Holocene boundaries posing a genuine threat to humanity? That seems perfectly reasonable to me
I’m not really sure I understand the argument? Whilst in some ways the world has indeed got less vulnerable, in other ways it has got more connected, more economically vulnerable to natural disasters etc. Cascading impact seems to be seen more along these lines than along others. Moreover, if you only had a 5% probability of such a cascade occuring over a century, and we have hardly had a hyper-globalised economy for even that long, why would you expect it to have happened already? Your statements here seem pretty out of step with my actual probabilities etc.. And as I talk about in my talk, I also see problems from AI, biorisk and a whole host more. Thats why this talk, and this approach, is seriously not just about climate change; the hope is to add another approach to studying X-Risk.
I’m also pretty interested in your approach to evidence on X-Risk. I should say from the outset that I think climate change is unlikely to cause a catastrophe, but I don’t think you have provided compelling evidence that the probability is exceptionally small. Your evidence often seems to rely on the very things that we think ought to be suspect in X-Risk scenarios (economic models, continued improved resilience, best case scenario analogies etc.), and you seem to reject some things that might be useful for reasoning in such evidence poor environments (plausibly useful but somewhat flawed historical analogies, foresight, storytelling, scenarios etc.) . Basically, you seem to have a pretty high bar for evidence to be worried about climate change, which whilst I in general think is useful, I’m just not sure how appropriate it is in such an evidence poor environment as X-Risk, including climate change contributions to it. Its pretty interesting that you seem very willing to rely on much more speculative evidence for AI and biorisk (eg probabilistic forecasts which don’t have track records of being able to work well over such long time scales), and I genuinely wonder why this is. Note that such more speculative approaches (in this case superforecasters) gave a 1% probability of climate change being a necessary but not sufficent cause of human extinction by 2100, and gave an even higher probability to global catastrophe by 2100, which certainly then has the probability of later leading to extinction. Whilst I myself am somewhat sceptical of such approaches, I’d be interested in seeing why you seem accepting of them for bio and AI but not climate? Is it because you see evaluation of the existential risk from climate change as a much more evidence rich environment than for bio/AI?
I’m not sure they’re middle of the road on civilisational vulnerability. It would be pretty surprising if extreme weather events made a big difference to the overall picture. For the kinds of extreme weather events one sees in the literature, it’s just not a big influence on global GDP. How bad would a hurricane or flood have to be to push things from ‘counterfactual GDP reduction of 5%’ to civilisational collapse.
I don’t think they fully discount/ignore the possibility of catastrophe 3/4ºC. In part this is just an outcome of the models and of the scientific literature. There are no impacts that come close to catastrophe in the scientific literature for 3/4ºC. I agree they miss some tipping points, but looking at the scientific literature on that, it’s hard to see how it would make a big difference to the overall picture.
I haven’t read those papers and don’t have time to do so now unfortunately. My argument there doesn’t rely on one study but on a range of studies in the literature for different warm periods. The Permian was a very extreme and unusual case because it caused such massive land-based extinctions, which was caused by the release of halogens, which is not relevant to future climate change. Also, both the Permian and PETM were extremely hot relative to what we now seem to be in for (17ºC vs 2.5ºC).
I’m not sure I see how I am not engaging with you on planetary boundaries. I thought we were disagreeing about whether to put weight on planetary boundaries, and I was arguing that the boundaries just seem made up. Using EV may have its own problems but that doesn’t make planetary boundaries valid.
I don’t really see how the world now is more vulnerable to any form of weather events in any respect than it has been at any other point in human history. Society routinely absorbs large bad weather events; they don’t even cause local civilisational collapse any more (in middle and high income countries). Deaths from weather disasters have declined dramatically over the last 100 or so years, which is pretty strong evidence that societal resilience is increasing not decreasing. In the pre-industrial period, all countries suffered turmoil and hunger due to cold and droughts. This doesn’t happen any more in countries that are sufficiently wealthy. Many countries now suffer drought, almost entirely due to implicit subsidies for agricultural water consumption. It is very hard to see how this could lead to eg to collapse in California or Spain.
Can you set out an example of a cascading causal process that would lead to a catastrophe?
I’m not sure that there is some meta-level epistemic disagreement, I think we just disagree about what the evidence says about the impacts of climate change. In 2016, I was much more worried than the average FHI person about climate change, but after looking at the impacts literature and recent changes in likely emissions, I updated towards climate change being a relatively minor risk. Comparing to bio for instance, after reading about trends in gene synthesis technologies and costs, it takes about 30 minutes to see how it poses a major global catastrophic risk in the coming decades. I’ve been researching climate change for six years and struggle to see it. I am not being facetious here, this is my honest take.
Thanks for this it is useful. What is your estimate of the existential risk due to climate change? I obviously have it very low, so it would be useful to know where you are at on that. Could you explain what the main drivers of the risk are, from your point of view? Then we can get into the substance a bit more
I suppose the problem with that question from my perspective is I don’t think “existential risk due to X” really exists, as I explain in the talk. The number of percentage points it raises overall risk by, I would put climate change between <0.01% and 2%, and I would probably put overall risk at between 0.01% to 10% or something. But I’m not sure that I actually have much confidence in many approaches to xrisk quantification (as per Beard et al 2020a), even if it does make quantification easier.
