By and large, the President of the United States can order people to do things, and they will do those things.

I think this exaggerates the power of the president. Obama did try to order Gitmo closed. Trump did try to withdraw troops from Afghanistan and failed.

On the specific topic of COVID-19 Trump spoke about having a vaccine quite early, likely because he believed he could just approve it and get it distributed even if the evidence for the vaccine was only a little better then the evidence then what Benjamin Jesty had. 

It turns out that the president doesn't have the power to just approve a vaccine without it having gone through "enough" testing. 

This is one of those posts, like "pain is not the unit of effort," that combines a memorable and informative and very useful and important slogan with a bunch of argumentation and examples to back up that slogan. I think this type of post is great for the LW review.

When I first read this post, I thought it was boring and unimportant: trivially, there will be some circumstances where knowledge is the bottleneck, because for pretty much all X there will be some circumstances where X is the bottleneck.

However, since then I've ended up saying the slogan "when money is abundant, knowledge is the real wealth" probably about a dozen separate times when explaining my career decisions, arguing with others at CLR about what our strategy should be, and even when deliberating to myself about what to do next. I guess longtermist EAs right now do have a surplus of money and a shortage of knowledge (relative to how much knowledge is needed to solve the problems we are trying to solve...) so in retrospect it's not surprising that this slogan was practically applicable to my life so often.

I do think there are ways the post could be expanded and improved. Come to think of it, I'll make a mini-comment right here to gesture at the stuff I would add to it if I could:

1. List of other ideas for how to invest in knowledge. For example, building a community with good epistemic norms. Or paying a bunch of people to collect data / info about various world developments and report on them to you. Or paying a bunch of people to write textbooks and summaries and explainer videos and make diagrams illustrating cutting-edge knowledge (yours and others').

2. Arguments that in fact, right now, longtermist EAs and/or AI-risk-reducers are bottlenecked on knowledge (rather than money, or power/status)

--My own experience doing cost-benefit analyses is that interventions/plans vary in EV by OOMs and that it's common to find new considerations or updated models that flip the sign entirely, or add or subtract a few OOMs, for a given intervention/plan. This sure seems like a situation in which more knowledge is really helpful compared to just having more money & ability to execute on plans.

--Everyone I've talked to in government/policy says that the bottleneck is knowledge. Nobody knows what to advocate for right now because everything is so uncertain and backfirey. (See previous point, lol)

--One might counterargue that it is precisely for the above reasons that we shouldn't invest in knowledge; we aren't getting much knowledge out of our research and we still won't in the future. Instead, our best hope is to accumulate lots of power and resources and then when the crucial crunch time period comes, hopefully it'll be clear what to do. Because the world might hand us knowledge on a silver platter, so to speak, in the form of new evidence. No need to deduce it in advance.

--(I have a couple responses to the above counterargument, but I take it seriously and think that others should too)

--Reasoning by analogy, making AI go well sure seems like the sort of problem where knowledge is the bottleneck rather than money or power. It seems a lot more like figuring out the laws of physics and building a safe rocket before anyone gets killed in an unsafe rocket, or building a secure merchant drone operating system before anyone else builds an unsecure one, than e.g. preventing malaria or reforming US animal welfare laws.

Curated.

If I understood it correctly, the central point of this post is that very often, knowing what to do is a much larger problem than having the ability to do things, i.e., money and power. I often like to say that planning is an information problem for this reason. This post is an excellent articulation of this point, probably the best I've seen.

It's an important point. Ultimately, it is precisely this point that unifies epistemic and practical rationality, the skills of figuring out what's true and skills of achieving success. When you recognize that success is hard because you don't know what to do, you appreciate why understanding what is actually true is darned important, and that figuring out how to discover truth is among the best way to accomplish goals whose solution isn't known.

This can all get applied downstream in Value of Information calculations and in knowledge-centric approaches to planning. It's good stuff. Thanks!

Great summary! A nit:

our lizard-brains love politics

it's more likely our monkey (or ape) brains that love politics. e.g. https://www.bbc.co.uk/news/uk-politics-41612352

On the note of monkey-business - what about investments in collective knowledge and collaboration? If you've not come across this, you might like it https://80000hours.org/articles/coordination/

EDIT to add some colour to my endorsement of the 80000hours link: I've personally found it beneficial in a few ways. One such is that although the value of coordination is 'obvious', I nevertheless have recognised in myself some of the traits of 'single-player thinking' described.

This is an idea I've been struggling to wrap my head around for a while now. I usually think of it as "capital vs knowledge" instead of "money vs knowledge". But since knowledge is a form of capital, your phrasing is more accurate.

I also agree the low hundred thousands is about where this happens for someone who lives in the United States and works a full-time job. I wonder how this number changes if you have passive income instead.

Excellent article! I agree with your thesis, and you’ve presented it very clearly.

I largely agree that we cannot outsource knowledge. For example, you cannot outsource the knowledge to play the violin, and you must invest in countless hours of deliberate practice to learn to play the violin.

