An Ethnolinguistic Research Agenda for Intelligent Autonomous Systems

Depicting intelligence by autonomous systems by extracting patterns from heterogeneous data streams poses significant computational and analytical challenges in real-time. We need technologies that can provide multilingual services while respecting each culture and its values and ethics. In many cases, language is not the only reason for misunderstandings and unsatisfactory services, but sometimes cultural properties also play an equivalent role. Current technologies can prominently understand and work with multilingual information; what is required is to embed the cultural constructs and properties during automation. Ethnolinguistics is precisely talking about that, i.e., the relationship between language and culture. The semantic representations of language and cultural differences can prove expressive enough in making judgements when decisions cross geographic boundaries. The vision is to utilize a hybrid of both the syntactic (deep learning) and the symbolic (knowledge graphs) approaches to modeling behaviour. This paper tries to lay forward the current status and future research directions for the vision of intertwining ethnolinguistics and knowledge bases for the intelligent autonomous systems (IAS).