80,000 Hours recommends undergraduates to pursue these options to build flexible career capital:
We think it’s reasonable to aim for the most fundamental, quantitative option you can do i.e. one of these in the following order: mathematics, economics, computer science, physics, engineering, political science / chemistry / biology (the last three are roughly equal). If you want to focus on something non-quantitative, then consider focusing on developing great written communication skills in philosophy, history or English. If you want to do something more applied, then maybe business or accounting. A good combination seems to be a major in a quantitative subject and a minor in a subject that requires great written skills (e.g. major in maths and minor in philosophy). We say this because people who can both understand quantitative topics and communicate clearly seem to be highly in-demand in all kinds of areas.
80, 000 Hours' latest survey indicates that the most needed skills/experience in the EA community are these:
EA organisation leaders said experience with operations or management, and generalist researchers are what their organisations will need most of over the next five years. They said the community as a whole will most need more government and policy experts, operations experience, machine learning/AI technical expertise, and skilled managers.
80,000 Hours has also claimed that these skills make people most employable:
According to this analysis, the most valuable skills could be summed up as “leadership” skills, such as: 1. Analysis and learning, including judgement, critical thinking, complex problem solving, active learning. 2. Management, including time management, monitoring performance, coordinating people. 3. Social skills, including active listening, spoken communication, social perceptiveness.
Suppose someone already implemented advice given here, e.g. they chose an impressive quantitative program, minored in something non-quantitative to practice writing, and organized a student society or started some other project. What courses would you recommend her/him to take to develop broadly most useful skills for EA organizations slightly more directly?
Of course, it depends on the specific goal of the person (for example, whether she/he wants to do research at GiveWell or Global Priorities Institute), but let's continue with the theme of keeping options open here. For example, would you recommmend this person to take microeconomics, courses about cost-effectiveness assessment, or programming for data science? What would you recommend?
I think more people should be studying statistics, machine learning, and data science, especially Bayesian methods and causal inference. Not only do these skills offer a chance to contribute to AI safety, they're also critical for evaluating scientific papers (important for any field given the replication crisis), doing predictive modeling, and generally thinking in a data-driven and evidence-based way. Math is apparently 80k's #1 recommendation, but when I was a student, I went to an event where math majors talked about their experiences in industry. Most of them said they didn't use the math they learned much and they wish they had studied more statistics. So I would suggest applied math with a statistics emphasis.