Ontology in Hybrid Intelligence: a concise literature review

In a context of constant evolution and proliferation of AI technology, Hybrid Intelligence is gaining popularity to refer a balanced coexistence between human and artificial intelligence. On the other side, the concept has been extensively used in the past two decades to define models of intelligence involving more than one technology. This paper aims to provide (i) a concise and focused overview of the adoption of Ontology in the broad context of Hybrid Intelligence regardless of its definition and (ii) a critical discussion on the possible role of Ontology to reduce the gap between human and artificial intelligence within hybrid intelligent systems. Beside the typical benefits provided by an effective use of ontologies, at a conceptual level, the analysis conducted has pointed out a significant contribution to quality and accuracy, as well as a more specific role to enable extended interoperability, system engineering and explainable/transparent systems. On the other side, an application-oriented analysis has shown a significant role in present systems (70+% of the cases) and, potentially, in future systems. However, a proper holistic discussion on the establishment of the next generation of hybrid-intelligent environments with a balanced co-existence of human and artificial intelligence is fundamentally missed in literature. Last but not the least, there is currently a relatively low explicit focus on automatic reasoning and inference.