A rule of thumb I like is only to delegate things that you know how to do yourself. A successful startup founder is capable of comfortably stepping into the shoes of anyone they delegate work to. Otherwise, they would have no idea what high-quality work looks like and how long work is expected to take. The same perspective applies to wanting to cure ageing with an investment of a billion dollars. If you don’t know how to do the work yourself, you have little chance of successfully delegating that work.

Do you think outsourcing knowledge to experts would be more feasible if we had more accurate and robust mechanisms for distinguishing the real experts from the noise?

This post’s claim seems to have a strong and weak version, both of which are asserted at different places in the post.

1. Strong claim: At some level of wealth and power, knowledge is the most common or only bottleneck for achieving one’s goals.
2. Weak claim: Things money and power cannot obtain can become the bottleneck for achieving one’s goals.

The claim implied by the title is the strong form. Here is a quote representing the weak form:

“As one resource becomes abundant, other resources become bottlenecks. When wealth and power become abundant, anything wealth and power cannot buy become bottlenecks - including knowledge and expertise.”

Of course, knowing arbitrary facts (N values of an infinite sequence of randomly generated numbers) is not what’s meant by “knowledge and expertise.” What is?

I’d suggest “sufficient and necessary knowledge to achieve a given goal.” A person who can achieve a goal, given some reasonable but not excessive amount of time and money, is an expert at achieving that goal.

As others pointed out, just because a person calls themselves an expert in goal G doesn’t mean that they are. John’s point is that being able to identify an expert in goal G, or an expert in identifying experts in goal G, when you yourself wish to achieve goal G, is its own form of expertise.

This in turn suggests that finding, sharing and verifying expertise is a key problem-solving skill. At any given time, we have:

1. Questions nobody can answer.
2. Answers nobody can understand.
3. Answers nobody can verify.

To these short statements, insert the qualifiers “crucial,” “presently,” “efficiently,” and so on. Some of the most important questions are about other questions, such as “what questions should we be asking?”

I expect these problems to be simultaneous and mutually-reinforcing.

in the space of aging (or models in bioscience research in general), you should contact Alexey Guzey and Jose Ricon and Michael Nielsen and Adam Marblestone and Laura Deming. You'd particularly click with some of these people, and many of them recognize the low number of independent thinkers in the area.

I think you have a kind of thinking that almost everyone else in aging I know seems to lack (If I showed your writing to most aging researchers, they'd most likely glare over what you wrote), so writing a good way to, say, put a physical principles framework to aging can result in a lot of people wanting to fund you (a la Pascal's wager - there are LOTS of people who are willing to throw money into the field even if it doesn't have a huge chance of producing results - and a good physical framework can make others want you to make the most out of your time, especially as many richer/older people lack the neuroplasticity to change how aging research is fine). Many many many papers have already been written on the field (many by people making guesses as to what matters most) - a lot of them being very messy and not very first-principles (even JP de magalhaes's work, while important, is kind of "messy" guessing at the factors that matter).  

Are you time-limited? Do you have all the money needed to maximize your output on the world? (note for making the most out of your limited time, I generally recommend being like mati roy and trying to create a simulation of yourself that future you/others can search, which generally requires a lot of HD/streaming - though even that is not that expensive). 

It seems that you can understand a broad range of extremely technical fields that few other people do (esp optimization theory and category theory), and that you get a lot out of what you read (the time investment of other people reading a technical textbook may not be as high as that of you reading one) - thus you may be more suited for theoretical/scaleable work than you are for work that's less generalizeable/scaleable (one issue with bioscience research is that most people in bioscience research spend a lot of time on busywork that may be automated later, so most biologists aren't as broad or generalizeable as you are, and you can put together broad frameworks that can improve the efficiencies/rigor of future people who read you, so you should optimize for things that are highly generalizeable.)

[you also put them all in a clear/explainable fashion that makes me WANT to return back to reading your posts, which is not something I can say for most textbooks].

There are tradeoffs between spending more time on ONE area vs spending time on ANOTHER area of academic knowledge - though there are areas where good thinking in one area can transfer to another (eg optimization theory => whole cell modeling/systems biology in biology/aging). Building general purpose models (if described well) could be an area you might have unique comparative advantage over others in, where you could guide someone else's thinking on the details even if you did not have the time to look at the individual implementations of your model on the system at hand. 

If you become someone who everyone else in the area wants to follow (eg Laura Deming), you can ask question and get pretty much every expert swarming over you, wanting to answer your questions.

You seem good at theory (which is low-cost), but how much would you want to ideally budget for sample lab space and experiments? [the more details you put in your framework - along with how you will measure the deliverables, the easier it would be to get some sort of starter funding for your ideas]. Doing some small cheap study (and putting all the output in an open online format that transcends academic publishing) can help net you attention and funding for more studies (it certainly seems that with every nascent field, it takes a certain something to get noticed, but once you do get noticed, things can get much easier over time, particularly if you're the independent kind of person). Wrt biology, I do get the impression that you don't interact much with other biologists, which might make the communication problems more difficult for now [like, if I sent your aging posts as is to most biologists I know, I don't think they would be particularly responsive or excited].

