Lessons Learned from Designing and Evaluating CLAICA: A Continuously Learning AI Cognitive Assistant

Learning to operate a complex system, such as an agile production line, can be a daunting task. The high variability in products and frequent reconfigurations make it difficult to keep documentation up-to-date and share new knowledge amongst factory workers. We introduce CLAICA, a Continuously Learning AI Cognitive Assistant that supports...

Harnessing Large Language Models for Cognitive Assistants in Factories

As agile manufacturing expands and workforce mobility increases, the importance of efficient knowledge transfer among factory workers grows. Cognitive Assistants (CAs) with Large Language Models (LLMs), like GPT-3.5, can bridge knowledge gaps and improve worker performance in manufacturing settings. This study investigates the opportunities,...

How Emoji and Explanations Influence Adherence to AI Recommendations

Emoji have become an essential part of modern communication, helping to convey emotions and tone quickly and concisely. Emoji used by humans and Intelligent Agents (IA) have been shown to affect people’s decision making intentions, suggesting they could be used to manipulate users to follow their advice. We present a mixed-methods...

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

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 inefficient and resource intensive. Conversational...