Deliberate Grad School

Among my friends interested in rationality, effective altruism, and existential risk reduction, I often hear: "If you want to have a real positive impact on the world, grad school is a waste of time. It's better to use deliberate practice to learn whatever you need instead of working within the confines of an institution."

While I'd agree that grad school will not make you do good for the world, if you're a self-driven person who can spend time in a PhD program deliberately acquiring skills and connections for making a positive difference, I think you can make grad school a highly productive path, perhaps more so than many alternatives. In this post, I want to share some advice that I've been repeating a lot lately for how to do this:

  1. Find a flexible program. PhD programs in mathematics, statistics, philosophy, and theoretical computer science tend to give you a great deal of free time and flexibility, provided you can pass the various qualifying exams without too much studying. By contrast, sciences like biology and chemistry can require time-consuming laboratory work that you can't always speed through by being clever.

     

  2. Choose high-impact topics to learn about. AI safety and existential risk reduction are my favorite examples, but there are others, and I won't spend more time here arguing their case. If you can't make your thesis directly about such a topic, choosing a related more popular topic can give you valuable personal connections, and you can still learn whatever you want during the spare time a flexible program will afford you.

     

  3. Teach classes. Grad programs that let you teach undergraduate tutorial classes provide a rare opportunity to practice engaging a non-captive audience. If you just want to work on general presentation skills, maybe you practice on your friends... but your friends already like you. If you want to learn to win over a crowd that isn't particularly interested in you, try teaching calculus! I've found this skill particularly useful when presenting AI safety research that isn't yet mainstream, which requires carefully stepping through arguments that are unfamiliar to the audience.

     

  4. Use your freedom to accomplish things. I used my spare time during my PhD program to cofound CFAR, the Center for Applied Rationality. Alumni of our workshops have gone on to do such awesome things as creating the Future of Life Institute and sourcing a $10MM donation from Elon Musk to fund AI safety research. I never would have had the flexibility to volunteer for weeks at a time if I'd been working at a typical 9-to-5 or a startup.

     

  5. Organize a graduate seminar. Organizing conferences is critical to getting the word out on important new research, and in fact, running a conference on AI safety in Puerto Rico is how FLI was able to bring so many researchers together on its Open Letter on AI Safety. It's also where Elon Musk made his donation. During grad school, you can get lots of practice organizing research events by running seminars for your fellow grad students. In fact, several of the organizers of the FLI conference were grad students.

     

  6. Get exposure to experts. A top 10 US school will have professors around that are world-experts on myriad topics, and you can attend departmental colloquia to expose yourself to the cutting edge of research in fields you're curious about. I regularly attended cognitive science and neuroscience colloquia during my PhD in mathematics, which gave me many perspectives that I found useful working at CFAR.

     

  7. Learn how productive researchers get their work done. Grad school surrounds you with researchers, and by getting exposed to how a variety of researchers do their thing, you can pick and choose from their methods and find what works best for you. For example, I learned from my advisor Bernd Sturmfels that, for me, quickly passing a draft back and forth with a coauthor can get a paper written much more quickly than agonizing about each revision before I share it.

     

  8. Remember you don't have to stay in academia. If you limit yourself to only doing research that will get you good post-doc offers, you might find you aren't able to focus on what seems highest impact (because often what makes a topic high impact is that it's important and neglected, and if a topic is neglected, it might not be trendy enough land you good post-doc). But since grad school is run by professors, becoming a professor is usually the most salient path forward for most grad students, and you might end up pressuring yourself to follow that standards of that path. When I graduated, I got my top choice of post-doc, but then I decided not to take it and to instead try earning to give as an algorithmic stock trader, and now I'm a research fellow at MIRI. In retrospect, I might have done more valuable work during my PhD itself if I'd decided in advance not to do a typical post-doc.

That's all I have for now. The main sentiment behind most of this, I think, is that you have to be deliberate to get the most out of a PhD program, rather than passively expecting it to make you into anything in particular. Grad school still isn't for everyone, and far from it. But if you were seriously considering it at some point, and "do something more useful" felt like a compelling reason not to go, be sure to first consider the most useful version of grad that you could reliably make for yourself... and then decide whether or not to do it.

Please email me ([email protected]) if you have more ideas for getting the most out of grad school!

Comments

sorted by
magical algorithm
Highlighting new comments since Today at 8:12 AM
Select new highlight date
Rendering 50/155 comments  show more

PhD programs in mathematics, statistics, philosophy, and theoretical computer science tend to give you a great deal of free time and flexibility, provided you can pass the various qualifying exams without too much studying.

