Below I'll argue that transitioning to a diet produced without sunlight (via vertical farming as well as labs and, eventually, food synthesizers) has several major benefits that I feel are underappreciated. As this will require colossal amounts of power, a rapid transition away from farming is likely only advantageous after the widespread construction of clean energy and carbon capture infrastructure; however, I feel that greater resources should be directed towards developing new food production technologies immediately.
1) Potential to restore vast amounts of natural habitat:
According to the UN FAO, roughly 38% of Earth's surface area is used for agriculture; perhaps more relevantly--as, for example, deserts host relatively little life for either animals as a whole or farmers--over half of the planet's habitable land mass is reserved for human food production. A scenario where vertical farming produces plant food, labs supply synthetic meat, and, perhaps, primitive food synthesizers provide some simple foods with high value like milk, it might be possible to almost double the amount of natural habitat available for non-human life (and, to some extend, human life as well).
2) Protection from WMDs:
Our dependence on sunlight may render us vulnerable to a near extinction event via nuclear winter. It's beyond my knowledge how likely it is that billions of people would die from starvation due specifically to nuclear winter (both due to its plausibility and its relevance if almost everyone would be more directly killed by nukes anyways in a nuclear winter scenario); however, from what I gather, it's a reasonable enough risk to give at least some weight to.
Filtered air entering these facilities could protect against chemical (defoliants and otherwise) and biological attacks. (There is a counterpoint that concentrating a nation's food supply, at least if done to an extreme extent, makes it easier to significantly destroy with explosives.)
3) Greater food supply reliability:
As the variables with indoor production are largely optimized and controlled while conventional farming is subject to extreme weather, societies should benefit from much more predictable food output; this would not only offer enhanced food security and lower price volatility but also--everything else being equal--result in lower prices as labor force efficiency is enhanced by not needing to frequently shift practices to meet the challenges of supply constrictions and excesses.
Additionally, as growing seasons are shorter (and able to be planned without regard to nature), indoor farming could more rapidly rectify shortages during the era where both indoor and conventional farming are substantially practiced.
4) Expedited space colonization:
Even a largely or highly terraformed planet may have difficulty growing certain Earth crops (eg due to low gravity or loss to indigenous subterranean peoples) and highly developed indoor food production technology may accelerate life's ability to multiple throughout the universe.
I believe this also slightly lowers our chance of extinction; however--as I see AI as the only bona fide extinction threat before we are capable of space colonization and I'm skeptical that becoming multiplanetary will save us from hostile superintelligent AI--I suspect our survival hinges more on education and appreciated mutual interests rather than rapid space colonization or technological solutions in general.
~Ty
Reactions
More posts like this
Curated and popular this week
·
Note: I am not a malaria expert. This is my best-faith attempt at answering a question that was bothering me, but this field is a large and complex field, and I’ve almost certainly misunderstood something somewhere along the way.
Summary
While the world made incredible progress in reducing malaria cases from 2000 to 2015, the past 10 years have seen malaria cases stop declining and start rising. I investigated potential reasons behind this increase through reading the existing literature and looking at publicly available data, and I identified three key factors explaining the rise:
1. Population Growth: Africa's population has increased by approximately 75% since 2000. This alone explains most of the increase in absolute case numbers, while cases per capita have remained relatively flat since 2015.
2. Stagnant Funding: After rapid growth starting in 2000, funding for malaria prevention plateaued around 2010.
3. Insecticide Resistance: Mosquitoes have become increasingly resistant to the insecticides used in bednets over the past 20 years. This has made older models of bednets less effective, although they still have some effect. Newer models of bednets developed in response to insecticide resistance are more effective but still not widely deployed.
I very crudely estimate that without any of these factors, there would be 55% fewer malaria cases in the world than what we see today. I think all three of these factors are roughly equally important in explaining the difference.
Alternative explanations like removal of PFAS, climate change, or invasive mosquito species don't appear to be major contributors.
Overall this investigation made me more convinced that bednets are an effective global health intervention.
Introduction
In 2015, malaria rates were down, and EAs were celebrating. Giving What We Can posted this incredible gif showing the decrease in malaria cases across Africa since 2000:
Giving What We Can said that
> The reduction in malaria has be
·
Cross-posted to Lesswrong
Introduction
Several developments over the past few months should cause you to re-evaluate what you are doing. These include:
1. Updates toward short timelines
2. The Trump presidency
3. The o1 (inference-time compute scaling) paradigm
4. Deepseek
5. Stargate/AI datacenter spending
6. Increased internal deployment
7. Absence of AI x-risk/safety considerations in mainstream AI discourse
Taken together, these are enough to render many existing AI governance strategies obsolete (and probably some technical safety strategies too). There's a good chance we're entering crunch time and that should absolutely affect your theory of change and what you plan to work on.
