The Human Factors of AI-Empowered Knowledge Sharing

Abstract

Many industries are facing the challenge of how to capture workers' knowledge such that it can be shared, in particular tacit knowledge. The operation of complex systems such as a manufacturing line is knowledge-intensive, especially if the operator must frequently reconfigure it for different products. Considering the breadth and dynamic nature of this knowledge, existing solutions for sharing knowledge (e.g., word-of-mouth, issue reports, document creation, and decision support systems) are inefficient and/or resource-intensive. Conversational user interfaces are an efficient way to convey information that mimics the way humans share knowledge; however, we know little about how to design them specifically for this purpose, especially regarding tacit knowledge. In this work, my main goal is to investigate how a cognitive assistant can be designed to facilitate (tacit) knowledge transfer between users of dynamic complex systems. I aim to achieve this by outlining the design requirements, challenges, and opportunities in factories; by collaboratively designing, implementing, and evaluating a cognitive assistant for sharing knowledge; studying the effects of design characteristics on aspects such as user experience; and finally, creating a set of design guidelines.