Augmenting collaborative cognition is envisioned to be important to bolster human cognition with technologies through human-automation interaction in future complex manufacturing and operational environments. This project investigates the theoretical foundation of augmenting collaborative cognition from the perspectives of cyber-physical-human analysis and model-based decision support. The goal is to develop mathematical and computational models and tools to advance basic research for understanding human cognition augmentation regarding such critical issues as cognitive state sensing and assessment, human-automation interaction adaption and control, as well as group decision making in human-automation systems. Key research issues include effective cognition and perception learning, trust dynamics modeling, human cognitive performance prediction, and human-automation interaction optimization. The focus on collaborative cognition entails a human-automation mutual adaption strategy for augmenting human team cognition and collective intelligence. The ultimate goal of this project is to develop the necessary research personnel, research infrastructure, and foundational work to expand the opportunities for studying future technology, future workers, and future work at the level of a FW-HTF full research proposal.
This convergent project will provide new insights into cognitive interactions between workers, technologies, robots, and machines in future factories, empowering adaptive task abilities to improve both productivity and worker experience. It contributes to a deeper understanding of augmented manufacturing and operational environments of the future by amplifying cognitive capacities and leveraging human cognitive burden with artificial intelligence and smart automation. The proposed work has the potential to establish a new paradigm for augmenting human collaborative cognition, which will shed light on the economic and societal impacts on the future of work. The research results will be incorporated into new interdisciplinary engineering curricula to enrich undergraduate and graduate education. The testbed and prototype implementation will offer a unique opportunity to deploy new curriculum through the Makerspace to enhance a human-centered open design and innovation culture and promote mass customized education and learning experience for students to be exposed to multidisciplinary knowledge.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