Some of the main contributions to risk from climate, but note a number may also be unknown or unidentifiable:
Weakening local, regional and global governance
-Water and food insecurity
-Cascading economic impacts
-Conflict
-Displacement
-Biosphere integrity
-Responses increasing systemic risk
-Extreme Weather
-Latent Risk
Mostly these increase risk by:
-Increasing our vulnerability
-Multiple stressors coalescing into synchronous failure
-The major increase in systemic risk
-The responses we take
-Cascading effects leading to fast or slow collapse then extinction
Sometimes we have already gone in the forest, and we can hear howling, and we have no idea what is going on, and we are posed with a choice of things to do, but no option is safe. We are stuck between a rock and a hard place. Under such deep uncertainty, how can we act if we refuse to reduce the complexity of the world? We can’t just play it safe, because every option fails a precautionary principle. What do we do in such cases?
I recognize that your questions may be rhetorical, but here are some answers:
1. prioritize, by type of harm, the harms to avoid. The classic approach to understanding harm is to rank death as the greatest harm, with disease and other harms less harmful than death. I don’t agree with this but that’s not relevant. Some explicit ranking of harms to avoid clarifies costs associated with different actions.
NOTE: The story of climate change is one of rich countries making most of the anthropogenic GHG’s, damaging ecosystems more, threatening carbon sinks more, etc. Proactive actions can avoid more extreme harms but have known and disliked consequences, particularly for the wealthier of two compromising to save both (for example, societies, countries, or interest groups).
2. recognize the root causes. If you cannot play it safe, then harms will occur no matter what. In that case, recognize root causes of your quandary so that civilization has an opportunity to not repeat the mistake that got you where you are. In the case of climate change, I perceive a root cause shows in the simple equation impacts = population * per capita consumption. You can get fancy with rates or renewable resources or pollution sinks, but basically: consume less or shrink the population.
TIP: The problem reduces to the population size of developed countries offering plentiful public goods while allowing citizens to accumulate private goods. I’ve seen the suggestion to increase public goods and reduce private consumption. Another idea is to offer consistent family planning emphasizing women’s health and economic opportunities as well as free birth control for all, such as free condoms and free vasectomies for men.
3. find the neglected differences between actual, believed, and claimed assertions. As the situation is evolving into an existential crisis, differences appear between public claims, believed information, and the actual truth. During the crisis, the difference between beliefs and the truth gets less attention. Truth-seeking is ignored or assumed complete. You can buck that trend.
EXAMPLE: Right now, the difference to correct could be between claims and beliefs (for example, politicians lying about climate change), but another difference that is more neglected is between truths and beliefs about the lifestyle implications of successfully mitigating climate change. That is where we are now, I believe. People in the developed world are afraid that mitigating climate change for the global population will wreck their modern lifestyle. In many cases, I suspect those fears are overblown.
CAUTION: In a future of real extremes, involving the plausible loss of 100′s of millions of lives, don’t (claim to) expect that obvious solutions like “let 100 million climate migrants into the US over 5 years” will be easily accepted. Instead, expect the gap between claims and beliefs to widen as hidden agendas are acted upon. Climate change issues of rights, fairness, justice, and ethics, not just economics or technology, have been consistently neglected. The endgame looks to be a harmful one.
4. close information gaps wherever you can: Earth science can be confusing. You can follow most of a discussion easily but then lose understanding at some key point because the researcher is being a geek and doesn’t know how to communicate their complicated information well. Sometimes there’s no way to make the presentation any simpler. Sometimes, there isn’t enough information or the information is aged out but not updated fast enough. Policy guidance appears to stick longer than real-time measurements of earth system changes allow. This is a point of frustration and a policy bottleneck that actually comes from the research side. Examples of such issues include:
physical modelling parameters of tipping elements (for example, Greenland melt) are missing from widely cited computer models predicting climate change impacts (for example, sea-level rise). The implications of measurement data wrt those tipping elements goes missing from policy recommendations based on the computer models.
loss of carbon sinks that are tipping elements are not factored into carbon budget calculations at rates reflective of current and short-term expected changes to those sinks. Neither are other forcings on tipping elements (for example, people clearing the Amazon for farming).
smaller scale features relevant to ocean current modeling or weather changes due to climate. These require a model “grid size” of about 1km in contrast to 100x larger grid sizes used for modeling climate. Or thereabouts, according to one discussion I followed. The gist for me that modeling climate change in the ocean or as it affects weather in real-time is not happening effectively yet.
correct interpretation of statistics, units, terminology or research purpose prevents confusion about limits, measurements, and tracking of changes in atmospheric heating, tipping element significance, and the significance of concepts like global average surface temperature (GAST). There are many examples, some of which baffled me, including:
the relationship between gigatons and petagrams
the difference between CO2 and CO2e
amounts referring to carbon (C) vs carbon dioxide (CO2)
the relationship between GAST increases and regional temperature increases
the difference between climate and weather
the rate of warming of the Arctic
the relationship between heating impact and decay rate of CH4 (methane)
the % contribution of land vs ocean carbon sinks to total carbon uptake
the hysteresis effect in tipping element models
the relationship between tipping elements, tipping points, and abrupt climate change.
