17.2 Measuring Incremental Progress Toward Human-Level AGI 309 about how to measure incremental progress. How do you tell when you’re 25% or 50% of the way to having an AGI that can pass the Turing Test, or get an online university degree. Fooling 50% of the Turing Test judges is not a good measure of being 50% of the way to passing the Turing Test (that’s too easy); and passing 50% of university classes is not a good measure of being 50% of the way to getting an online university degree (it’s too hard — if one had an AGI capable of doing that, one would almost surely be very close to achieving the end goal). Measuring incremental progress toward human-level AGI is a subtle thing, and we argue that the best way to do it is to focus on particular scenarios and the achievement of specific competencies therein. As we argued in Chapter 8 there are some theoretical reasons to doubt the possibility of creating a rigorous objective test for partial progress toward AGI — a test that would be con- vincing to skeptics, and impossible to "game" via engineering a system specialized to the test. Fortunately, though we don’t need a test of this nature for the purposes of assessing our own incremental progress toward advanced AGI, based on our knowledge about our own approach. Based on the nature of the grand goals articulated above, there seems to be a very natural approach to creating a set of incremental capabilities building toward AGI: to draw on our copious knowledge about human cognitive development. This is by no means the only possible path; one can envision alternatives that have nothing to do with human development (and those might also be better suited to non-human AGIs). However, so much detailed knowledge about human development is available — as well as solid knowledge that the human developmental trajectory does lead to human-level AI — that the motivation to draw on human cognitive development is quite strong. The main problem with the human development inspire