A Cognitive Assistant for Operators: AI-Powered Knowledge Sharing on Complex Systems
S. Kernan Freire (TU Delft - Internet of Things)
Sarath Panicker (Cognizant)
S. Ruiz Arenas (Universidad EAFIT)
Zoltán Rusak (TU Delft - Internet of Things)
E. Niforatos (TU Delft - Internet of Things)
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Abstract
Operating a complex and dynamic system, such as an agile manufacturing line, is a knowledge-intensive task. It imposes a steep learning curve on novice operators and prompts experienced operators to continuously discover new knowledge, share it, and retain it. In practice, training novices is resource-intensive, and the knowledge discovered by experts is not shared effectively. To tackle these challenges, we developed an AI-powered pervasive system that provides cognitive augmentation to users of complex systems. We present an AI cognitive assistant that provides on-the-job training to novices while acquiring and sharing (tacit) knowledge from experts. Cognitive support is provided as dialectic recommendations for standard work instructions, decision-making, training material, and knowledge acquisition. These recommendations are adjusted to the user and context to minimize interruption and maximize relevance. In this article, we describe how we implemented the cognitive assistant, how it interacts with users, its usage scenarios, and the challenges and opportunities.