  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. The term 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 conducted analysis has
pointed out a significant contribution of Ontology to improve quality and
accuracy, as well as a more specific role to enable extended interoperability,
system engineering and explainable/transparent systems. Additionally, an
application-oriented analysis has shown a significant role in present systems
(70+% of the cases) and, potentially, in future systems. However, despite the
relatively consistent number of papers on the topic, 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
in hybrid intelligent systems.
