In an iconic scene from the original Planet of the Apes, Charlton Heston learns that he's been on Earth all along, thousands of years after...

First up this month, I spoke with Helen Toner, who recently helped found the Center for Security and Emerging Technology — a DC think tank which gives policymakers analysis of the potential security impacts of new technologies. Helen and I also discussed her decision to spend a year studying in China, to better understand the role it might play in the 21st century. Take a look if you're interested in international relations, security, technological progress, or China: The new 30-person research group in DC investigating how emerging technologies could affect national security Second, our newest staff member, Arden Koehler, substantially rewrote our review of doing a philosophy PhD with the aim of going into academia. We still have significant reservations about the path, but ended up more optimistic than when we last considered it in 2015. Many of the issues she covers are relevant to academic careers as a whole, and not just those in philosophy. If you're considering any research career, it's probably worth taking a look: Philosophy is one of the most competitive grad programs. Is it worth it, if you want to use ideas to change the world? Third, I interviewed the machine learning researcher and polymath Paul Christiano for a second time. His day job is improving the robustness and reliability of ML systems at OpenAI, so I got a substantial update on how that's going. But we also found time to have some fun discussions about whether divestment works, the possibility of leaving a message for future civilizations, and how poor office ventilation might be making us all a bit dumber. Take a look if you're interested in science and technology, thinking about the long-term future, or taking care of your brain: Paul Christiano on sending a message to the future, the impact of increasing compute, & how CO2 could be affecting your brain Finally, I threw together a model to try to understand how it is that organisations often say their top applicant for a vacancy is especially good, and not easily replaceable — even when hundreds of other people are applying for the same position. In short, this is actually what you would expect if the distribution of productivity has high variance or a 'fat tail' among the top performers. We don't know if this is the actual explanation, and like all models it has a number of problems, but if you like economics or statistics you might find it thought-provoking nonetheless: How replaceable are the top candidates in large hiring rounds? Why the answer flips depending on the distribution of applicant ability I've uploaded all the spreadsheets I used for that work so you can have a play with them, if that's your kind of thing. Have a great week, Rob In an iconic scene from the original Planet of the Apes, Charlton Heston learns that he's been on Earth all along, thousands of years after humanity has destroyed itself in a nuclear war. Are there any helpful messages we could leave to future civilizations on Earth, should our own disappear? That's one of a number of speculative questions I tackle with computer scientist Paul Christiano in my interview with him this month: Should we leave a helpful message for future civilizations, just in case humanity dies out? 80,000 Hours is a non-profit that provides research and support to help people switch into careers that effectively tackle the world's most pressing problems. Read about our key ideas, subscribe to our podcast, find a job on our job board, and find ways to meet others working to have an impact.