BTW - regarding wealth - fightaging has a great definition at https://www.fightaging.org/archives/2008/02/what-is-wealth/

Wealth is a measure of your ability to do what you would like to do, when you would like to do it - a measure of your breadth of immediately available choice. Therefore your wealth is determined by the resources you presently own, as everything requires resources.

Generally speaking, due to aging [and the loss of potential that comes with it] most people's wealth decreases with age (it's said that the wealthiest people are really those that are born) - however, your ability to imagine what you can do with wealth (within an affordance space - or what you can imagine doing over the next year if given all the resources you can handle - framework) can increase over time. Mental models are only wealth inasmuch as they actively work to improve people's decision-making on the margin relative to an alternative model (they are necessary for innovation, but there are now so many mental models that taking time to understand one reduces the amount of time one has to understand another mental model) - I do believe that compressible mental models (or network models) that explain a principle elegantly can offload the time investment it takes to use a model to act on a decision (eg superforecasters use elegant models that others believe and can act on - thus knowing when to use the expertise of superforecasters can help decision-making). Not many people can create an elegant mental model, and fewer can create one that is useful on top of all the other models that have been developed (useful in the sense that it makes it more useful for others to read your model than all the confusing model renditions used by others) - obviously there is vast space for improvement on this front (as you can see if you read quantum country) as most people forget the vast majority of what they read from textbooks or from conversations with others. Presentism is an ongoing issue as more papers/online content is published than there are total eyeballs to read them (+all the material published in the past)

The best kind of wealth you can create, in this sense, is a model/framework/tool that everyone uses. Think of how wealth was created with the invention of a new programming language, for example, or with Stack Exchange/Hacker News, or a game engine, or the wealth that could be created with automating tedious steps in biology, or the kind that makes it far easier for other people to make or write almost anything. The more people cite you, the more wealth and influence (of a certain kind) you get. This generalizes better than putting your entire life into studying a single protein or model organism, especially if you find a model/technique that is easily-adoptable and makes it easy to do/automate high-throughput "-omics" of all organisms and interventions at once (making it possible for others to speed up and generalize biology research where it used to be super-slow). Bonus points if you make it machine-readable and put in a database that can be queried so that it is useful even if no one reads it at first [as amount of data generated is higher/faster than the total mental bandwidth/capacity of all humans who can read it]. 

[btw, attention also correlates with wealth, and money/attention/wealth is competitive in a way that knowledge is not (wisdom may be which knowledge to read in which order - wisdom is how you can use knowledge to maximize the wealth that you can use with that knowledge)]

[Shaping people's framework by causing them to constantly refer to your list of causes, btw, is another way to create influence/wealth - but this may get in the way of maximizing social wealth over a lifetime if your frameworks end up preventing people from modeling or envisioning how they can discover new anomalies in the data that do not fit within those frameworks - this is also why we just need a better concrete framework with physical observables for measuring aging rate, where our ability to characterize epigenetic aging is a local improvement. ]

In the area of aging already there is too much "knowledge" (though not all of it particularly insightful), but does the sum of all aging papers published constitute as knowledge? Laura Deming mentions on her twitter that she thinks about what not to read, rather than what to read, and recommends students study math/CS/physics rather than biochemistry. There can be a way to compress all this knowledge into a more organized physical principles format that better helps other people map what counts as knowledge and what doesn't count - but at this moment the sum of all aging research is still a disorganized mess, and it may be that the details of much of what we know now will become superseded by new high-throughput papers that publish data/meta-data rather than as papers (along with a publicly accessible annotation service that better guides people as to which aging papers represent true progress and which papers will simply obsolete quickly.). Guiding people to the physical insight of a cell is more important for this kind of true understanding of aging, even though we can still get things done through rudimentary insight-free guesses like more work on rapamycin and calorie restriction.

The best investments in knowledge are mental models that can be applied across domains (some of which were mentioned in the post) and unchanging/permanent/durable knowledge like that in the STEM fields. This provides both leverage (from the cross-disciplinary latticework of mental models) and allows compounding to work as your knowledge compounds over the years.

The world would undoubtedly be better if more Data Scientists became monks. 

I agree. But knowledge was abundant for him too. What wasn’t abundant was critical thinking. And this was the problem from the start

The idea of knowledge over money is romantic and one that I agree, is at times the right long-run bet. I understand you're arguing for diminishing returns here but the issue I've found is that some tiers of wealth *on average* allow one to access tiers of collectives of knowledge that meaningfully impact your ability to scale with lower effort (& thus at equal effort, faster).

So, two years ago I quit my monetarily-lucrative job as a data scientist and have mostly focused on acquiring knowledge since then. I can worry about money if and when I know what to do with it.

Also this knowledge only matters if you do something useful with that knowledge, which I'm convinced that you are, for instance. many other people are not able to create useful knowledge and thus may be better suited for earning2give.

This is why money printing by itself doesn't generate more wealth. It's human ingenuity that comes from education/knowledge that actually moves the needle and improves our living standards over time.