Hi! I'm Cullen. I've been a Research Scientist in the Policy team at OpenAI since August. I also am a Research Affiliate at the Centre for the Governance of AI at the Future of Humanity Institute, where I interned in the summer of 2018.
I graduated from Harvard Law School cum laude in May 2019. There, I led the Harvard Law School and Harvard University Graduate Schools Effective Altruism groups. Prior to that, I was an undergraduate at the University of Michigan, where I majored in Philosophy and Ecology & Evolutionary Biology. I'm a member of Giving What We Can, One For The World, and Founder's Pledge.
Some things I've been thinking a lot about include:
- How to make sure AGI benefits everyone
- Law and AI development
- Law's relevance for AI policy
- Whether law school makes sense for EAs
- Social justice in relation to effective altruism
I'll be answering questions periodically this weekend! All answers come in my personal capacity, of course. As an enthusiastic member of the EA community, I'm excited to do this! :D
[Update: as the weekend ends, I will be slower replying but will still try to reply to all new comments for a while!]
I’m not involved in hiring at OpenAI, so I’m going to answer more in the spirit of “advice I would give for people interested in pursuing a career in EA AI policy generally.”
In short, I think actually trying your hand at the research is probably more valuable on the margin, especially if it yields high-quality research. (And if you discover it’s not a good fit, that’s valuable information as well.) This is basically what happened to me during my FHI internship: I found out that I was a good fit for this work, so I continued on in this path. There are a lot of very credentialed EAs, but (for better or worse), many EA AI policy careers take a combination of hard-to-describe and hard-to-measure skills that are best measured by actually trying to do it. Furthermore, there is unfortunately a managerial bottleneck in this space: there are far more people interested in entering it than people that can supervise potential entrants. I think it can be a frustrating space to enter; I got very lucky in many ways during my path here.
So, if you can’t actually try the research in a supervised setting, cultivating general skills or doing adjacent research (e.g., general AI policy) is a good step too. There are always skills I wish I had (and which I am fortunate to get to cultivate at OpenAI during Learning Day). Some of the stuff I studied during Learning Day which might guide your own skill cultivation include: