Impact of Non-Human Actors in Communicating Meaning: Towards a Knowledge Translation Framework

Abstract

Knowledge Translation is a core research topic in the field of knowledge sciences.   To date, traditional research on knowledge translation has come from medical and health sciences.  This is not surprising because in health sciences and medicine, there is a long tradition of review of evidence-based research, information dissemination and translating theory to application.  While providing a strong foundation for understanding knowledge translation, research focused on the healthcare domain overlooks the scope or the scale of knowledge translation we all encounter every day in the course of living in the 21st century.  In the knowledge economy, knowledge exchange and simple sharing represent an economic transaction.   Wherever and whenever knowledge is exchanged, knowledge transactions should be as effective and efficient as possible to ensure the flow of knowledge is maximised.   Knowledge exchange frequently occurs between human and non-human actors. In contrast, the traditional knowledge translation literature focuses on human-to-human knowledge translation. This paper looks at knowledge exchanges between human actors and non-human actors in two specific environments.  The first is human-to-machine knowledge translation in service call centres. The second environment focuses on doctor-patient conversations during patient visits, with the participation of third-party non-human actors, e.g. machine transcription applications. These non-human actors create persistent records of exchanges between doctors and patients.  They also have been found to generate high rates of errors in knowledge translation.  The problems, challenges and opportunities involved in each of these fields are the focus of this paper.  The authors identify factors that contribute to knowledge translation failures.