Series: How to Purchase AI Risk Reduction
A key part of SI's strategy for AI risk reduction is to build toward hosting a Friendly AI development team at the Singularity Institute.
I don't take it to be obvious that an SI-hosted FAI team is the correct path toward the endgame of humanity "winning." That is a matter for much strategic research and debate.
Either way, I think that building toward an FAI team is good for AI risk reduction, even if we decide (later) that an SI-hosted FAI team is not the best thing to do. Why is this so?
Building toward an SI-hosted FAI team means:
- Growing SI into a tighter, larger, and more effective organization in general.
- Attracting and creating people who are trustworthy, altruistic, hard-working, highly capable, extremely intelligent, and deeply concerned about AI risk. (We'll call these people "superhero mathematicians.")
Both (1) and (2) are useful for AI risk reduction even if an SI-hosted FAI team turns out not to be the best strategy.
This is because: Achieving part (1) would make SI more effective at whatever it is doing to reduce AI risk, and achieving part (2) would bring great human resources to the cause of AI risk reduction, which will be useful to a wide range of purposes (FAI team or otherwise).
So, how do we accomplish both these things?
Growing SI into a better organization
Like many (most?) non-profits with less than $1m/yr in funding, SI has had difficulty attracting the top-level executive talent often required to build a highly efficient and effective organization. Luckily, we have made rapid progress on this front in the past 9 months. For example we now have (1) a comprehensive donor database, (2) a strategic plan, (3) a team of remote contractors used to more efficiently complete large and varied projects requiring many different skillsets, (4) an increasingly "best practices" implementation of central management, (5) an office we actually use to work together on projects, and many other improvements.
What else can SI do to become a tighter, larger, and more effective organization?
- Hire a professional bookkeeper, implement additional bookkeeping and accounting best practices. (Currently underway.)
- Create a more navigable and up-to-date website. (Currently underway.)
- Improve our fundraising strategy, e.g. by creating a deck of slides for major donors which explains what we're doing and what we can do with more funding. (Currently underway.)
- Create standard policy documents that lower our risk of being distracted by an IRS audit. (Currently underway.)
- Shift the Singularity Summit toward being more directly useful for AI risk reduction, and also toward greater profitability—so that we have at least one funding source that is not donations. (Currently underway.)
- Spin off the Center for Applied Rationality so that SI is more solely focused on AI safety. (Currently underway.)
- Build a fundraising/investment-focused Board of Trustees (ala IAS or SU) in addition to our Board of Directors and Board of Advisors.
- Create an endowment to ensure ongoing funding for core researchers.
- Consult with the most relevant university department heads and experienced principal investigators (e.g. at IAS and Santa Fe) about how to start and run an effective team for advanced technical research.
- Do the things recommended by these experts (that are relevant to SI's mission).
They key point, of course, is that all these things cost money. They may be "boring," but they are incredibly important.
Attracting and creating superhero mathematicians
The kind of people we'd need for an FAI team are:
- Highly intelligent, and especially skilled in maths, probably at the IMO medal-winning level. (FAI team members will need to create lots of new math during the course of the FAI research initiative.)
- Trustworthy. (Most FAI work is not "Friendliness theory" but instead AI architectures work that could be made more dangerous if released to a wider community that is less concerned with AI safety.)
- Altruistic. (Since the fate of humanity may be in their hands, they need to be robustly altruistic.)
- Hard-working, determined. (FAI is a very difficult research problem and will require lots of hard work and also an attitude of "shut up and do the impossible.")
- Deeply committed to AI risk reduction. (It would be risky to have people who could be pulled off the team—with all their potentially dangerous knowledge—by offers from hedge funds or Google.)
- Unusually rational. (To avoid philosophical confusions, to promote general effectiveness and group cohesion, and more.)
There are other criteria, too, but those are some of the biggest.
We can attract some of the people meeting these criteria by using the methods described in Reaching young math/compsci talent. The trouble is that the number of people on Earth who qualify may be very close to 0 (especially given the "committed to AI risk reduction" criterion).
Thus, we'll need to create some superhero mathematicians.
Math ability seems to be even more "fixed" than the other criteria, so a (very rough) strategy for creating superhero mathematicians might look like this:
- Find people with the required level of math ability.
- Train them on AI risk and rationality.
- Focus on the few who become deeply committed to AI risk reduction and rationality.
- Select from among those people the ones who are most altruistic, trustworthy, hard-working, and determined. (Some training may be possible for these features, too.)
- Try them out for 3 months and select the best few candidates for the FAI team.
All these steps, too, cost money.
This is generally not an indicator available for young people (and I think it's reasonable for MIRI recruiting efforts to target young people), and when it is, it isn't obviously a good idea to use. There are research opportunities available at the high school and undergraduate level, but they are not universally available, and I have been told by people who sit on graduate admissions committees that most of the research that gets produced by these opportunities is bad. Among the research that is not bad, I think it's likely to be unclear to what extent quality of the work is due to the student's efforts or the program / advisor's. (I have heard rumors that in one particular such program, the advisor plots out the course of the research in advance and leads students through it as something like a series of guided exercises.) Edit: I worded that somewhat poorly; I didn't mean to suggest that the work has been done by someone other than the student, but a nontrivial portion of the success of a research project at this level is due to the careful selection of a research problem and careful guidance on the part of the program / advisor, which is not what we want to select for.
By contrast, tests like the AMC (which leads to the IMO in the US), the Putnam, and the SAT are widely available and standardized.