Bolding the parts to which I object.

I have never seen anyone in a rigorous postgraduate program who had a lot of free time and could pass their quals without large amounts of studying.

Of course, I could just be, like magic, on the lower part of the intelligence curve for graduate school, but given that my actual measured IQ numbers are pretty in-the-middle for scientific academia (I won't tell what they are, though), and given that almost everyone else says they have little free time and have to study hard in graduate school, I'm inclined to believe the bolded phrases only accurately describe a narrow slice of lucky individuals.

Are you talking about free time pre- or post-quals? And do you include work that goes towards your thesis but that you "have" to do (e.g. for a conference or internal deadline) as free time or non-free time?

My experience (and I would guess many of my labmates, though I don't know for sure) is that quals are really easy to pass, you spend at most 2 weeks of your life studying for them, and otherwise you're just doing research plus a few classes. Stanford is an outlier in that it has particularly few class requirements compared to other top CS departments, but it seemed like MIT grad students also often started doing research fairly early on, from my perspective as an undergrad there.

Depending on your funding situation, your actual time spent doing research may be more or less beholden to what grants your advisor has to do work towards. I'm on a fellowship and so can do whatever I want, the only consequences being that if my research after 5 years is uninteresting then I'll have trouble getting academic jobs.

I've only gotten up to doing an MSc (currently volunteering for Vikash Masinghka in my Copious Free Time), but I do know a hell of a lot of academics.

From my (second-hand) knowledge, easy quals are an artifact of something very like economic privilege: your school is very prestigious and doesn't need to cull its grad-student herds as much as others, so quals are allowed to be easy. In other places, quals are used to evict many grad-students from their PhD program because resources are more scarce.

but it seemed like MIT grad students also often started doing research fairly early on, from my perspective as an undergrad there.

I don't know anywhere where grad-students don't start doing research as early as possible. Do some programs really involve whole years of just classes?

A lot of it is historical accidents + inertia. When I was a greenhorn at UCLA, CS quals (the WQE, aka "the wookie") were two 5 hour tests (on two consecutive days) covering all of CS (e.g. networking, databases, AI, theory, systems, everything). They were not easy at all. At some point it was realized this was stupid, and neither teaches nor prepares one for research, and washes out good people. So it was changed.

UCLA math quals are .. formidable.

In Berkeley CS there are enough course requirements that I don't think people do serious research until their second year (although I'm sure they do some preliminary reading / thinking in year one).

It's striking how much value there is in academia that I didn't notice, and that a base-level rational person would've noticed if they'd asked "what are the main blind spots of the rationality community, and how can I steelman the opposing positions?". Not a good sign about me, certainly.

Also, is that your actual email address?

I have been talking about this very issue for ages here on LW. "Rationalists" (the tribe, not the ideal platonic type) share a ton of EY's biases, including anti-academic sentiment.

It's striking how much value there is in academia that I didn't notice, and that a base-level rational person would've noticed if they'd asked "what are the main blind spots of the rationality community, and how can I steelman the opposing positions?".

Well, to bloat my own ego, one of my most consistently banged-on themes has been, "HEY ACADEMIA BASICALLY TELLS US THINGS FOR FREE!"

I have some questions about step 1 (find a flexible program):

My understanding is that there are two sources of inflexibility for PhD programs: A. Requirements for your funding source (e.g. TA-ing) and B. Vague requirements of the program (e.g. publish X papers). I'm excluding Quals, since you just have to pass a test and then you're done.

Elsewhere in the comments, someone wrote:

"Grad school is free. At most good PhD programs in the US, if you get in then they will offer you funding which covers tuition and pays you a stipend on the order of $25K per year. In return, you may have to do some work as a TA or in a professor's lab."

So, there are two types of jobs you can have to fund your PhD (TA-ing and being a RA/Research Assistant to a professor). How time-consuming is TA-ing generally? I imagine it varies based on the school/class. How do you find a TA-ing gig that isn't time consuming? Can you generally TA during your entire PhD? I think I vaguely recall a university that only would let you TA for so many semesters.

You could also fund your PhD by getting a fellowship. Philip Guo has written about applying for the NSF, NDSEG, Hertz fellowships. I'm poorly calibrated about how hard it is to get one of these fellowships. I've also heard that certain schools will offer fellowships to some of their students. How hard are these to get relative to the fellowships mentioned above? There are ~33K science PhDs awarded each year. I wonder what distinguishes the ~4% who get fellowships from the median science PhD student.

