Some thoughts on Effective Altruism – Two memes

Perhaps the most important thing to understand about EA is that, from the beginning, it was composed of two entwined memes.

Charity is inefficient

The first of these memes was that by using reason and evidence you could do much more good, with charity, than the default

In the early 2010s, there were some nerds on the internet (LessWrong and GiveWell and some other places) writing about, among other things, how to optimize charitable giving.

It seemed like the charity sector, in general, was not very efficient. With careful thought and research you could easily outcompete the charity sector as a whole, making investments that are orders of magnitude more effective than donating with a typical amount of thought.

The basic claim here is about competence: by being more thoughtful and rational, by doing research, we can outcompete a charitable industry that isn’t trying very hard, at least by our standards.

Normal people can save lives

The second meme was that a person with relatively small life-style changes, a normal person in the first world could do a shocking level of good, and it is good for people to do that.

My guess is that this meme started with Peter Singer’s drowning child paper, which argued that by spending tiny amounts of money and giving up some small creature comforts, one could literally save lives in the third world. And given that, it’s really really good when people decide to live that way; the more people who do, the more lives are saved. The more resources that are committed to these problems more good we can do.

This basic meme became the seed of Giving What We Can, for instance.

Note that in its initial form, this was something like a redistributive argument: We have so much more stuff than others who are in dire need that there’s a moral pressure (if not an obligation) to push for wealth transfers that help address the difference.

To summarize the difference between these ideas: One of these is about using the altruistic budget more effectively, and the other is about expanding the size of the altruistic budget.

Synergies

These memes are obviously related. They’re both claims about the outsized impact one can have via charitable donation (and career prioritization).

The claim that a first-worlder can save lives relatively cheaply means that there’s not an efficient market in saving lives.

And in my experience at least, the kind of analytical person that is inclined to think “One charity is going to be the most effective one. Which one is that?” also tends to be the kind of person that thinks, at some point in their life, “There are people in need who are just as real as I am, and the money I’m spending could be spent on helping them. I should give most of my money away.” There’s an “EA type”, and both of these memes are appealing to that type of person.

So in some ways these two memes are synergistic. Indeed, they’re synergistic enough that they fused together into the core of the Effective Altruism movement.

Tensions

But, as it turns out, those memes are also in tension with each other in important respects, in ways that played out in cultural conflicts inside of EA, as it grew.

These two memes encode importantly different worldviews, which have different beliefs about the constraints on doing more good in the world. To make an analogy to AI alignment, one of these views holds that the limiting factor is capability, how much of an influence we you can have on the world, and the other holds that the limiting factor is steering, the epistemology to identify outsized philanthropic opportunities.

Obviously, both of these can be constraints on your operation, and doing the most good will entail finding an optimal point on the pareto frontier of their tradeoff.

Implications of a “resources moved” frame

If the operating model is that the huge philanthropic gains are primarily redistributive, the primary limiting factor is the quantitative amount of resources moved. That tends to imply…

The Effective Altruism community that wants to be a mass-movement 

If the good part of EA is more people deciding to commit more of their resources to effective charities, you want to convert as many people as possible. One high priority is convincing as many people as possible to become EAs.  

Indeed this was the takeaway from Peter Singer’s TED talk in all the way back in 2013: You can do more good by donating to effective charities than you can by being a doctor (a generally regarded way of “helping people”), but you can do even better than that by converting more people to EA.

Branding matters

If you’re wanting to spread that core message, to get more people to donate more of their resources to effective charities, there’s incentive to reify the EA brand, to be the sort of thing that people can join, rather than an ad hoc collection of ideas and bloggers.

And branding is really important. If you want lots of people to join your movement, it matters a lot if the general public perception of your movement is positive.

Implications of a “calling the outsized opportunities frame”

In contrast, if you’re operating on a model where the philanthropic gains are the result of doing better and more careful analysis, the limiting constraint on the project is not (necessarily) getting more material resources to direct, but the epistemic capability to correctly pinpoint good opportunities. This tends to imply…

Unusually high standards of honesty and transparency are paramount

If you’re engaged in the intellectual project of trying to figure out how the world works, and how to figure out which interventions make things better, it is an indispensable feature of your epistemic community that it has strict honesty norms, that are firmly in Simulacrum level 1.  

You need to have expectations for what counts as honest that are closer to those of the scientific community, compared to the standards of marketing. 

We might take for granted that in many facets of the world, people are not ever really trying to be accurate (when making small talk or crafting slogans) and that people and organizations will put their best foot forward, highlighting their success and quietly downplaying failures.

But that normal behavior is counter to a collective epistemic process of putting forward and critiquing ideas, and learning from (failed) attempts to do stuff.

