The meaningfulness gap in AI ethics: a guide on how to think through a complex challenge

Abstract

AbstractTechnological outsourcing is increasingly prevalent, with AI systems taking over many tasks once performed by humans. This shift has led to various discussions within AI ethics. A question that was largely ignored until recently, but is now increasingly being discussed, concerns the meaningfulness of such a lifestyle. The literature largely features skeptical views, raising several challenges. Many of these challenges can be grouped under what I identify as the “meaningfulness gap”. Although this gap is widely acknowledged, there is a notable absence of systematic exploration in the literature. This paper aims to fill this void by offering a detailed, step-by-step guide for systematically exploring the different instances of the meaningfulness gap and aids in navigating their complexities. More specifically, it proposes differentiating the gaps according to their realms and objects, normative nature, scope, and severity. To make these areas manageable, the paper takes several taxonomies and distinctions on board. Finally, the guide is summarized, and some skeptical replies are anticipated and countered by clarificatory remarks.