We want to understand how extremely good mathematicians think and work – real, live, human mathematicians at the top of their fields, or on their way there. We have lots of public data on this group (e.g., research talks, the papers they write, sometimes the blogs they create) but this huge volume is also a problem, and we need to hire people to help us make sense of things – people who are themselves expert mathematicians, who can work with us to help validate our analyses, develop stimuli for psychological experiments, and expand our understanding.
Mathematicians have ways of thinking and seeing that go well beyond our standard psychometric accounts of what we mean by intelligence (e.g., the pattern-recognition story in Raven's Progressive Matrices). Expert mathematicians, when they take the time to report their own mental processes, describe experiences, ways of thinking, and long-duration concentration and attention events that far exceed what psychological studies have been able to probe in any systematic fashion. Distinctions such as algebraic-geometric, the use of examples and mental experiments, and the notion of ontological transfer are just a few cases where we have reliable evidence to support their existence, but very little systematic knowledge of how these are deployed.
Mathematics is not the only domain in which extreme cognition happens, but it is a particularly fruitful one because it is cross-cultural (compared to, say, artistic works, mathematical proofs do not express any particular national culture), transhistorical (proof-based mathematics has existed for more than two thousand years), and largely free of capital constraints (in contrast to scientific experiments such as CERN or Hubble, proof-making does not require large equipment, or specific government of corporate investment).
We are not sure what we’re going to find, but we think this will be a first scientific portrait of humans thinking at this extreme edge of our species’ limits. Understanding the weird ways they do things will expand our understanding of what intelligence is, and help us develop new ways to think about the next stages of AGI.