Furthermore, if you have a worldview that holds that the charity sector is incredibly inefficient, you’re apt to ask why that is. And part of the answer is that this kind of normal “covering one’s ass” / “putting forward a good face” behavior kills the accounting that causes charities to be effective in their missions. This background tends to make people more paranoid about these effects in their “let’s try to outcompete the charity sector” community.

“More people” is not an unadulterated good

Adding more people to a conversation does not, in the typical case, make the reasoning of that conversation more rigorous.

A small community of bloggers and intellectuals engaged in an extended conversation, aiming make progress together on some questions about how to most effectively get altruistic gains at scale, doesn’t necessarily benefit from more participants. 

And it definitely doesn’t benefit from the indiscriminate addition of participants. A small number of people will contribute to the extended conversation more than the communication and upfront enculturation cost that each new person imposes. 

These two world views give rise to two impulses in the egregore of EA: the faction that is in favor of professionalism  and the faction in vocal support of epistemics and integrity.

We see this play out everytime someone posts something arguably unseemly on the EA forum, and someone comments, “I think it was bad to post this, it makes EA look bad and has a negative impact in expectation.”

And I think the tension between these impulses goes a long way towards explaining why EA seems so much less promising to me now than it did 5 years ago.
I have more to say here, about how the incentive to do the hard work of rigorous thinking things through and verifying lines of argument is somewhat self-cannibalizing, but I don’t feel like writing that all right now, so I’m shipping this as a post.

Request for parellel conditional-market functionality

In responses to James’ plan for a manifold dating site, I just wrote tho following comment.

I think this needs a new kind of market UI, to setup multiple conditional markets in parallel. I think this would be useful in general, and also the natural way to do romance markets, in particular.

What I want is for a user to be able to create a master (conditional) prompt that includes a blank to be filled in. eg “If I go on a date with ____, will we end up in a relationship 2 months later?” or “If I read ____ physics textbook, will I be impressed with it?” or “Will I think the restaurant ____, is better than the Butchers Son, if I eat there?” The creator of this master question can include resolution details in the description, as always.

Then other users can come and submit specific values of for the blank. In these cases, they suggest people, physics textbooks, or restaurants.

However (and this is the key thing that makes this market different from the existing multiple choice markets), every suggestion becomes it’s own market. Each suggestion gets a price between 100% and 0%, rather than all of the suggestions in total having adding up to a probability of 100%.

After all, it’s totally possible that someone would end up in a relationship with Jenny (if they end up going on a date with Jenny) and end up in a relationship with George (if they go on a date with George). And it’s likely that there there are multiple restaurants that one would like better than the Butcher’s Son. There’s no constraint that all the answers have to sum to 100%.

(There are other existing markets that would make more sense with this format. Aella’s one-night stand market for one, or this one about leading AI labs. It’s pretty common for multiple choice questions to not need to sum to 100% probability, because multiple answers can be correct.)

Currently, you can create a bunch of conditional markets yourself. But that doesn’t work well for romance markets in particular, for two reasons.

1. Most of the value of these markets is in discovery. Are there people who the market thinks that I should go on a date with, who I’ve never met?
2. It is very socially forward to create a market “Will I be in a relationship with [Jenny], if we go on one date?” That means that I reveal that I’m thinking about Jenny enough to make a market, to Jenny, and to all the onlookers, which could be embarrassing to her. It’s important that the pairings are suggested by other people, and mixed in with a bunch of other suggestions, instead of highlighted in a single top-level market. Otherwise it seems like this is pushing someone’s personal life into a public limelight too much.

If this kind of market UI existed, I would immediately create a “If Eli goes on a date with ____, will the be in a relationship 3 months later?”, and a link to my existing dating doc, and a large subsidy (we’d have to think about to allocate subsidies across all the markets in a set).

In fact, if it were possible and legal to do this with real money, I would probably prefer spending $10,000 subsidizing a set of real money prediction markets of this form, compared to would spending $10,000 on a matchmaker. I just expect the market (and especially “the market” when it is composed of people who are one or two degrees removed from people that I might like to date), to be much better at suggesting successful pairings.

A letter to my 20 year old self

If I could send some advice back in time, to myself when I was 20 years old, this is a lot of what I would say. I think almost all of this is very idiosyncratic to me, and the errors that I, personally, am inclined towards. I don’t think that most 20 year olds that are not me should take these points particularly seriously, unless they recognize themselves in it.

[See also First conclusions from reflections on my life]

  1. Order your learning

You want to learn all skills, or at least all the awesome and useful ones. This is completely legitimate. Don’t let anyone tell you that you shouldn’t aim for that (including with words like “specialization” or “comparative advantage”.)

