Today I was appointed the new Executive Director of Singularity Institute.
Because I care about transparency, one of my first projects as an intern was to begin work on the organization's first Strategic Plan. I researched how to write a strategic plan, tracked down the strategic plans of similar organizations, and met with each staff member, progressively iterating the document until it was something everyone could get behind.
I quickly learned why there isn't more of this kind of thing: transparency is a lot of work! 100+ hours of work later, plus dozens of hours from others, and the strategic plan was finally finished and ratified by the board. It doesn't accomplish much by itself, but it's one important stepping stone in building an organization that is more productive, more trusted, and more likely to help solve the world's biggest problems.
I spent two months as a researcher, and was then appointed Executive Director.
In further pursuit of transparency, I'd like to answer (on video) submitted questions from the Less Wrong community just as Eliezer did two years ago.
The Rules
1) One question per comment (to allow voting to carry more information about people's preferences).
2) Try to be as clear and concise as possible. If your question can't be condensed into one paragraph, you should probably ask in a separate post. Make sure you have an actual question somewhere in there (you can bold it to make it easier to scan).
3) I will generally answer the top-voted questions, but will skip some of them. I will tend to select questions about Singularity Institute as an organization, not about the technical details of some bit of research. You can read some of the details of the Friendly AI research program in my interview with Michael Anissimov.
4) If you reference certain things that are online in your question, provide a link.
5) This thread will be open to questions and votes for 7 days, at which time I will decide which questions to begin recording video responses for.
I might respond to certain questions within the comments thread and not on video; for example, when there is a one-word answer.
I have noticed increasing numbers of very talented math and CS folk expressing interest or taking actions showing significant commitment. A number of them are currently doing things like PhD programs in AI. However, there hasn't been much of a core FAI team and research program to assimilate people into. Current plans are for Eliezer to switch back to full time AI after his book, with intake of more folk into that research program. Given the mix of people in the extended SIAI community, I am pretty confident that with abundant funding a team of pretty competent researchers (with at least some indicators like PhDs from the top AI/CS programs, 1 in 100,000 or better performance on mathematics contests, etc) could be mustered over time, based on people I already know.
I am less confident that a team can be assembled with so much world-class talent that it is a large fraction of the quality-adjusted human capital applied to AGI, without big gains in recruiting (e.g. success with the rationality book or communication on AI safety issues, better staff to drive recruiting, a more attractive and established team to integrate newcomers, relevant celebrity endorsements, etc). The Manhattan Project had 21 then- or future Nobel laureates. AI, and certainly FAI, are currently getting a much, much smaller share of world scientific talent than nukes did, so that it's easier for a small team to loom large, but it seems to me like there is still a lot of ground to be covered to recruit a credibly strong FAI team.
Thanks. You didn't answer my questions directly, but it sounds like things are proceeding more or less according to expectations. I have a couple of followup questions.
At what level of talent do you think an attempt to build an FAI would start to do more (expected) good than harm? For simplicity, feel free to ignore the opportunity cost of spending financial and human resources on this project, and just consider the potential direct harmful effects, like accidentally creating an UFAI while experimenting to better understand AGI, or building a would-be FAI ... (read more)