the precise definition of “famine” and “drought”
the nature of BECCS and DACCS solutions at this point in time
the intended meaning of “carbon budget” versus its commonly understood meaning of “carbon that is safe to produce”
the pragmatic meanings of “energy conservation” or “natural resources” or “carbon pollution”
the relationship between SDGs, SSPs, RCPs, SPAs, CMIP5 and 6 models, and radiative forcing (still confusing me)
Here’s a thought about the use of the word “ontology”. I actually chose that word myself for a criticism I submitted to the Red Team Contest this year. I think no one has read it. However, I suspect that its use by you, someone who gets noticed, could put EA’s off, since it is rarely used outside discussion of knowledge representation or philosophy. That said, I agree with your use of it. However, if you have doubts, other choices of words or phrases with similar meaning to “ontology” include:
model of the world
beliefs about the world
idea of reality
worldview
reality (as you understand it)
In a revision of my criticism (still in process), I introduce a table of alternatives:
EA terminology
probabilism-avoiding alternative
example of use
possible
plausible
it is plausible that the planet will reach 6C GAST by 2100.
impossible
implausible or false
It is false that the planet reached −1C GAST in 2020.
likely or probable
expected … if/assuming …
It is expected that solar power development will add to global energy production, rather than substitute for existing production, assuming business as usual continues.
unlikely
not expected
It is not expected that countries will stay under their carbon budgets between now and 2030.
risk
danger
The existential danger from climate destruction is apparently still controversial.
uncertain
unknown
The danger of human extinction from the proximate cause of climate change is unknown.
uncertainty
ignorance
At the moment, there is some unavoidable ignorance reflected by inferences of changes in weather from changes in climate.
chance that
opportunity for
There is an opportunity for the faith of techno-optimists to be vindicated.
usually
typically
Typically the corrupt politicians and selfish business barons work against the common good.
update
change or constrain
I constrained my beliefs about Greenland resilience against melting after learning that Greenland altitude losses could turn its snow to rain.
**EDIT:**Sorry I cannot get this table to render well
I’m not recommending those changes to your vocabulary, since you are dealing with foresight and forecasting while juggling models from Ord, Halstead, and other EAs. However, if you do intend to “take a break” from thinking probabilistically, consider some of the alternatives I offered here. It can also be helpful to make these changes when your audience needs to discuss scenarios as opposed to forecasts.
I have not spent much time studying geo-engineering, but I have formed the impression that climate scientists look at polar use of water vapor for marine cloud brightening with less fear than the use of aerosols like diamond dust elsewhere in the world. EDIT:Apparently Marine Cloud Brightening is a local effort with much shorter residence time, giving more time for gathering feedback, whereas aerosol dusts are generally longer-term and potentially global.
Also I recall a paint that is such a brilliant white that its reflectivity should match that of clean snow. If the world’s roofs were painted with that paint, could that cool the planet through the albedo effect, or would the cooling effect remain local? I need some clarity on the albedo effect, but I’ll leave the math to you for the moment, and best of success with your efforts!
Hi John, thanks for the comment, I’ve DM’d you about it. I think it may be easier if we did the discussion in person before putting something out on the forum, as there is probably quite a lot to unpack, so let me know if you would be up for this?
Thanks for this Gideon. Having read this and your comments on my climate report, I am still not completely sure what the crux of the disagreement is between us. I get that you disagree with my risk estimates, but I don’t really understand why. Perhaps we could discuss on here, if you were up for it
I obviously think we need more time to flesh out real cruxes but I think our differences are cruxes are probably a few fold:
I think I am considerably less confident than you in the capacity of the research we have done thus far to confidently suggest climate’s contribute to existential risk. To some degree, I think the sort of evidence your happier relying on to make negative claims (ie not a major contributor to existential risk) I am much less happy with doing, as I think they often (and maybe always will) fail to account for plausible major contributors to the complexity of a system. This is both an advantage of the simple approach as Toby lays out earlier, but I’m more skeptical at its usage to make negative rather than positive claims.
I think you are looking for much better thought out pathways to catastrophe than I think is appropriate. I see climate acting as something acting to promote serious instability in a large number of aspects of a complex system, which should give us serious reasons to worry. This probably means my priors on climate are higher than yours immediately, as I’m of the impression you don’t hold this “risk emerges from an inherently interconnected world” ontology. This is why I’ve often put our differences down to our ontology and how we view risk in the real world
Because of my ontology and epistemology, I think I’m happier to put more credence on things like past precedent (collapses trigger by climate change, mass extinctions etc.), and decently formulated theory (planetary boundaries for GCR (although I recognise their real inherent flaws!), the sort of stuff laid out in Avin et al 2018, whats laid out in Beard et al 2021 and Kemp et al 2022). I’m also happier to take on board a broader range of evidence, and look more at things like how risk spreads, vulnerabilities/exposures, feedbacks, responses (and the plausible negatives therin) etc, which I don’t find your report convincing deals with, partially because they are really hard to deal with and partially because, particularly for the heavy tails of warming and other factors, there is a very small amount of research as Kemp et al lays out. Correct me if I’m wrong, but you see the world as a bit more understandable than I do, so simpler, quantitative, more rational models are seen as more important to be able to make any positive epistemic claim, and so you would somewhat reject the sort of analysis that I’m citing.
I’m also exceptionally skeptical of your claim that if direct risks are lower than indirect risks are lower; although I would reject the use of that language full stop
I also think its important to note that I make these claims in (mostly) the context of X-Risk. I think in “normal” scenarios, I would fall much closer to you than to disagreeing with you on a lot of things. But I think I have both a different ontology of existential risk (emerging mostly out of complex systems, so more like whats laid out in Beard et al 2021 and Kemp et al 2022) and perhaps more importantly a more pessimistic epistemology. As (partially) laid out when I discuss Existential Risk, Creativity and Well Adapted Science in the talk, I think that with Existential Risk negative statements (this won’t do this) actually have a higher evidentiary burden than positive statements of a certain flavour (it is plausible that this could happen). Perhaps this is because my priors of existential risk from most things are pretty low (owing I think in part to my pessimistic epistemology) that it just does take much more evidence to cause me to update downwards than to be like “huh, this could be a contributor to risk actually!”