But because of this, every time you encounter something awesome, you respond by planning to make the practice of it part of your life in the short term. This is a mistake. Learning most things will require either intense bouts of focusing on only that one thing for (at least small numbers of) days at a time, or consistent effort over weeks or months. 

If every time you encounter some skill that seems awesome or important, you resolve to learn it, this dilutes your focus, which ends up with you not learning very much at all. Putting a surge of effort into something and then not coming back to it for some weeks is almost a total waste of that effort—you’ll learn almost nothing permanent from that.

The name of the game is efficiency. You should think of it like this:

Your skill and knowledge, at any given time, represents a small volume in a high dimensional space. Ultimately you want to expand in all or almost all directions. There’s no skill that you don’t want, eventually. But the space is very high dimensional and infinite, so trying to learn everything that crosses your path won’t serve you that well. You want to order your learning.

Your goal should be to plot a path, a series of expansions in this high dimensional space, that results in expanding the volume as quickly as possible. Focus on learning the things that will make it easier and faster to continue to expand, along the other dimensions, instead of focusing on whatever seems cool or salient in the moment.

[added:] More specifically, you should be willing to focus on doing one thing at a time (or one main thing, with a one or at most, two side projects). Be willing to take on a project, ideally but not necessarily involving other people, and make it your full time job for at a month. You’ll learn more and make more progress when you’re not dividing your efforts. You won’t loose nearly as much time in the switching costs, because you won’t have to decide what to do next: there will be a clear default. And if you’re focusing on one project at a time, it’s much easier to see if you’re making progress. You’ll be able to tell much faster if you’re spinning your wheels doing something that feels productive, but isn’t actually building anything. Being able to tell that you failed at a timeboxed goal means that you can notice and adapt.

A month might feel like a long time, to put aside all the other things you want to learn, but it’s not very long in the grand scheme of things. There have been many months since I was 20, and I would be stronger now, if I had spent more of them pushing hard on some specific goal, instead of trying to do many good things and scattering my focus.

You want to be a polymath; but the way to polymathy is not trying to do everything all at once: it’s mostly going intensely, on several different things, in sequence.

  1. Learn technical skills

In particular, prioritize technical skills. They’re easier to learn earlier in life, and I wish I had a stronger grounding in them now.

First and foremost, learn to program. Being able to automate processes, and build simple software tools for yourself is a superpower. And it is a really great source of money.

Then, learn calculus, linear algebra, differential equations, microeconomics, statistics, probability theory, machine learning, information theory, and basic physics. [Note that I’ve so far only learned some of these myself, so I am guessing at their utility].

It would be a good use of your time if you dropped everything else and made your only priority in the first quarter of college to do well in IBL calculus. This would be hard, but I think you would make substantial steps towards mathematical maturity if you did that.

In general, don’t bother with anything else in college, except learning technical subjects. I didn’t find much in the way of friends or connections there, and you’ll learn the non-technical stuff fine on your own.

The best way to learn these is to get a tutor, and walk through the material with the tutor on as regular a basis as you can afford.

  1. Prioritize money 

You’re not that interested in money. You feel that you don’t need much in the way of “stuff” to have an awesome life. You’re correct about that. Much more than most of the people around you, you don’t want or need “nice things”. You’re right to devalue that sort of thing. You’ll be inclined to live frugally, and that has served me very well.

However, you’re missing that money can be converted into learning. Having tens or hundreds of thousands of dollars is extraordinarily helpful for learning pretty much anything you care to learn. If nothing else, most subjects can be learned much faster by talking with a tutor. When you have money, if there’s anything you want to learn, you can just hire someone who knows it to teach you how to do it, or to do it with you. This is an overpowered strategy.

It is a priority for you to get to the point that you’re making (or have saved) enough money that you feel comfortable spending hundreds of dollars on a learning project.

Combining 1, 2, 3, the thing that I recommend that you do now is drop almost everything and learn to become a good programmer. Your only goal for the next few months should be 1) to have enough money for rent and food, and 2) to become a good enough programmer that you can get hired for it, as quickly as you can. Possibly the best way to do this is to do a coding boot camp, instead of self-teaching. You should be willing to put aside other cool things that you want to do and learn, for only a couple of months, to do this.

Then get a job as a software engineer. You should be able to earn small hundreds of thousands of dollars a year with a job like that, while still having time to do other stuff you care about in your off hours. If you live frugally, you can work for 2.5 years and come away with a small, but large enough (eg >100k) nest egg for funding all the other skills that you want to learn.

(If you’re still in college, staying to do IBL first, and then focusing on learning programing isn’t a bad idea. It might be harder to get mathematical maturity, in particular, outside of college.)

  1. Make things / always have a deliverable

I’ve gained much much more skill over the course of projects where I was just trying to do something, than from the sum of all my explicit learning projects. Mostly you learn skills as a side effect of doing things. This just works better than explicit learning projects. 

This also means that you end up learning real skills, instead of the skills that seem abstractly useful or cool from the outside, many of which turn out to have not much relevance to real problems. Which is fine; you can pursue things because they’re cool. But very often, what is most useful and relevant are pieces that are too mundane to come to mind, and doing real things reveals them. Don’t trust your abstract model of what elements are useful or relevant or important or powerful, too much. Better to let your learning be shaped to the territory directly, in the course of trying to do specific things.

The best way to learn is to just try to do something that you’re invested in, for other reasons, and learn what you need to know to succeed along the way. Find some software that you wish existed, that you think would be useful to you, and just try and build it. Run a conference. Take some work project that seems interesting and knock it out of the park. 

Try to learn as much as you can this way.

In contrast, I’ve spent a huge amount of time thinking over the years that didn’t create any value at all. If I learned something at the time, I soon forgot it, and it is completely lost ot me now. This is a massive waste. 

So your projects should always have deliverables. Don’t let yourself finish or drop a project, especially a learning project, until you have produced some kind of deliverable. 

A youtube video of yourself explaining some new math concept. A lecture for two friends. Using a therapy technique with a real client.

A blog post jotting down what you learned, or summarizing your thoughts on a domain is the minimum viable deliverable. If nothing else, write a blog post for everything that you spend time on, to capture the the value of your thinking for others, and for yourself later.

Don’t wait to create a full product at the end. Ship early, ship often. Create intermediate deliverables, capturing your intermediate progress, at least once a day. Write / present about your current thoughts and understanding, including your open confusions. (I’ve often gotten more clarity about something in the process of writing up my confusions in a blog post).

The deliverable can be very rough. But it shouldn’t be just your personal notes. If you’re writing a rough blog post, write it as if for an audience beyond yourself. That will force you to clarify your thoughts and clearly articulate the context much more than writing a personal journal entry. In my experience, the blog posts that I write like this are usually more helpful for my future self than the personal journal entries are.

The rule should be that someone other than you, in principle, could get value from it. A blog post or a recorded lecture, that no one reads, but someone could read and find interesting counts. The same thing, but on a private google drive, doesn’t count. (Even better, though, is if you find just one person who actually gets value out of it. Make things that provide value to someone else.)

Relatedly, when you have an idea for a post or an essay, write it up immediately, while the ideas are alive and energizing. If you wait, they’ll go stale and it is often very hard to get them back. There are lots of thoughts and ideas that I’ve had, which are lost forever because I opted to wait a bit on writing them down. This post is itself the result of some thoughts that I had while listening to a podcast, which I made a point to right up while the thoughts were alive in me.

  1. Do the simple thing first

You’re going to have many clever ideas for how to do things better than the default. I absolutely do not want to discourage you in that.

But it will behoove you to start, by doing the mundane, simple thing. Try the default first, then do optimizations and experiments on top of that, and feel free to deviate from the default, when you find something better.

If you have some fancy idea for how to use spaced repetition systems to improve your study efficiency, absolutely try that. But start by doing the simple thing of sitting down, reading the textbook, and doing the exercises, and then apply your fancy idea on top of that.

You want to get a baseline to compare against. And oftentimes, clever tricks are less important than just putting in the hours doing the work, and so you want to make sure to get started doing the work as soon as possible, instead of postponing it until after you’ve developed a clever system. Even if your system is legitimately clever, if the most important thing is doing the hard work, you’ll wish you started earlier.

You’re sometimes going to be more ambitious than the structures around you expect of you. That’s valid. But start with the smaller goals that they offer, and exceed them, instead of trying to exceed them in one fell swoop.

When you were taking Hebrew in high school, you were unimpressed by the standards of the class and held yourself higher than them. For the first assignment, you were to learn the first list of vocabulary words from the book, for the next week. But you felt that you were better than that, and resolved to study all the vocab in the whole book (or at least a lot of it) in that period, instead.

But that was biting off more than you could easily chew, and (if I remember correctly), when you came back the next week, you had not actually mastered the first vocab list. You would have done better to study that list first, and then move on to the rest, even if you were going to study more than was required.

I’ve fallen into this trap more than once. “Optimizing” my “productivity” with a bunch of clever hacks, or ambitious targets, which ultimately mask the fact that my output is underperforming very mundane work habits, for instance. 

You might want to work more and harder than most people, but start by sticking to a regular workday schedule, with a weekend, and then you can adjust it, or work more than that, from there.

Don’t fall into the trap of thinking that the simple thing that everyone else is doing is beneath you, since you’re doing a harder or bigger thing than that. Do the simple thing first, and then do more or better.

I’m sure there’s more to say, but this is what I was pressing on me last night in particular.