Hi, I’m Florian. I am enthusiastic about working on large scale problems that require me to learn new skills and extend my knowledge into new fields and subtopics. My main interests are climate change, existential risks, feminism, history, hydrology and food security.
FJehn
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Just out of curiosity, how much time did you spend on modelling and writing this?
I am asking, because you are saying that you probably need 0.75 hours to vote. Let’s say your remaining life expectancy is 40 years. If we have a 4 year election cycle, this means 10 elections. So, in total you would need 7.5 hours in your remaining life to go vote.
And I wondered if convincing yourself to not go vote took more time than to just go vote?
In general I see this post as part of work around civilizational resilience (similar to ALLFED) and in particular this post is part of a blog series which is meant to help us understand societal collapse better: https://existentialcrunch.substack.com/p/introducing-a-living-literature-review
As hinted on in the other comment I made to your separate question, I think it makes more sense to stay in one reasonably good place and try to keep societal structures there intact as much as possible. Staying mobile only makes more sense if everything has broken down and you are just a scavenger. However, you will want to avoid this kind of outcome as much as possible, as everything will be so much harder.
I think the kinds of famine that would happen in the scenarios that I describe would be quite different to the ones of the past when it comes to the scale. If there is just no food locally where you are, it does not really matter how resourceful you are. Also, I think that cooperation is quite important in such events. My own research, as well as the conclusions I took from reading a lot on this is that when cooperation breaks down, things will get much much worse. Therefore, I think the main thing you should be concerned about is not trying to get as many resources as possible, but work on maintaining cooperation. If you fail at that, the overall food security will drop so hard, it just become unlikely that you will be one of the few “lucky” people who still find something.
That’s the big question of contemporary history. I discussed this a bit more here: https://existentialcrunch.substack.com/p/lessons-from-the-past-for-our-global
But in general I think that while our societies have changed a lot, many things have stayed the same. Especially, the food system and its importance for societies is still very similar. Also, if you read a lot of history, you come to realize that humans often tend to follow the same trajectories, in the sense of “history does not repeat, but it rhymes”.
Views like the one from Lenton that I discussed in the post are also independent of the industrial revolution shift and if we could validate them, I think this would make a stronger case for the validity of historical comparisons.
Having such a accuracy in your prediction is still pretty impressive when it comes to history. There is no super clear cut on how you define the start and end of things like “crisis of the middle ages”, so I think the prediction is actually quite good.
Thanks David. I think the paper you are referring to might be the one I cited. At least Herrington also looked at the rate of change as well (Table 2). There you can see that the current trajectory and rate of change is most similar to the CT and the BAU2 scenario. CT being a scenario like you described (we innovated ourselves out of limits to growth), while BAU2 being a scenario where we are still on a collapse trajectory, but the resources of Earth are 2x of the default limits to growth scenario. Therefore, I would argue that we still can’t tell if we just had more resources on Earth than originally estimated or if we solved our problem with innovation. But if you have another paper that discusses this as well, I’d be happy to read it.
Just out of curiosity: Where is the word “schlep” originating from in the context of AI? Don’t think I ever came across it before reading this post.
The food shock resulting from the Russian invasion of Ukraine ultimately turned out comparatively small. ALLFED is looking mainly at food shocks of >10% of global calories. For events below that, especially if they are regional, it is much more cost efficient to trade grain globally. ALLFED’s work is about what we could do if this current mechanism fails. Therefore, Ukaine and the resulting food problems are not really solvable with resilient foods, but more of a political problem.
Though I agree with you that it would be great to test out many of the ALLFED solutions before a catastrophe. However, this would cost magnitudes more money than ALLFED currently has.
Just a thought here. I am not sure if you can literally read this as EA being overwhelmingly left, as it depends a lot on your view point and what you define as “left”. EA exists both in the US and Europe. Policy positions that are seen as left and especially center left in the US would often be more on the center or center right spectrum in Europe.
In my personal experience you always get downvotes/disagree votes for even mentioning any problems with gender balance/representation in EA, no matter what your actual point is.
This is just another data point that the existential risk field (like most EA adjacent communities) has a problem when it comes to gender representation. It fits really well with other evidence we have. See, for example Gideon’s comment under this post here: https://forum.effectivealtruism.org/posts/QA9qefK7CbzBfRczY/the-25-researchers-who-have-published-the-largest-number-of?commentId=vt36xGasCctMecwgi
While on the other hand there seems to be no evidence for your “men just publish more, but worse papers” hypothesis.
Yeah good point. I’ll probably do it differently if I revisit this next year.
Yeah fair enough. I personally, view the Robock et al. papers as the “let’s assume that everything happens according to the absolute worst case” side of things. From this perspective they can be quite helpful in getting an understanding of what might happen. Not in the sense that it is likely, but in the sense of what is even remotely in the cards.
Just a side note. The study you mention as especially rigorous in 1) iii) (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017JD027331) was made in Los Alamos Labs, an organization who job it is to make sure that the US has a large and working stockpile of nuclear weapons. It is financed by the US military and therefore has a very clear inventive to talk down the dangers of nuclear winter. Due to this reason this study has been mentioned as not to be trusted by several well connected people in the nuclear space I talked to.
An explanation of why it makes sense to talk down the risk of nuclear winter, if you want to have a working deterrence is describe here: https://www.jhuapl.edu/sites/default/files/2023-05/NuclearWinter-Strategy-Risk-WEB.pdf
What exactly confused you about the code? It only strips down the names and counts them.
That the publications by someone are under counted makes sense, given how TERRA works, as likely not all publications are captured in the first place and probably not all publications were considered existential risk relevant. When I look at Bostrom’s papers I see several that I would not count as directly x-risk relevant.
Where exactly did you find the number for Torres? On their own website (https://www.xriskology.com/scholarlystuff) they have listed 15 papers and the list only goes to 2020. Since then Torres published several more papers, so this checks out.
I personally did not exclude any papers. I simply used the existing TERRA database. Interestingly, the database only contains one paper by Whittlestone. Seems like the current key words used by TERRA did not catch Whittlestone’s work. So, yes this is an undercount.
Exactly, this only counts the number.
Thanks for the kind words (sometimes feels like those are hard to come by in the forum).
Good point. Changed the title accordingly.
“can’t really draw much in the way of conclusions from this data” seems like a really strong claim to me. I would surely agree that this does not tell you everything there is to know about existential risk research and it especially does not tell you anything about x-risk research outside classic academia (like much of the work by Ajeya).
But it is based on the classifications of a lot of people on what they think is part of the field of existential risk studies and therefore I think gives a good proxy on what people in the field think what is part of their field. Also, this is not meant to tell you that this is the ultimate list, but as stated in the beginning of the post, as a way to give people an overview of what is going on.
Finally, I think that this surely tells you something about the participation of women in the field. 1 out of 25 is really, really unlikely to happen by chance.
I do think that things like voting are dominated in their impact not by direct, but by indirect effects, which cannot really be captured in simple numbers. For example, if I vote I set a good example for my friends, which in turn makes them more likely to vote, which in turn makes their friends more likely to vote. Repeat this enough times and you have more stable democracy. I get that you could also model this in a relatively simple way, but my point is that there are a lot of interacting factors like this.
Making a only numbers based argument in such and similar cases gives the illusion of certainty, while actually you likely have not considered many important factors, which makes the number kinda random and not something that you can base solid decisions on. However, I think having such a number anchors you strongly, which makes it harder to change your opinion in the future, especially if the arguments are non-number based.