Evolution and control of artificial superintelligence (ASI): a management perspective

Abstract

Purpose The purpose of this paper is to address both the evolutionary and control aspects associated with the management of artificial superintelligence. Through empirical analysis, the authors examine the diffusion pattern of those high technologies that can be considered as forerunners to the adoption of artificial superintelligence (ASI). Design/methodology/approach The evolutionary perspective is divided into three parts, based on major developments in this area, namely, robotics, automation and artificial intelligence (AI). The authors then provide several dynamic models of the possible future evolution of superintelligence. These include diffusion modeling, predator–prey models and hostility models. The problem of control in superintelligence is reviewed next, where the authors discuss Asimov’s Laws and IEEE initiative. The authors also provide an empirical analysis of the application of diffusion modeling to three technologies from the industries of manufacturing, communication and energy, which can be considered as potential precursors to the evolution of the field of ASI. The authors conclude with a case study illustrating emerging solutions in the form of long-term social experiments to address the problem of control in superintelligence. Findings The results from the empirical analysis of the manufacturing, communication and energy sectors suggest that the technology diffusion model fits well with the data of robotics, telecom and solar installations till date. The results suggest a gradual diffusion process, like any other high technology. Thus, there appears to be no threat of “existential catastrophe” (Bostrom, 2014). The case study indicates that any future threat can be pre-empted by some long-term social measures. Originality/value This paper contributes to the emerging stream of artificial superintelligence. As humanity comes closer to grappling with the important question of the management and control of this technology for the future, it is important that modeling efforts be made to understand the extant perspective of the development of the high-technology diffusion. Presently, there are relatively few such efforts available in the literature.