Safely crowd-sourcing critical mass for a self-improving human-level learner/"seed AI"

Abstract

Artificial Intelligence (AI), the "science and engineering of intelligent machines", still has yet to create even a simple "Advice Taker" [11]. We argue that this is primarily because more AI researchers are focused on problem-solving or rigorous analyses of intelligence rather than creating a "self" that can "learn" to be intelligent and secondarily due to the excessive amount of time that is spent re-inventing the wheel. We propose a plan to architect and implement the hypothesis [19] that there is a reasonably achievable minimal set of initial cognitive and learning characteristics (called critical mass) such that a learner starting anywhere above the critical knowledge will acquire the vital knowledge that a typical human learner would be able to acquire. We believe that a moral, self-improving learner ("seed AI") can be created today via a safe "sousveillance" crowd-sourcing process and propose a plan by which this can be done. © 2013 Springer-Verlag.