Do you want a first-principled preparedness guide to prepare yourself and loved ones for potential catastrophes?

Many of us have heard how we should prepare for potential disasters. But is such advice outdated given increasing threats from both AI and biotechnology? This post is both a test for people’s appetite for an up-to-date, first principled rationalist preparedness guide as well as a call for collaborators to create such a guide (even just reading and commenting on draft versions of the guide would be helpful).

In the rest of this post, I attempt to outline my preliminary thoughts around the contents of such a guide and the analysis I foresee needing to be done. I hope this is sufficient for people to let me know if this guide is something they are likely to find useful. I also hope readers can help improve this guide right from the outset:

  • What sections/​topics are missing from the guide?

  • Is there better/​additional analysis that is likely to improve the guide?

  • Is anything proposed in this post wrong or irrelevant?

  • Is the guide likely to be useful at all?

  • Any other comments that are likely to help people be better prepared for the most likely catastrophes that could harm them

I am structuring this post the way I currently and preliminarily envision structuring the actual guide. Therefore, each section below roughly corresponds to each chapter/​heading/​section in the final preparedness guide, as well as their ordering. Moreover, the sections below contain a mix of the content I foresee in these chapters, and what analysis needs to be performed.

It should be noted that an outcome of the process of creating an updated, rationalist preparedness guide might be that it is realized that current preparedness advice is sufficient even for threats posed by emerging technologies like AI and biotechnology. Or it might be decided that the uncertainty around these new risks is so high that it is hard to anticipate how to prepare.

Moreover, as I was writing this post, I realized that some sections below might in fact already be the draft text of the final guide. For example, for the purpose of this post I am making a case for why an updated preparedness guide is needed—I think that text would be helpful to include in the final guide as well.

I should also let readers know that I am unsure about how much time I will have to dedicate to this effort. I am therefore especially interested in collaborators that can help me by completing one or more sections, or take a coordinating role in assembling this guide. It could take a couple of years before the guide is done. However, I also foresee this to become a living document as we learn more about emerging technologies going forward.

Epistemic status: This post is written very much from the hip and I am not too certain about any numbers or comparisons made herein. In fact, a reason for posting is to get input that strengthens the arguments so that the final preparedness guide is as useful and reliable as possible. That said, I have spent quite a lot of time lately on pondering how to best prepare for especially catastrophes due to engineered pathogens.

When a rough draft is done, I envision to post that here on LessWrong in order to get input for the final version.

With that introduction/​context out of the way, here are the sections I envision the guide to contain:

Risks from emerging technologies might pose the greatest risk to your life

Preparedness advice does not seem to have changed much over the last few decades despite the emergence of technologies with the potential for catastrophic harm on a global scale. Two of perhaps the most concerning technological developments are Artificial Intelligence and the rapidly falling cost of biotechnology. While we are still only learning about these threats, estimates of the catastrophe they could cause are concerning and preliminary analysis shows that they might be the most likely ways some of us could die.

I anticipate that the guide would include some rough threshold numbers for readers to make up their own mind whether preparing is worth it or not. For example, this section could include something like:

“If you believe there is a 25% of a catastrophe this century, and you believe 15% of such scenarios stem from pandemic risks, you might seriously want to consider preparing as this translates into a roughly 0.009% chance of dying each year. For comparison, the annual chance of dying in a hurricane if you live in Louisiana (arguably one of the high-income locations most at-risk from hurricane deaths) is at most about 0.006%, and probably much lower. It might therefore be more rational to prepare for an extreme pandemic than for a hurricane, especially if you put higher chances of such an event happening and/​or if you are already preparing but live in an area less likely to be struck by disaster then Louisiana.”

Current preparedness advice likely not addressing emerging risks + emerging risks might be more effective to protect against

This section is building on the previous section, making the case that current preparedness advice is insufficient and also that there might be ways you can more cost effectively buy down risk from emerging risks than from traditional risks. In this section, one might want to show what preparedness for emerging risks looks like.

