Augmenting cognition: Reviewing the symbiotic relation between man and machine

One of the goals of augmented cognition is creation of adaptive human-machine collaboration that continually optimizes performance of the human-machine system. Augmented Cognition aims to compensate for temporal limitations in human information processing, for instance in the case of overload, cognitive lockup, and underload. Adaptive behavior, however, may also have undesirable side effects. The dynamics of adaptive support may be unpredictable and may lead to human factors problems such as mode errors, ‘out-of-the-loop’ problems, and trust related issues. One of the most critical challenges in developing adaptive human-machine collaboration concerns system mitigations. A combination of performance, effort and task information should be taken into account for mitigation strategies. This paper concludes with the presentation of an iterative cognitive engineering framework, which addresses the adaptation strategy of the human and machine in an appropriate manner carefully weighing the costs and benefits