The reason why I would recommend people get a machine learning PhD, if they’re in a position to do so, is that this is where we are currently the most talent constrained. So, at DeepMind, and for the technical AI safety team, we’d love to hire more people who have a machine learning PhD or equivalent experience, and just get them to work on AI safety.
Want to help steer the 21st century’s most transformative technology? First complete an undergrad degree in computer science and mathematics. Prioritize harder courses over easier ones. Publish at least one paper before you apply for a PhD. Find a supervisor who’ll have a lot of time for you. Go to the top conferences and meet your future colleagues. And finally, get yourself hired.
That’s Dr Jan Leike’s advice on how to join him as a Research Scientist at DeepMind, the world’s leading AI team.
Jan is also a Research Associate at the Future of Humanity Institute at the University of Oxford, and his research aims to make machine learning robustly beneficial. His current focus is getting AI systems to learn good objective functions in cases where we can’t easily specify the outcome we actually want.
How might you know you’re a good fit for this kind of research?
Jan says to check whether you get obsessed with puzzles and problems, and find yourself mulling over questions that nobody knows the answer to. To do research in a team you also have to be good at clearly and concisely explaining your new ideas to other people.
We also discuss:
- Where do Jan’s views differ from those expressed by Dario Amodei in episode 3?
- Why is AGI alignment one of the world’s most pressing problems?
- Common misconceptions about artificial intelligence
- What are some of the specific things DeepMind is researching?
- The ways in which today’s AI systems can fail
- What are the best techniques available today for teaching an AI the right objective function?
- What’s it like to have some of the world’s greatest minds as coworkers?
- Who should do empirical research and who should do theoretical research
- What’s the DeepMind application process like?
- The importance of researchers being comfortable with the unknown.
The 80,000 Hours podcast is produced by Keiran Harris.