Lack of conceptual understanding of the basics seems to me like a major reason why people keep on doing activities that sound like "AI Safety" but are likely making things worse.
It's also what we're trying to change with Lens Academy.
Interesting hypothesis that such basics might be less understood because they're inherently less trained in practice while doing research. Seems plausible.
I do also think the AI Safety education space has a share in this, focusing too much on prosaic empirical methods at the cost of strategy and conceptual fundamentals.
Shout outs to AFFINE and Iliad Intensive for also emphasising the basics (as far as I can see)
The point I make here is that having a deep understanding of AI safety helped keep me focused in my undergrad. That is, deeply understanding what the problem is and why it is difficult keeps one convinced that they should continue working on the right kinds of things.
Also though: A lot of pretty profound ideas come from pretty simple intuitions about foundational concepts. E.g., my understanding is Alan Turing came up with the idea of a Turing machine by reasoning about how a human computer would calculate something. But then the Turning machine model is a really powerful mathematical tool for all sorts of things. Similar things (where a simple intuition motivated a key discovery) happened with neural networks and possibly special relativity if my understanding of the history is correct. To me, understanding the basics is a prerequisite (or maybe the main prerequisite) for all of this.
thanks!
these examples are much more convincing than the essay's. i haven't looked at each closely, but if these several inventions are all due to deep understanding, that is indeed a recommendation for deep understanding.
were i not already convinced of the importance of deep understanding in advancing the frontier of human knowledge, this comment would be a good starting point.
may i ask: why not use these examples in the original essay? the essay touts results like "know dates", "save face if documentarians come round", "finish a degree / turn down quant offers". these are -- lightly now -- relatively less interesting to me than, like, "invent turing machines".
if i model the goal of the essay's author as "try to convince me that deep understanding is worthwhile", then i am very confused. why would such an author appeal to the examples in the essay, if they could have reached for the ones in the comment?
do i misunderstand the essay's goal?
I see the goal here is to give an intuitive feeling for how basic gaps in knowledge can emerge. I see this happen all the time in AI safety and as someone who runs an AI safety program, I actually find this example more interesting than the Turing machine example. But that's a personal thing and although I think this kind of lesson should hold generally, convincing the reader of this isn't the core thing I'm interested in.
Taking this literally, trees being made out of air implies a lot of useful facts about the world:
Obviously much of this speculation of how 'trees are made out of air' allows you to predict that Drexlerian assemblers, constructed via a misaligned superintelligence, will convert the Earth into computronium is benefited by a lot of hindsight; if you told a 15th-century peasant that 'trees are made out of what Plato called aer', they would almost certainly say 'neat fact' and not suddenly refactor their entire epistemology to be based on that factoid, even though I think they should.
But knowing such facts with as much general utility as 'trees are made of air' are very useful to gain a highly sample-efficient epistemology; and you very much want sample efficiency when trying to align AI, because aligning sufficiently advanced AI is a textbook example of a problem with extremely sparse rewards (this follows naturally from the fact that the entirety of humanity may only get only one shot to align said AIs).
The power to correctly reason about trees in a wider range of circumstances, which generalizes to all organisms that do photosynthesis and their effect on their environment? Also a generalization that the physical properties of a thing don't always intuitively match the properties of "where it came from" - trees are solid and brown like ground, and so it will seem like there's probably a strong relation between the content of a tree and the content of the ground, And the roots really look like they're sucking important things from the ground, but guessing that trees came mostly from ground would be wrong, and this "the world is weird and your intuitions can be wrong" lesson generalizes, and could spark thoughts of what other cool things chemistry might be capable of, as well as making one more careful about making similar guesses in the future.
Understanding the basics of the carbon cycle is pretty critical - misunderstanding of which, e.g., drives much of the idiocy around climate chang being unsolvable.
Very little, but realising that implies you have a gears level understanding of what's actually happening in biology rather than just being able to solve the problems you get asked in exams.
Reminds me of https://calteches.library.caltech.edu/46/2/LatinAmerica.htm
https://en.wikipedia.org/wiki/Justus_von_Liebig. Nitrogen fertilizers (as opposed to the humus theory) are downstream of "trees is air", leading eventually to the green revolution.
It's evidence of a wider array of knowledge they have not unlocked. Learning more biochemistry has put me on firmer ground when trying to evaluate nutrition facts which was an area where before I was epistemically helpless. Learning the basics takes less time than you might think and you waste less time listening to idiots (on for example nutrition). Language models are good at biochemistry, but they will imitate a dumb nutritionist rather than a nutritionist who knows biochemistry if you don't use the right vocabulary.
One student, upon being told that most of the mass in the wood comes from and not the dirt in the ground, said “that's very disturbing and I wonder how that could happen.” And that’s an MIT graduate.
Yes, and some Harvard grads thought the seasons were caused by varying distance between the Earth and the Sun. However, this source was 1987, and judging by the VHS cassette in yours, it was probably also old. So I suspect that there would greater awareness now with climate change that trees soak up CO2, and that both unis have made more of an effort to have their students know things like this because of the bad press. Also, I expect that there was some cherry-picking. However, I agree with your overall point that many well educated people don't know basic facts about the world.
Some pedantry: living trees have a lot of water, so by mass the tree may even be predominantly water, depending on the tree.
Yes! This is true. I tried to say "dead tree" or "dry tree" to avoid this but reading through it again maybe it is confusing. I think I'll add a footnote to clarify. Thanks!
I also read the Aeneid while studying Latin. It isn't hard to recognize the symmetrical structure of the line 'spem vultu simulat, premit altum corde dolorem' in Book 1, line 209. You might also know—whether from being taught or simply by intuition—that this reflects Aeneas's internal state at the time. To be fair, in the context of studying Latin, that qualifies as 'basic knowledge.' I don't want to deny that this played a huge role in helping me read the Aeneid to the very end. That specific knowledge wasn't actually all that useful for getting a high score on the AP Latin exam. Ultimately, however, that seemingly trivial piece of information helped me finish the book, and it undoubtedly gave me the motivation to master the rest of the material needed to get a good grade. I'm not entirely sure, though, if my experience relates to the aspiring AI alignment researchers you mentioned.
Its a beautiful line! Not sure if it relates to this essay but I find it highly relevant to our current moment.
Thank you for saying that. In fact, I believe this is exactly why many colleges still utilize a 'holistic review' process in their admissions, evaluating essays and extracurricular activities rather than just relying on numbers.
Numbers like GPAs and AP scores certainly demonstrate a student's academic capabilities. However, through essays, colleges want to see how foundational knowledge—such as the fascinating yet scientifically obvious truth that a tree is mostly made of air—supports and shapes a person's life values. College is a marathon, not a sprint. And I believe it is precisely this kind of wisdom that helps us complete that marathon.
I am currently 19 years old and will be starting college as a freshman this September, which is probably why your writing resonated with me so deeply.
When you do a BlueDot reading group you hopefully learn AI safety basics.
How sure are you about this?
[Epistemic status: Rumor
Someone told me that the BlueDot team don't believe in full AI X-risk, but instead teach smaller risk, e.g. misuse risks. I have not verified this, or looked at their curriculum to see what they teach.]
But when you ask them why they care about AI safety they don’t provide a particularly coherent answer. So I get more specific: “Why should we think AI is an existential risk?” Again, incoherent answer.
I'm not surprised about this. But I'm leaning towards that the problem is that they never really leaned it, rather than that they learned it and forgot.
Historical context - the human stories of science, vignettes from the climb up from animal ignorance, driven by need or curiosity - helps to make that story coherent. It was around 1620 when curiosity impelled Jan van Helmont to grow a willow tree, in a weighed pot of soil, for 5 years - then pull it up, clean the roots, and weigh both tree and soil. His conclusion was that trees are made of water. Generations later Lavoisier amended that to "air and water" - by carefully capturing and analyzing combustion products - before being beheaded in the French Revolution (1794).
dry wood is mostly CO2
FWIW, you appear to be confusing two claims:
"Most mass in trees was previously part of the surrounding air"
"dry wood is mostly CO2"
From a US Forest Service website:
Wood is best defined as a three-dimensional biopolymer composite composed of an interconnected network of cellulose, hemicelluloses and lignin with minor amounts of extractives, and inorganics. The major chemical component of a living tree is water, but on a dry weight basis, all wood cell walls consist mainly of sugar-based polymers (carbohydrates, 65-75%) that are combined with lignin (18-35%).
https://research.fs.usda.gov/treesearch/42245
"Trees are mostly made of air" (direct quote from post title) is more clickbait headline than scientific fact.
Tangentially, here's a little Feynman interview excerpt in which he talks about trees coming out of the air, and how they store sunlight in a sense.
Trees are air actually came from people reasoning across fields (physicians, ministers, chemists, not botanists). I buy the missing-basics point, but what's the AI safety equivalent?
But when you ask them why they care about AI safety they don’t provide a particularly coherent answer. So I get more specific: “Why should we think AI is an existential risk?” Again, incoherent answer.
Related: My hobby: running deranged surveys
At the risk of embarrassing myself, I’ll share a confession.
For context, I took five years of Latin: four in high school and one in college. In addition to learning the language, all my Latin classes taught a lot about Roman history. Emperors, internal politics, Caesar, etc. I was always learning some random bag of facts about Roman history. In high school, I won the award for top Latin student in my graduating class. So I wasn’t a bad Latin student.
Here’s the confession: I somehow don’t even vaguely remember the rough timespan the Roman Empire existed. Maybe Jesus time? I know he was killed by the Romans (is that right?). Were they around for a long time after? A long time before that? When was Romulus and Remus allegedly fighting? Virgil wrote the Aeneid when? I don’t have a clue. Despite being a kind of “Latin expert” I am missing a much more important foundational fact: when all of this was happening.
