This collection of essays offers an analysis of issues that biological systems raise from a network perspective. It brings together scholars from biology, neuroscience, process philosophy, computer science and mathematics to explore this theme. As a whole, the contributors highlight the depth of the nexial dimension of biological systems, from the molecular to the organic scales, as well as the social and cultural levels. The flexibility of these systems enables them to reuse modules in order to generate new skills that will characterize a given species. One type of network has become the source of inspiration for the development of deep learning. This result opens the prospect that other types of biological systems may inspire innovations in artificial intelligence. Here, the purpose of common good could lead the path to some sort of enlightened conciliation and Solomonic wisdom that would help buttress and foster these future developments.