On the first point of this section, having face masks and a bicycle might be examples of advice lacking in most current guides. Pandemic risks, for example, might involve having a cache of face masks, something few existing preparedness guides seem to advocate for. Another, at this point purely speculative and likely totally misguided preparedness action is mobility in case of AI scenarios where we become to AI kind of what owls are to us—mostly unimportant and ignored in the destruction of their habitat and food sources. Thus, if we were to e.g. live in an area for a planned uranium mine for AI, we might want to be able to move quickly and over significant distances. This might be as simple as having a bicycle with bags to carry a tent, fishing equipment, etc. Please do not worry too much about this example, I just made it up on the spot with little expertise—I included it only to show that regular prepping advice is with some chance inappropriate for bad AI scenarios)

The second point of this section, on making the case for cost effectiveness, consists of 2 parts:

  1. The cost of different preparedness investments. Here one example in traditional preparedness advice could be that of a bunker. These are costly, and might not offer much protection.

  2. The second part is about likely reduction in risk. For example, going back to the hurricane example, it might well be that traditional preparedness advice is not that helpful in disasters. For example, stockpiling food and warm blankets did not do much for the victims of Hurricane Katrina where drowning and injuries were the main causes of death. A bunker likely does not buy down risk much—there is very little risk from dying even in a civil war, looking at civilian death rates during e.g. the American Civil War (for the final version of the guide we should probably also look at civilian casualties from more recent conflicts such as Ukraine and Syria). An independent electricity supply might also not offer much protection, especially compared to an independent and purified water supply (especially in case of pandemics or other toxic releases/​fallout scenarios).

After going through a couple of illustrative examples of cost effectiveness of different preparedness solutions, the hope is that this section of the guide has convinced the reader to read on to learn about the top advice for preparedness.

This section might also include some analysis on how well current preparedness advice has worked out. There are 3 potential approaches that can be investigated:

  • What has worked for people who have successfully escaped disaster? For example, one of the most popular strategies from people affected by conflict and/​or economic collapse is to be mobile, such as refugees from Syria. However, few preparedness guides emphasize mobility, especially preparedness advice from governments. It is also worth noting that current strategies of mobility involve mobility over large distances and across often multiple national borders. A backpack is therefore likely to be insufficient.

  • What might have kept people who have died in catastrophes from dying? Disease kills millions each year—it seems protection from diseases is useful, especially in epidemic/​pandemic hotspots.

  • What types of recommended preparedness are unlikely to have much impact? For example, how many people dying in catastrophes could have been saved by keeping the recommended 72 hours worth of food supply? Probably few, if none. In cases where food is a problem, it only becomes acute after a week or two and famines can last for years meaning the best preparations for catastrophes that involve food shortages would be multi-year food storage (and/​or production), something that is not widely recommended (I have heard Mormons do food storage for around 1 year). I am not indicating that one should not do 72 hours’ worth of supplies. Instead, it might be that analysis shows one should not derive too much comfort from such a short supply and that it might be cost-effective to have much larger caches of food. Moreover, this speculative example also might highlight the shortcoming of using the number of deaths to underpin the analysis—it would ignore hardship from non-fatal events such as lacking food for ~5 days.

List of preparedness activities ranked by cost effectiveness

The idea here is to quite early on in the guide give people the conclusion. Here they can look at their budget and focus their money on the preparedness investments that most cost effectively reduces risk.

Shortcomings of the guide

This section seems useful to include before launching into analysis that leads to the preceding recommendations. This is because all the analysis suffers from some shortcomings that apply to most if not all calculations and investigations:

  • Prioritizing risk categories suffer from a lack of track record of anyone for being able to look >5 years into the future. This might to some degree be alleviated by looking for relevant catastrophe-related forecasts that are ~5 years in the future and see what risk picture emerges from these as Metaculus has a track record of up to ~5 years.

  • Using experiences from the past to predict the future. For example, that having a food supply for 72 hours has been inadequate in preventing death (but not hardship!) in most catastrophes and disasters to date might not mean it is unhelpful in the future.

  • Using likelihood of death as a metric for preparedness. In general, people are trying to avoid suffering, and not necessarily death. It could even be argued that death is inevitable. While this might be an important philosophical conversation to have, it is beyond the scope of this guide. Moreover, number of deaths is a metric that is widely used and there is agreement about its definition and measurement. Ideally, we would have based this whole report on risks of suffering, which might have included societal events that caused a drastic increase in e.g. rates of depression. However, risk assessments in terms of suffering or well-being do not seem available and even risk estimates based on deaths are hard to come by, hence we settle for a risk assessment based on the number of deaths. Moreover, there are probably correlations between the number of deaths and other things we might care about such as the safety and well being of our loved ones, our likelihood of mental illness, suffering from injuries, etc. That said, deaths are not perfect. One example is looking at war affected areas like Ukraine and Syria. While there is a significant risk to people’s lives from staying in these places, it also seems that the sheer discomfort of living in war affected areas is sufficient to cause people to take drastic actions such as migrating to another country.

  • Probably other, significant shortcomings I have not yet considered.

Our best understanding of the future risk landscape

Perhaps surprisingly, there is not a lot of trusted information about what risks might be most important to hedge against in the coming decades. This can be especially frustrating when there are so many preparedness guides from governmental as well as private sources—how can they so confidently tell us how to prepare when they do not know well what scenarios are most likely to unfold? This section therefore intends to go through what is known about future risks and discuss the extent to which we might trust various sources. Here is a quick overview of sources I have found so far:

  1. Metaculus, Good Judgement, Manifold Markets and other forecasting platforms with some amount of track record.

  2. US-based FEMA might have information. However my very preliminary understanding is that these are not quantified and hence it is hard to compare their identified risks with those identified by others.

  3. The CDC in the US, the ECDC in the EU and other governments’ disease control agencies might or might not have quantified the risks from different pathogens, categories of pathogens or pandemics/​epidemics of different magnitudes.

  4. The Global Catastrophic Risk Institute might or might not have quantified risks from different sources.

  5. The World Economic Forum (WEF) annually publishes a risk report. It is to some degree quantified (arbitrary scales, no probabilities unfortunately) and intends to cover all possible risks to humanity.

  6. Perhaps the XPT outputs could be considered an alternative source of at least certain categories of risk?

  7. Michael Aird has produced this very helpful overview of different risk estimates of extinction from various sources, as well as some estimates of “extinction approaching” events. There might be other relevant sources of the overall risk landscape herein.

  8. Toby Ord in his 2020 publication The Precipice has included extinction probabilities from all possible sources.

  9. A 2008 conference polled participants on probabilities of various catastrophes and extinction scenarios.

  10. The UK Cabinet Office’s National Risk Register

  11. Others I have not yet come across?

I have only preliminarily looked into Metaculus and the WEF reports. Metaculus and some other sources put probabilities on their questions and hence it is easier to get an understanding of the relative risk and also make what are probably some very rough estimates of the likelihood of death to a person.

The WEF risk reports, at first glance, look underwhelming both in terms of the extent to which risks are quantified as well as some quick checks on their track record. For example, their 2006 report (just before the 2008 financial crisis) scored “market crash hits several hedge funds” at a likelihood of 1 out of 4 (4 being most likely). Moreover, their 2019 report (just ahead of COVID) put “spread of infectious diseases” at 3 out of 5 in likelihood, with only 5 risks ranked lower but with >20 other risks ranked as more likely such as “profound social instability”. While it is hard to say whether they did well or not as their estimates are notoriously impossible to quantify, a source such as Metaculus has had a prediction of “major naturally-originated pandemic by 2026” running since ~2016 putting a 36% chance of this before the COVID pandemic and with an easily quantifiable definition of what “major” means.

The suggestion is therefore for this guide to lean more heavily on sources that both quantify their risks but that also have some track record. This would put less weight on e.g. Toby Ord’s estimates as he has no forecasting track record that is easily available publicly. Instead, the guide will likely lean most heavily on:

  • Metaculus

  • Good Judgment

  • XPT

However, other risk assessments will not be completely disregarded. Instead they will be used for 2 purposes:

  1. Sanity check and compare conclusions of the guide based on the above 3 sources. For example, if all other sources highlight climate change as extremely important while the above 3 hardly assigns any probability to this at all, it might be worth including preparedness advice that hedges against this discrepancy by at least recommending minor, high-return investments in preparedness for climate change.

  2. Give readers a sense of what might be the uncertainty of the likelihood of different scenarios. For example, if the likelihood of climate change differs markedly between WEF and Metaculus, one might want to instead prepare for scenarios where most predictions agree (if any!).

Scoring methodology

This section would explain the method used to arrive at the scores for the different preparedness interventions. Ideally, there would even be a link to a spreadsheet so that readers can go in and input their own assumptions and preferences in order to get their customized list of most cost effective preparedness investments.

Preliminarily, it is suggested that each intervention is evaluated under each risk scenario and that for each of these, an estimated reduction in risk is assigned. For example, having either a bicycle with bags or a sailboat might reduce risk under a range of scenarios from conflict/​unrest all the way to certain AI scenarios. As such, the risk reduction in each category might not be the largest, but the sum across categories could make sure preparedness investments amongst the most highly ranked, especially something like a bicycle with bags that are relatively inexpensive and is often anyways part of a household’s inventory. This is just a speculative example, but meant to highlight the ranking methodology.

Another example to consider might be an emergency plan for the family, especially with a list of prioritized meet-up locations contact details. Perhaps the best scoring function would not be to only consider the loss of one’s own life, but of one’s loved ones. For example, many parents would trade their own lives for those of their children’s and as such a proper risk estimate should perhaps include both the risk to one’s own life as well as the risk to that of one’s children.

Is is noted that there are 3 ways for interventions to score highly:

  • Low or moderate reduction in risk at moderate to high price for most likely scenarios

  • Large risk reduction at low prices for less likely scenarios

  • Low to moderate risk reduction at moderate prices but that applies to multiple scenarios

Hence, it is not given that the most cost effective ways to prepare will all be for the most likely scenarios.

It is also imagined that all inputs to the calculations should be referenced in publicly available sources and where subjective, from-the-hip estimates are given (such as for the amount of risk reduction an investment results in) rationales should be given for the values chosen.

Perhaps it would be too ambitious for the first iteration of this guide, but at some point one might also want to consider including uncertainty ranges in the various inputs so that one can pick investments not only based on expected cost effectiveness, but also in terms of uncertainty—some people might prefer spending slightly more but having higher certainty that their investments is likely to be useful.

If it is possible, I would also like to explore including something about the current, unfolding catastrophes and what that might imply about future risks. For example, if one looks across the world today, one can see people looking for ways to escape suffering in Ukraine, Lebanon, Syria, Yemen, Afghanistan and many other places. There might be value in simply extrapolating from the recent past and saying that what makes people desperate today is likely to continue to make people desperate in the future. Hence, it might be more worthwhile for the users of this guide to invest in mobility, allowing them to escape hardship and move to another location where they and their loved ones can have more fulfilling lives.

Lastly, and perhaps better saved for future versions, it might be interesting to compare traditional investments in life expectancy to preparedness. For example, buying vegetables costs extra money but reduces risk from cancer and cardiovascular disease. They also take time to prepare. The same with working out and sleeping—could it be that sleeping 30 minutes less is rational to do because the decrease in life expectancy from associated disease is lower than the gain in life expectancy from spending this time being prepared?

Details on most likely risks

This section is envisioned to include more information about the most likely scenarios. In addition to the most likely risks, there might also be a sub section or two on risks that are commonly believed to be large but that analysis shows might not be worth prioritizing.

For the sake of keeping this post from becoming extremely long, I will not list these sections. Moreover, it is currently not clear which risks are the largest—this would require more detailed analysis across the sources we have.

