Tacit Knowledge Elicitation for Shop-floor Workers with an Intelligent Assistant

Abstract

Many industries face the challenge of capturing workers' knowledge to share it, particularly tacit knowledge. The operation of complex systems such as a manufacturing line is knowledge-intensive. Considering this knowledge's breadth and dynamic nature, existing knowledge-sharing solutions are inefcient and resource intensive. Conversational user interfaces are an efcient way to convey information that mimics how humans share knowledge; however, we know little about how to design them specifcally for knowledge sharing, especially regarding tacit knowledge. In this work, we present an intelligent assistant that we have developed to support the elicitation of tacit knowledge from workers through systematic refection. The system can interact with workers by voice or text and generate visualizations of shop foor data to support refective prompts. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; Interactive systems and tools; Natural language interfaces.