Employing AI for Better Understanding Our Morals

Abstract

Having addressed the prerequisite issues for a justified and contextualized computational morality, the absence of radically new problems resulting from the co-presence of agents of different nature, and addressed the difficulties inherent in the creation of moral algorithms, it is time to present the research we have conducted. The latter considers both the very aspects of programming, as the need for protocols regulating competition among companies or countries. Its aim revolves around a benevolent AI, contributing to the fair distribution of the benefits of development, and attempting to block the tendency towards the concentration of wealth and power. Our approach denounces and avoids the statistical models used to solve moral dilemmas, because they are “blind” and risk perpetuating mistakes. Thus, we use an approach where counterfactual reasoning plays a fundamental role and, considering morality primarily a matter of groups, we present conclusions from studies involving the pairs egoism/altruism; collaboration/competition; acknowledgment of error/apology. These are the basic elements of most moral systems, and studies make it possible to draw generalizable and programmable conclusions in order to attain group sustainability and greater global benefit, regardless of their constituents.