Does this answer our cruxes? I know this doesn’t go into object level aspects of your report, but I think this may do a better job at explaining why we disagree, even when I do think your analysis is top-notch, albeit with a methodology that I disagree with on existential risk.
I also think its important that you know that I’m still not quite sure if I’m using the right language to explain myself here, and that my answer here is why I find your analysis unconvincing, rather than it being wrong. Perhaps as my views evolve I will look back and think differently. Anyway, I really would like to talk to you more about this at some point in the future.
Does this sound right to you?
Thanks yes that is helpful. Perhaps we can now get into the substance.
It is noteworthy how different your estimates of the x-risk of climate change are to all other published attempts to quantify the aggregate costs of climate change. All climate-economy models imply not just that climate change won’t cause an existential catastrophe, but that average living standards will be higher in the future despite climate change. When people try to actually quantify and add up the effect on things like agriculture, sea level rise and so on, they don’t get anywhere near to civilisational collapse, but instead get a counterfactual reduction in GDP on the order of 1-5% relative to a world with no climate change (not relative to today).
I don’t think past precedent can take us very far here, since there are no precedents of climate change causing human extinction, though anthropics is obviously an issue here. In the report, I also discuss how in the last 160 million years, climate change has not been associated with elevated rates of species loss. Humans also survive and thrive in very diverse environmental niches at the moment, with an annual average temperature of 10ºC in the UK, but closer to 25ºC in South Asia. Within this annual average, there is also substantial diurnal and seasonal variation. It’s around 5ºC in the UK now but will reach 20ºC in the summer. Humans have survived dramatic climate change over the last 300,000 years, and our hominid ancestors also survived when the world was about 4ºC warmer. It’s hard to see why climate change of 2-4ºC would make such a massive difference, so as to constitute an existential catastrophe
I disagree about planetary boundaries for reasons I discuss in the report. I have examined several of the boundaries in depth and they just seem to be completely made up.
It is not true that there is a small amount of research on the tails of warming. Business as usual is now agreed to be 2.5ºC with something like a 1-5% chance of 4ºC. The impacts literature has in fact been heavily criticised for focusing too much on the impacts of RCP8.5, which implies 5ºC by 2100.
The approach that you advocate for seems to me to establish not just that climate change is a much bigger risk than commonly recognised but also that many other problems are as well. Other problems also have similar or larger effects to climate change when calculated in the usual way used in economic analysis. This includes things like mispricing of water, immigration restrictions, antimicrobial resistance, underinvestment in vaccines, a lot of things that affect the media, the prohibition of GM food, underinvestment in R&D, bad monetary policy, economists focusing on RCTs, housing regulation, the drug war etc. If climate change is a cascading risk on the order of 0.01pp to 1pp, then these problems should be as well. But if they are as well, then total existential risk from non-AI and non-bio sources is way way higher than commonly recognised and doom is almost certain. The reasoning suggests that the world is so fragile that it is unlikely that we could even have got to the current level of technological development.
I would view a lot of my report as assessing cascading risk. I discuss pathways such as climate change ⇒ civil conflict ⇒ political instability ⇒ interstate war. I also discuss effects on migration and the spillover effects this might have. What difference would a cascading risk approach take here? Related to this, I don’t view causal chains like this as very understandable and I say so in the report. But we still have ideas about how big effects some things have. The causes of war between the US and China or Russia and China
To answer each of your points in turn
I think its important to note that much of the literature looking at those estimates for extreme scenarios (not just extreme levels of warming, but other facets of the extremes as well), has suggested that current techniques for calculating climate damage aren’t great at the extremes, and tend to function well only when close to status quo. So we should expect that these models don’t act appropriately under the conditions we are interested in when exploring GCR/X-Risk. This has pretty commonly been discussed in the literature on these things (Beard et al 2021, Kemp et al 2022, Wagner &Weitzmann 2015, Weaver et al 2010 etc.)
I still think past events can give us useful information. Firstly, climate change has been a contributing factor to A LOT of societal collapses; whilst these aren’t perfect analagies and do show a tremendous capacity of humanity to adapt and survive, they do show the capacity of climate change to contribute to major socio-political-technological crises, which may act as a useful proxy for what we are trying to look for. Moreover, whilst a collapse isn’t an extinction, if we care about existential risk, we might indeed be pretty worried about collapse if it makes certain lock-in more or less likely, but to be honest thats a discussion for another time. Moreover, whilst I think your paleoclimatic argument is somewhat reasonable, given the limited data here (and your reliance on a few data points + a large reliance on a single study of plant diversity (which is fine by the way, we have limited data in general!)), I don’t find it hugely comforting. Particularly because climate change seems to have been a major factor in all of the big 5 mass extinction events, and the trends that Song et al 2021 note in their analysis of temperature change and mass extinction over the Phraneozoic. They mostly use marine animals. When dealing with pass processes, explainations are obviously difficult to disentangle, so there are reasons to be sceptical of the causal explanatory power of Song’s analysis, although obvious such similar uncertainty should be applied to your analysis, particularly with the claims of this fundamental step change 145 million years ago.