When I say trees are made out of air I’m not talking about the fact that there is a lot of empty space inside a tree (or actually anything made out of atoms). I mean something more mind-blowing.
Imagine you are holding a piece of dry wood. Where did that wood come from? A tree. Okay sure, but what are you actually holding? Where did the tree get that stuff? It turns out that almost all of the mass in dry wood comes from the in the air. This follows from a simple fact about how photosynthesis works:
The carbon and the oxygen in the glucose ( ) come from the and the hydrogen comes from the water. Since hydrogen is the lightest atom in the universe, it adds almost no mass, so nearly all the mass of glucose traces back to the . Wood is mostly built from glucose, so by mass, a dead tree[1] is mostly the carbon and oxygen that came out of the air.
It’s kind of unintuitive. Wood is hard and stiff and air is not even close to either of those things. But if you are a biologist or know some basic chemistry you would think that this is the kind of obvious thing you would want to know. At the very least you would expect the best math and science students in the world to be familiar with such basic biology. But take a look at this video of a documentary film crew asking MIT graduates where they think wood comes from:
One student, upon being told that most of the mass in the wood comes from and not the dirt in the ground, said “that's very disturbing and I wonder how that could happen.” And that’s an MIT graduate.
“Trees come from mostly air” is pretty fundamental for biology because it follows from photosynthesis which is in many ways the basis for life on earth. In a sane world, every 8th grader would know that dry wood is mostly , not like minerals found in the ground or something. MIT grads probably have vast amounts of detailed knowledge of math, physics, biology, chemistry or all of the above. But they don’t know some basic facts about biology.
There is this assumption that you should first learn the foundational facts of an area of study and then move to more and more specific questions and ideas. As you move up levels of classes, the foundational stuff seems more and more basic and less and less relevant. Some stuff is continually hammered in because it’s useful background knowledge. In a perfect world, this helps you internalize the basics and learn how to reason about them to solve harder and harder problems.
There are some areas where, without much effort, this may work out. For example, you learn fractions in first or second grade but will probably understand them more deeply by the time you get to calculus because you need to know fractions to do calculus and all the classes that come before calculus. But not all foundational knowledge is like this! Knowing where trees come from doesn’t help you answer organic chemistry or evolutionary biology questions.
Being 1. foundational and being 2. useful for answering increasingly specific questions are different things. They are certainly not orthogonal but they are also not perfectly correlated. When 1 & 2 diverge, you get MIT grads who are confused about what wood is.
In AI safety, this can be a serious problem.
I have had one-on-ones or interviewed dozens of students who want a career in AI safety. There are many examples of students who are something like this: they know what alignment faking is, read LessWrong, know who Neel Nanda is, know what METR is, have done an interp project, etc. But when you ask them why they care about AI safety they don’t provide a particularly coherent answer. So I get more specific: “Why should we think AI is an existential risk?” Again, incoherent answer.
This may be because they don’t really care much about AI safety and they just like to hang out with EA/rationalist types. An alternative reason (which I think is more likely) is because AI safety basics are something you learn and don’t exercise. When you do a BlueDot reading group you hopefully learn AI safety basics. But when doing interp experiments or your first SPAR research project, you think about specific empirical questions, not the orthogonality thesis. You don’t think about the basics and you don’t internalize them and certainly cannot reason about them.
Instrumental convergence, inner alignment, reward misspecification, etc. are our “trees are made out of air” or “the Roman Empire was 27 BC to 476 AD”. But lots of people in AI safety programs or those applying for them don’t know the basic facts. They know a lot of specific things but somehow not the foundational things.
This strikes me as a genuine failure mode. A lot of focus goes into having great fellowship programs and university groups but some conceptual knowledge seems to be slipping through the cracks. I hope the next generation of AI safety researchers have all of the conceptual knowledge of earlier researchers and more.
I’ll leave you with an additional confession. 6ish years ago, before I started college, this was probably me, at least partly. I understood the basic alignment problem but understood it mostly through outer-alignment issues and didn’t fully internalize the difficulty of the problem until I started college. That was roughly 4 years ago when I moved into the UChicago dorms. From the very beginning, I was a CS major because I wanted to be an AI safety researcher. A few hours ago I turned in my last paper, and now I’m done.
My primary reflection is this: I would not have become a CS major, would not have worked so hard, would not have been so laser-focused on AI safety if I didn’t actually understand it. I would have got distracted and ended up probably on Wall Street or worse. This is because knowing a problem tells you why you should care. So if there is one reason to embrace the basics, it is that. There is so much fucking power in actually understanding something.
The reason I'm saying "dead tree" or "dry tree" above is that living trees can contain a lot of water mass but this analysis only focuses on the non-water parts of the tree--i.e., the hard "wood stuff."