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:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 (lastname@thisdomain.com) if you have more ideas for getting the most out of grad school!
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.
Agree. The lab work in CS is also large, though it comes in huge blocks rather than on a steady schedule.