Whilst planetary boundaries do have their flaws and to some degree where they are set is quasi-arbitary, as discussed in the talk, something like this may be necessary when acting under such deep uncertainty; don’t walk out into the dark forest and all that. Moreover, I think your report fails to argue convincingly against the BRIHN framework that Baum et al 2014 developed, in part in response to the Nordhaus criticisms which you cite.
Extreme climate change is not just RCP 8.5/ SSP5-8.5, its much broader than that. Kemp et al 2022′s response to Burgess et al’s comment lays out this argument decently well, as does Climate Endgame itself.
I don’t really understand this point, particularly in response to my talk. I explicitly suggest in my talk I think systemic risk, which those could all contribute to, are very important. The call for more complex risk assessment (the core point of the talk alongside a call for pluralism) is that there are likely significant limits to conventional economic analysis in analysing complex risk. The disagreement on this entire point seems to be explained reasonably well by the difference between the simple/complex approach.
I think your causal pathways are too simple and defined (ie they are those 1st and 2nd order indirect impacts), and probably don’t account for the ways in which climate could contribute to cascading risk. Whilst of course this is still under explored, some of the concepts in Beard et al 2021 and Richards et al 2021 are a useful starting place, and I don’t really see how your report refutes the concepts around cascades they bring up. I’d also like to agree these cascades are really hard to understand, but I struggle to see how that fact acts in the favour of your approach and conclusions?
I hope this has helped show some of our disagreements! :-)
I agree that climate-economy models aren’t good at some types of extremes, but I think there are different versions of this argument, some of which have become weaker over the years. One of Weitzman’s points was that there was a decidedly non-negligible chance of more than 6ºC and our economic models weren’t good at capturing how bad this would be and so tended to underestimate climate risk. I think this was basically right at the time he was writing. But since 5ºC now looks less and less likely, this critique has less and less bite. Because there is such a huge literature on the impact of 5ºC, the models now in principle have a much firmer foundation for damage estimates. eg the Takakura 2019 paper that I go on about in the report uses up to date literature on a wide range of impact channels, but still only gets like a 5% counterfactual reduction in welfare-equivalent of GDP by 2100, and so probably higher average living standards than today.
Another version of this is that the models aren’t good at capturing tipping points. I agree with this, but I also find it difficult to see how this would make a dramatic difference to the damage estimates if you actually drill down into the literature on the impact of different tipping points. Tipping points that might cause different levels of warming are not relevant to damage estimates, so the main ones that seem relevant are ice sheet collapse, regional precipitation and temperature changes, such as changes in monsoons, which might be caused eg by collapse of the AMOC. For the impacts discussed in the literature, it is difficult to see how you get anywhere close to an existential catastrophe if any of these things happen.
Aside from that, it is noteworthy that some economic models actually try to capture the literature on the impact of warming of 5ºC on things like agriculture, sea level rise, temperature-related deaths, lost productivity from heat etc. There is a group of scientists who say that 3ºC/4ºC is catastrophic on the basis of what the scientific literature says about these impacts. The models strongly suggest that they are wrong, and it is not clear what their response is.
All this being said, I am sympathetic to some critiques of the economic models, eg a lot of the Nordhaus stuff. When I was writing the report, I had thought about putting no weight on them at all, but after digging a bit I changed my mind. I think some of the models make a decent stab at quantifying aggregate costs.
I agree that climate changes have contributed at least to some civilisational trauma throughout history. The literature on this suggests that climate change has been correlated with local civilisational trauma. But: (a) local collapse is a far cry from global collapse; (b) most of the time this was due to cooling rather than warming; (c) the mechanism was usually damage to agricultural output, but there is now far more slack in the system, and we have massively better technology to deal with any disruption; (d) we in general have far more advanced technology, and whereas in the past >90% of the workforce would have been employed in agriculture, now <20% is (or whatever); (e) the relationship between climate change and civilisational turmoil breaks down by the industrial revolution, which provides some support for point (c).
The paleoclimate point doesn’t rely on one datapoint: it’s data from 160 million years of climatic and evolutionary history. Massive climate change over that period didn’t cause species extinctions, as some might have expect it to have done.
As you say, with climate change, the extinctions usually happened among marine life, due to ocean anoxia and ocean acidification, and it’s hard to see the mechanism by which CO2 pollution would cause land-based extinctions, unless something else weird happens at the time, such as a volcanic eruption puncturing though salt deposits as happened at the Permian.
For the level of warming that now looks likely of 2-4ºC, it’s really hard to see why it would cause similar damage eg to the Permian, given that the effect is an order of magnitude smaller.
I don’t think they are quasi-arbitrary, they are totally arbitrary. eg they propose a planetary boundary for biodiversity intactness which by their own admission is made up. The boundary also can’t be real since various countries across Eurasia completely destroyed their pre-modern ecosystems after the agricultural revolution without causing anything like civilisational collapse.
A lot of people criticise planetary boundaries for being political advocacy. The clearest evidence for this is Steffen et al proposing a supposed planetary boundary for a ‘Hothouse earth’ at 2ºC (which happens to be the Paris target) on the basis of no argument.
When we are acting under uncertainty I think we should use expected value. Alleged boundaries might be a useful schelling point for political negotiation (like the 2ºC threshold), but it’s not a good approach for actually quantifying risk. Another downside of a boundary is that it implies that anything we do once we pass the boundary is pointless.
Kemp, Jehn and others claim that the effect of warming of more than 3ºC is ‘severely neglected’. But all of the impacts literature explores the effect of rcp8.5 by 2100, which implies 4-5ºC of warming. Jehn’s search strategy uses temperature mentions to measure neglect, but if you use RCP mentions, you don’t get the same result.
My argument here was that I think your argument proves too much—it suggests that the world is extremely fragile to eg agricultural disruption and heat waves that happen all the time. Given that the world was eg a lot poorer in 1980 and so had a lot lower adaptive capacity, why didn’t various weather disasters trigger cascading catastrophes back then? The number of people dying in weather-related disasters has declined massively over time, so we should expect the cascade to have happened in the 1920s and less so in the future?
I also don’t see why cascading risk would change the cause ranking among top causes. Why aren’t democratised bioweapons and AI also cascading risks?
What are the causal pathways that might contribute to conflict risk that you think I have missed? I don’t really get what is meant to happen that I haven’t already discussed. I talk about all of the contributors to war outlined in textbooks about war and combine that with the literature on climate impacts. It is just really a stretch to make it an important contributor to US-China dynamics.
Hi John, sorry this has taken a while.
In particular, climate economy models still do bad at the heavy tail, not just of warming, but at civilisational vulnerability etc, again presenting a pretty “middle of the road” rather than heavy tailed distribution. The sort of work from Beard et al 2021 for instance highlights something I think the models pretty profoundly miss. Similarly, I’d be really interested in research similar to Mani et al 2021 on extreme weather events and how this may change due to climate change.
I dpon’t see why the models discount the idea that there is a low but non-negligable probability of catastrophic consequences from 3-4 degrees of warming. What aspect of the models? I’m reticent to rely on things like damage functions here, as they don’t seem to engage with the possib;le heavy-tailedness of damage. Whilst I agree that the models probably are decent approximations of reality, I’m just not really very sure they are useful at telling us anything about the low probabil;ity high impact scenarios that we are worried about here.
Whilst I agree there are reasons to think our vulnerability is less, there is clear reasons to think with a growing interconnected (and potentially fragile) global network and economy, our vulnerability is increasing, meaning that whilst the past collapse data might not be prophetic, there is at least value in it; after all, we are in a very evidence poor environment, meaning that I would be reticent to dismiss it as strongly as you seem to. And whilst it is true our agricultural system is more resilient, there is still a possibility of multiple breadbasket failures etc caused by climate change, and the beard et al and richards et al both explore plausible pathways to this. Again, whilst the past collapse data is definitely not a slam dunk in my favour, I would at least argue it is an update nonetheless. I think you might argue the fact that none led to human extinction makes that data an update in yopur direction, and i think your view on this depends on whether you see collapse and GCR and extinction on a continuum or not; I broadly do, and I assume you broadly don’t?
When I said one data point, I meant really one study. The reason I say this, is as cited, studies of different species/ species groups. In your comment, you don’t seem to engage with Song et al 2021. Kaiho at al 2022 also shows a positive relationship between warming and extinction rate. Moreover, I think it takes an overly confident view of our understanding of kill mechanisms, and seems to suggest that just because we don’t have all what you speculate were the important factors that were present in past mass extinctions doesn’t make that not useful evidence. I think a position like Keller et al 2018 (PETM as the best case, KPg as the worst case) is probably useful at looking at this (only using modern evidence!). Once again, this is an attempt by me, in a low evidence situation, to make best use of the evidence available, and I don’t find your points compelling enough to make me not think that this past precident can’t be informative.
On the Planetary Boundaries, you don’t seem to be engaging with what I’m saying here, which is most alluding to the Baum et al paper on this. Moreover, even if you think we are to use EV, what are you basing the probabilities on? I assume some sort of subjective bayesianism, in which case you’ll have to tell me why I should put a decently high (>1%) prior on moving beyond certain Holocene boundaries posing a genuine threat to humanity? That seems perfectly reasonable to me
I’m not really sure I understand the argument? Whilst in some ways the world has indeed got less vulnerable, in other ways it has got more connected, more economically vulnerable to natural disasters etc. Cascading impact seems to be seen more along these lines than along others. Moreover, if you only had a 5% probability of such a cascade occuring over a century, and we have hardly had a hyper-globalised economy for even that long, why would you expect it to have happened already? Your statements here seem pretty out of step with my actual probabilities etc.. And as I talk about in my talk, I also see problems from AI, biorisk and a whole host more. Thats why this talk, and this approach, is seriously not just about climate change; the hope is to add another approach to studying X-Risk.
I’m also pretty interested in your approach to evidence on X-Risk. I should say from the outset that I think climate change is unlikely to cause a catastrophe, but I don’t think you have provided compelling evidence that the probability is exceptionally small. Your evidence often seems to rely on the very things that we think ought to be suspect in X-Risk scenarios (economic models, continued improved resilience, best case scenario analogies etc.), and you seem to reject some things that might be useful for reasoning in such evidence poor environments (plausibly useful but somewhat flawed historical analogies, foresight, storytelling, scenarios etc.) . Basically, you seem to have a pretty high bar for evidence to be worried about climate change, which whilst I in general think is useful, I’m just not sure how appropriate it is in such an evidence poor environment as X-Risk, including climate change contributions to it. Its pretty interesting that you seem very willing to rely on much more speculative evidence for AI and biorisk (eg probabilistic forecasts which don’t have track records of being able to work well over such long time scales), and I genuinely wonder why this is. Note that such more speculative approaches (in this case superforecasters) gave a 1% probability of climate change being a necessary but not sufficent cause of human extinction by 2100, and gave an even higher probability to global catastrophe by 2100, which certainly then has the probability of later leading to extinction. Whilst I myself am somewhat sceptical of such approaches, I’d be interested in seeing why you seem accepting of them for bio and AI but not climate? Is it because you see evaluation of the existential risk from climate change as a much more evidence rich environment than for bio/AI?
I’m not sure they’re middle of the road on civilisational vulnerability. It would be pretty surprising if extreme weather events made a big difference to the overall picture. For the kinds of extreme weather events one sees in the literature, it’s just not a big influence on global GDP. How bad would a hurricane or flood have to be to push things from ‘counterfactual GDP reduction of 5%’ to civilisational collapse.
I don’t think they fully discount/ignore the possibility of catastrophe 3/4ºC. In part this is just an outcome of the models and of the scientific literature. There are no impacts that come close to catastrophe in the scientific literature for 3/4ºC. I agree they miss some tipping points, but looking at the scientific literature on that, it’s hard to see how it would make a big difference to the overall picture.
I haven’t read those papers and don’t have time to do so now unfortunately. My argument there doesn’t rely on one study but on a range of studies in the literature for different warm periods. The Permian was a very extreme and unusual case because it caused such massive land-based extinctions, which was caused by the release of halogens, which is not relevant to future climate change. Also, both the Permian and PETM were extremely hot relative to what we now seem to be in for (17ºC vs 2.5ºC).
I’m not sure I see how I am not engaging with you on planetary boundaries. I thought we were disagreeing about whether to put weight on planetary boundaries, and I was arguing that the boundaries just seem made up. Using EV may have its own problems but that doesn’t make planetary boundaries valid.
I don’t really see how the world now is more vulnerable to any form of weather events in any respect than it has been at any other point in human history. Society routinely absorbs large bad weather events; they don’t even cause local civilisational collapse any more (in middle and high income countries). Deaths from weather disasters have declined dramatically over the last 100 or so years, which is pretty strong evidence that societal resilience is increasing not decreasing. In the pre-industrial period, all countries suffered turmoil and hunger due to cold and droughts. This doesn’t happen any more in countries that are sufficiently wealthy. Many countries now suffer drought, almost entirely due to implicit subsidies for agricultural water consumption. It is very hard to see how this could lead to eg to collapse in California or Spain.
Can you set out an example of a cascading causal process that would lead to a catastrophe?
I’m not sure that there is some meta-level epistemic disagreement, I think we just disagree about what the evidence says about the impacts of climate change. In 2016, I was much more worried than the average FHI person about climate change, but after looking at the impacts literature and recent changes in likely emissions, I updated towards climate change being a relatively minor risk. Comparing to bio for instance, after reading about trends in gene synthesis technologies and costs, it takes about 30 minutes to see how it poses a major global catastrophic risk in the coming decades. I’ve been researching climate change for six years and struggle to see it. I am not being facetious here, this is my honest take.
Thanks for this it is useful. What is your estimate of the existential risk due to climate change? I obviously have it very low, so it would be useful to know where you are at on that. Could you explain what the main drivers of the risk are, from your point of view? Then we can get into the substance a bit more
I suppose the problem with that question from my perspective is I don’t think “existential risk due to X” really exists, as I explain in the talk. The number of percentage points it raises overall risk by, I would put climate change between <0.01% and 2%, and I would probably put overall risk at between 0.01% to 10% or something. But I’m not sure that I actually have much confidence in many approaches to xrisk quantification (as per Beard et al 2020a), even if it does make quantification easier. Some of the main contributions to risk from climate, but note a number may also be unknown or unidentifiable:
Weakening local, regional and global governance -Water and food insecurity -Cascading economic impacts -Conflict -Displacement -Biosphere integrity -Responses increasing systemic risk -Extreme Weather -Latent Risk
Mostly these increase risk by: -Increasing our vulnerability -Multiple stressors coalescing into synchronous failure -The major increase in systemic risk -The responses we take -Cascading effects leading to fast or slow collapse then extinction
Acting as a “risk factor”
Hi Gideon,
I recognize that your questions may be rhetorical, but here are some answers:
1. prioritize, by type of harm, the harms to avoid. The classic approach to understanding harm is to rank death as the greatest harm, with disease and other harms less harmful than death. I don’t agree with this but that’s not relevant. Some explicit ranking of harms to avoid clarifies costs associated with different actions.
NOTE: The story of climate change is one of rich countries making most of the anthropogenic GHG’s, damaging ecosystems more, threatening carbon sinks more, etc. Proactive actions can avoid more extreme harms but have known and disliked consequences, particularly for the wealthier of two compromising to save both (for example, societies, countries, or interest groups).
2. recognize the root causes. If you cannot play it safe, then harms will occur no matter what. In that case, recognize root causes of your quandary so that civilization has an opportunity to not repeat the mistake that got you where you are. In the case of climate change, I perceive a root cause shows in the simple equation impacts = population * per capita consumption. You can get fancy with rates or renewable resources or pollution sinks, but basically: consume less or shrink the population.