Let's say that you were really frugal and/or financially independent already. My impression is that many schools would still require you to TA in order to have your tuition waved.

Let’s assume you have the financial aspect of your PhD taken care of (e.g. You have an easy/enjoyable TA job). What other requirements are there other than passing Quals? Could I read interesting books indefinitely until I find something interesting to publish?

I'd like to believe that achieving step 1 is possible, but as eli_sennesh pointed out, this is hard.

How hard your quals are depends on how well you know your field. I went to a top 5 physics program, and everyone passed their qualifying exams, roughly half of whom opted to take the qual their first year of grad school. Obviously, we weren't randomly selected though.

Fellowships are a crapshoot that depend on a lot of factors outside your control, but getting funding is generally pretty easy in the sciences. When you work as an "RA" you are basically just doing your thesis research. TAing can be time consuming, but literally no one cares if you do it poorly, so it's not high pressure.

But this is a red flag:

Let’s assume you have the financial aspect of your PhD taken care of (e.g. You have an easy/enjoyable TA job). What other requirements are there other than passing Quals? Could I read interesting books indefinitely until I find something interesting to publish?

That isn't how research works, at least in the sciences. Research is generally 1% "big idea" and 99% slowly grinding it out to see if it works. Your adviser, if he/she is any good, will help you find a big idea that you can make some progress on and you'll be grinding it out every week and meeting with your adviser or other collaborators if you've gotten stuck.

That said, a bad adviser probably won't pay any attention to you. So you can do whatever you want for about 7 years until people realize you've made no progress and the wheels come off the bus (at which point they'll probably hand you a masters degree and send you on your way).

literally no one cares if you do [TAing] poorly

I have heard rumours that students are actually people, and that they care about the quality of the teaching they receive.

You'd think so, but office hours and TA sections without attendance grades are very sparsely attended.

How much TAing is allowed or required depends on your field and department. I'm in a statistics department that expects PhD students to TA every semester (except their first and final year). It has taken me some effort to weasel out of around half of the teaching appointments, since I find teaching (especially grading) quite time-consuming, while industry internships both pay better and generate research experience. On the other hand, people I know from the CS department only have to teach 1-2 semesters during their entire PhD.

I am of the opinion that if you do grad school and you don't attach yourself to a powerful and wise mentor in the form of your academic adviser, you're doing it wrong. Mentorship is a highly underrated phenomenon among rationalists.

I mean, if you're ~22, you really don't know what the hell you're doing. That's why you're going to grad school, basically. To get some further direction in how to cultivate your professional career.

If you happen to have access to an adviser who won a Nobel or whose adviser won a Nobel, they would make a good choice. The implicit skills involved in doing great work are sometimes passed down this way. The adviser won't even necessarily know which of their habits are the good ones. I'm thinking specifically of a professor I knew whose adviser was a Nobel laureate, who would take his students out for coffee almost every day. They would casually talk shop while getting coffee. This professor's students were generally well above average in their research accomplishments.

I mostly agree, but would add two caveats.

Relying too much on getting one very specific advisor is risky. Most advisors are middle-aged (or outright old), especially those with Nobel Prizes, and they do sometimes die or move away with little notice. If that happens, universities can be very bad about finding replacements (let alone comparably brilliant replacements) for any students cast adrift.

Also, an adviser's personality & schedule are as important as their research skills: a Nobel Prize winner who's usually away giving speeches, and is a raging, neglectful arsehole when they are around, is likely to be more of a hindrance than a help in getting a PhD. Put like that, what I just wrote is obvious, but I can imagine it being the kind of thing potential applicants would overlook.

I think there'd be value in just listing graduate programs in philosophy, economics, etc., by how relevant the research already being done there is to x-risk, AI safety, or rationality. Or by whether or not they contain faculty interested in those topics.

For example, if I were looking to enter a philosophy graduate program it might take me quite some time to realize that Carnegie Melon probably has the best program for people interested in LW-style reasoning about something like epistemology.

I think it depends more on specific advisors than on the university. If you're interested in doing AI safety research in grad school, getting in touch with professors who got FLI grants might be a good idea.

PhD programs in mathematics, statistics, philosophy, and theoretical computer science tend to give you a great deal of free time and flexibility, provided you can pass the various qualifying exams without too much studying.

Economics also has good opinion among the EA/rationality crowd: