A clarifying question. By ‘rigor’, do you mean the kind of rigor that is required to publish in journals like Risk Analysis or Minds and Machines, or do you mean something else by ‘rigor’?
I mean the kind of precise, mathematical analysis that would be required to publish at conferences like NIPS or in the Journal of Philosophical Logic. This entails development of technical results that are sufficiently clear and modular that other researchers can use them in their own work. In 15 years, I want to see a textbook on the mathematics of FAI that I can put on my bookshelf next to Pearl’s Causality, Sipser’s Introduction to the Theory of Computation and MacKay’s Information Theory, Inference, and Learning Algorithms. This is not going to happen if research of sufficient quality doesn’t start soon.
How are you going to address the perceived and actual lack of rigor associated with SIAI?
There are essentially no academics who believe that high-quality research is happening at the Singularity Institute. This is likely to pose problems for your plan to work with professors to find research candidates. It is also likely to be an indicator of little high-quality work happening at the Institute.
In his recent Summit presentation, Eliezer states that “most things you need to know to build Friendly AI are rigorous understanding of AGI rather than Friendly parts per se”. This suggests that researchers in AI and machine learning should be able to appreciate high-quality work done by SIAI. However, this is not happening, and the publications listed on the SIAI page—including TDT—are mostly high-level arguments that don’t meet this standard. How do you plan to change this?