Published June 2013 in International Journal of Machine Consciousness 5(1): 59-74
Artificial intelligence, the “science and engineering of intelligent machines”, still has yet to create even a simple “Advice Taker” [McCarthy, 1959]. We have previously argued [Waser, 2011] that this is because researchers are focused on problem-solving or the rigorous analysis of intelligence (or arguments about consciousness) rather than the creation of a “self” that can “learn” to be intelligent. Therefore, following expert advice on the nature of self [Llinas, 2001; Hofstadter, 2007; Damasio, 2010], we embarked upon an effort to design and implement a self-understanding, self-improving loop as the totality of a (seed) AI. As part of that, we decided to follow up on Richard Dawkins’  speculation that “perhaps consciousness arises when the brain’s simulation of the world becomes so complete that it must include a model of itself” by defining a number of axioms and following them through to their logical conclusions. The results combined with an enactive approach yielded many surprising and useful implications for further understanding consciousness, self, and “free-will” that continue to pave the way towards the creation of safe/moral autopoiesis.