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The importance of augmenting human-technology collaborative cognition has been envisioned as one of the fundamental ways to bolster human cognition through human-automation interaction in complex manufacturing and operational environments. The focus on collaborative cognition entails a human-automation mutual adaption strategy for augmenting team cognition and collective intelligence. This paper provides an overview of augmenting collaborative cognition from an analytic and model-based decision-making perspective. Aiming to advance basic research for understanding human cognition augmentation, the fundamental and applied aspects of creating mathematical and computational models are discussed in regard to cognitive state sensing and assessment, human-automation interaction adaption and control, as well as group decision making in human-automation systems. A research roadmap towards cyber-physical-human analysis is deliberated to reveal a variety of opportunities of developing novel methods for enhancing affective cognition and perception learning, trust dynamics modelling, human cognitive performance prediction, as well as human-automation interaction optimisation.
Jiao et al. (Thu,) studied this question.