Note that this section is not meant to discuss what might be most useful under each scenario. Instead, such discussion is relegated to the next section. However, it might be that such a separation of scenarios and preparedness investments is suboptimal. Instead, it might be better to integrate a discussion of the solutions into each section on risks. This might also contribute to a shorter text as the authors would not have to repeat or make convoluted references to content in this section on the most likely risk scenarios. There is also the complicating factor of certain preparedness strategies that works across a range of threats.

In any case, it is envisioned that there will be links and references both ways to the spreadsheet with calculations. This is envisioned to help explain certain assumptions in the spreadsheet and also to show the relevance of the content to the calculations that result in the prioritized preparedness investments.

If possible, the section on AI risks will be broken down into action-relevant AI scenarios. For example, there might be a separate section on totalitarian regimes spreading and strengthening, as this would likely have very different preparedness strategies from a scenario in which an AI is putting in motion a mining project on lower Manhattan.

This section will also include a discussion on the probabilities assigned to the most likely risks. This might be important as it seems initially different sources of risk estimates put different probabilities on the various risk categories. This discussion will also help users adjust the probability of each risk category to suit their world view in case they have one they trust more than the authors’.

Details on top ranked interventions

This section serves a few different purposes:

  • More information to help people acquire the top investments. For example, there might be a discussion about whether a bicycle is needed if one has a car, or what exactly a family plan for meet-ups and contacts looks like. As much as possible, such information should refer to sources that describe these well in order to keep the guide brief and minimize the burden on the authors.

  • Explanation of why the top rated investments are the top ones. While this should be possible to understand from the accompanying Google Sheet, a text summary for the reasons behind the top ranked solutions is given both for people to more quickly understand but also for readers that are less numerically inclined.

  • Other discussions, such as perhaps synergies across interventions. For example, perhaps there is a 1 + 1 = 3 from both living a bit away from people and having 5+ years of food storage.

  • Other information I have not yet considered

Local considerations

This section will emphasize that this guide only deals with preparedness that is roughly globally applicable. It is therefore important for users to also factor in local risks. For example, it might be that a user lives in an avalanche prone area, or for users in California, they really want to think about earthquakes.

It might be worth giving readers a few example calculations in this section so they are better prepared to make judgments about risks in their geography. Such an example might be the risk of dying in a hurricane for someone living in Louisiana. The deadliest hurricane in recent history was Katrina with 1392 deaths. With a population of 4600000, you get a chance of dying in the hurricane to be 1392/​4600000=0.03%. If we then assume that with climate change such disasters happen every 5th year (just used my intuition here—to be more closely scrutinized when doing analysis for the guide!), we get 0.03%/​5=0.006% chance of dying each year. This is a crude estimate, and you might want to consider whether you are more or less likely to die than those in previous disasters. For example, during heat waves, deaths are often most common for pregnant women, newborns and the elderly. If you do not belong to the main demographic group of those most likely to die, you might want to further decrease this probability, for example by halving it or so.

Getting started

This section is among the more speculative ones and it is less clear it should be included in the final guide. That said, it might be useful to have some sort of “call to action”. More specifically, for busy readers that just want to do something quick and defer to the analysis and knowledge behind the guide, it might be good to say something like:

  1. Search online for “3M aura face masks” and get 200 of them or whatever maximum quantity you can afford up to 200. If these masks are not available, it is suggested to look for other FFP2 or FFP3 certified masks that fit you well. You might first want to order 1 of these to test their fit as fit is the most important factor in a mask’s protection + something about how to test fit

  2. Clean out as many unnecessary items as possible from your kitchen. With the space that is hopefully released, fill up as much of it as possible with:

    1. 10% of the space with refined canola oil

    2. 50% of the space with rice and pasta

    3. 40% of the space with dried beans and lentils

  3. Etc.

The above is just an example of what this section might look like and it is imagined the final “get started” section is likely to have other recommendations. Still, it is envisioned to be written in the style above, like a recipe with specific and easy actions someone can take.

It is unclear if another section should be added such as “stepping up your game” in which one assumes all action in the getting started section has been taken and the reader is looking at spending more time and/​or money on preparing more thoroughly.