TIP: The problem reduces to the population size of developed countries offering plentiful public goods while allowing citizens to accumulate private goods. I’ve seen the suggestion to increase public goods and reduce private consumption. Another idea is to offer consistent family planning emphasizing women’s health and economic opportunities as well as free birth control for all, such as free condoms and free vasectomies for men.
3. find the neglected differences between actual, believed, and claimed assertions. As the situation is evolving into an existential crisis, differences appear between public claims, believed information, and the actual truth. During the crisis, the difference between beliefs and the truth gets less attention. Truth-seeking is ignored or assumed complete. You can buck that trend.
EXAMPLE: Right now, the difference to correct could be between claims and beliefs (for example, politicians lying about climate change), but another difference that is more neglected is between truths and beliefs about the lifestyle implications of successfully mitigating climate change. That is where we are now, I believe. People in the developed world are afraid that mitigating climate change for the global population will wreck their modern lifestyle. In many cases, I suspect those fears are overblown.
CAUTION: In a future of real extremes, involving the plausible loss of 100′s of millions of lives, don’t (claim to) expect that obvious solutions like “let 100 million climate migrants into the US over 5 years” will be easily accepted. Instead, expect the gap between claims and beliefs to widen as hidden agendas are acted upon. Climate change issues of rights, fairness, justice, and ethics, not just economics or technology, have been consistently neglected. The endgame looks to be a harmful one.
4. close information gaps wherever you can: Earth science can be confusing. You can follow most of a discussion easily but then lose understanding at some key point because the researcher is being a geek and doesn’t know how to communicate their complicated information well. Sometimes there’s no way to make the presentation any simpler. Sometimes, there isn’t enough information or the information is aged out but not updated fast enough. Policy guidance appears to stick longer than real-time measurements of earth system changes allow. This is a point of frustration and a policy bottleneck that actually comes from the research side. Examples of such issues include:
physical modelling parameters of tipping elements (for example, Greenland melt) are missing from widely cited computer models predicting climate change impacts (for example, sea-level rise). The implications of measurement data wrt those tipping elements goes missing from policy recommendations based on the computer models.
loss of carbon sinks that are tipping elements are not factored into carbon budget calculations at rates reflective of current and short-term expected changes to those sinks. Neither are other forcings on tipping elements (for example, people clearing the Amazon for farming).
smaller scale features relevant to ocean current modeling or weather changes due to climate. These require a model “grid size” of about 1km in contrast to 100x larger grid sizes used for modeling climate. Or thereabouts, according to one discussion I followed. The gist for me that modeling climate change in the ocean or as it affects weather in real-time is not happening effectively yet.
correct interpretation of statistics, units, terminology or research purpose prevents confusion about limits, measurements, and tracking of changes in atmospheric heating, tipping element significance, and the significance of concepts like global average surface temperature (GAST). There are many examples, some of which baffled me, including:
the relationship between gigatons and petagrams
the difference between CO2 and CO2e
amounts referring to carbon (C) vs carbon dioxide (CO2)
the relationship between GAST increases and regional temperature increases
the difference between climate and weather
the rate of warming of the Arctic
the relationship between heating impact and decay rate of CH4 (methane)
the % contribution of land vs ocean carbon sinks to total carbon uptake
the hysteresis effect in tipping element models
the relationship between tipping elements, tipping points, and abrupt climate change.
the precise definition of “famine” and “drought”
the nature of BECCS and DACCS solutions at this point in time
the intended meaning of “carbon budget” versus its commonly understood meaning of “carbon that is safe to produce”
the pragmatic meanings of “energy conservation” or “natural resources” or “carbon pollution”
the relationship between SDGs, SSPs, RCPs, SPAs, CMIP5 and 6 models, and radiative forcing (still confusing me)
Here’s a thought about the use of the word “ontology”. I actually chose that word myself for a criticism I submitted to the Red Team Contest this year. I think no one has read it. However, I suspect that its use by you, someone who gets noticed, could put EA’s off, since it is rarely used outside discussion of knowledge representation or philosophy. That said, I agree with your use of it. However, if you have doubts, other choices of words or phrases with similar meaning to “ontology” include:
model of the world
beliefs about the world
idea of reality
worldview
reality (as you understand it)
In a revision of my criticism (still in process), I introduce a table of alternatives:
**EDIT:**Sorry I cannot get this table to render well
I’m not recommending those changes to your vocabulary, since you are dealing with foresight and forecasting while juggling models from Ord, Halstead, and other EAs. However, if you do intend to “take a break” from thinking probabilistically, consider some of the alternatives I offered here. It can also be helpful to make these changes when your audience needs to discuss scenarios as opposed to forecasts.
I have not spent much time studying geo-engineering, but I have formed the impression that climate scientists look at polar use of water vapor for marine cloud brightening with less fear than the use of aerosols like diamond dust elsewhere in the world. EDIT:Apparently Marine Cloud Brightening is a local effort with much shorter residence time, giving more time for gathering feedback, whereas aerosol dusts are generally longer-term and potentially global.
Also I recall a paint that is such a brilliant white that its reflectivity should match that of clean snow. If the world’s roofs were painted with that paint, could that cool the planet through the albedo effect, or would the cooling effect remain local? I need some clarity on the albedo effect, but I’ll leave the math to you for the moment, and best of success with your efforts!
Hi John, thanks for the comment, I’ve DM’d you about it. I think it may be easier if we did the discussion in person before putting something out on the forum, as there is probably quite a lot to unpack, so let me know if you would be up for this?