Motivations for Artificial Intelligence, for Deep Learning, for ALife: Mortality and Existential Risk

Abstract

Abstract We survey the general trajectory of artificial intelligence (AI) over the last century, in the context of influences from Artificial Life. With a broad brush, we can divide technical approaches to solving AI problems into two camps: GOFAIstic (or computationally inspired) or cybernetic (or ALife inspired). The latter approach has enabled advances in deep learning and the astonishing AI advances we see today—bringing immense benefits but also societal risks. There is a similar divide, regrettably unrecognized, over the very way that such AI problems have been framed. To date, this has been overwhelmingly GOFAIstic, meaning that tools for humans to use have been developed; they have no agency or motivations of their own. We explore the implications of this for concerns about existential risk for humans of the “robots taking over.” The risks may be blamed exclusively on human users—the robots could not care less.