In this piece I try to give a quick summary of these developments and think through the broader implications these have for AI safety. At the end of the piece I give some quick initial thoughts on how these developments affect what safety-concerned folks should be prioritizing. These are early days and I expect many of my takes will shift, look forward to discussing in the comments!
Implications of recent developments
Updates toward short timelines
There’s general agreement that timelines are likely to be far shorter than most expected. Both Sam Altman and Dario Amodei have recently said they expect AGI within the next 3 years. Anecdotally, nearly everyone I know or have heard of who was expecting longer timelines has updated significantly toward short timelines (<5 years). E.g. Ajeya’s median estimate is that 99% of fully-remote jobs will be automatable in roughly 6-8 years, 5+ years earlier than her 2023 estimate. On a quick look, prediction markets seem to have shifted to short timelines (e.g. Metaculus[1] & Manifold appear to have roughly 2030 median timelines to AGI, though haven’t moved dramatically in recent months).
We’ve consistently seen performance on benchmarks far exceed what most predicted. Most recently, Epoch was surprised to see OpenAI’s o3 model achi
·
Cross-posted from my blog.
Contrary to my carefully crafted brand as a weak nerd, I go to a local CrossFit gym a few times a week. Every year, the gym raises funds for a scholarship for teens from lower-income families to attend their summer camp program. I don’t know how many Crossfit-interested low-income teens there are in my small town, but I’ll guess there are perhaps 2 of them who would benefit from the scholarship. After all, CrossFit is pretty niche, and the town is small.
Helping youngsters get swole in the Pacific Northwest is not exactly as cost-effective as preventing malaria in Malawi. But I notice I feel drawn to supporting the scholarship anyway. Every time it pops in my head I think, “My money could fully solve this problem”. The camp only costs a few hundred dollars per kid and if there are just 2 kids who need support, I could give $500 and there would no longer be teenagers in my town who want to go to a CrossFit summer camp but can’t. Thanks to me, the hero, this problem would be entirely solved. 100%.
That is not how most nonprofit work feels to me.
You are only ever making small dents in important problems
I want to work on big problems. Global poverty. Malaria. Everyone not suddenly dying. But if I’m honest, what I really want is to solve those problems. Me, personally, solve them. This is a continued source of frustration and sadness because I absolutely cannot solve those problems.
Consider what else my $500 CrossFit scholarship might do:
* I want to save lives, and USAID suddenly stops giving $7 billion a year to PEPFAR. So I give $500 to the Rapid Response Fund. My donation solves 0.000001% of the problem and I feel like I have failed.
* I want to solve climate change, and getting to net zero will require stopping or removing emissions of 1,500 billion tons of carbon dioxide. I give $500 to a policy nonprofit that reduces emissions, in expectation, by 50 tons. My donation solves 0.000000003% of the problem and I feel like I have f
I agree the benefits of closed environments system that you bring up are considerable, in fact there are even more benefits than those mentioned (see this paper). I wanted to bring in some other considerations to enrich the discussion around this:
If the closed environment system depends significantly on sunlight-based renewable energy sources such as solar and wind, then it is not resilient to abrupt sunlight reduction scenarios such as nuclear winter.
There are many other possibilities outside of vertical farming for closed environment food production, many of which are significantly more efficient in their energy usage. I ran a simple estimation based on a yield of between 5-40 kg lettuce/m2/y and a calorie content of 150 kcal/kg, resulting on and energy efficiency in terms of electricity to calories of 0.1-0.9%. Compare to other systems with efficiencies around 20% such as single cell protein from CO2 (From one of my papers on closed environment food production methods for space/bunkers).
Thanks for your response.
I checked out your website (including your FAQ where you point out the limits of storing food rather than focusing on the means to resiliently produce it) and I was wondering if you guys thought there might be some merit to strategic supplies of vegetable oil even if to only help buy several months of time for other operations to ramp up? A 55 gallon barrel of vegetable oil has ~2,100,000 calories, is edible for ~2 years, and--in order to prevent waste--could be sold and replaced after several months as it has industrial value (eg as biofuel).
While you are correct that vegetable oil would be the most compact way of storing edible calories, we wouldn't be able to rely only on it as it misses several key nutrients, and it would still not solve the prohibitive cost of storing enough food to last for a multi-year catastrophe. We think strategic micronutrient supplement stocks could be cost-effective but haven't looked into it in depth yet.
Any type of food stock would be very useful on the onset of a catastrophe, but the cost-effectiveness of large-scale long-term food storage interventions is not great.