In Search of Clarity: Discerning between Human Replacement and Augmentation

Abstract

As intelligent systems become more autonomous, humans increasingly delegate important tasks and decisions to them. On the one hand, this approach seems to be very supportive to humans, on the other it generates apprehension about a future dominated by machines. These contrasting viewpoints encapsulate what in literature is usually referred to as augmenting, enhancing or amplifying humans versus replacing them. However, these concepts lack clear and shared definitions. To fill this gap, we conducted a semi-systematic literature review to elicit existing definitions, if any. We found out that replacement is generally negatively considered while a hybrid approach is often preferred, as there is a hesitancy to embrace complete automation, primarily driven by a lack of trust in AI systems. To make these concepts applicable, it is essential to identify shared and actionable definitions. Building on these insights, our upcoming research aims at developing a framework that fosters their measurement.