Empowering Adaptive Human Autonomy Collaboration with Artificial Intelligence

We can now see examples emerge of intelligent distributed hybrid systems with autonomous functions pursuing a specific goal while adapting dynamically to changing environments. Such solutions are made possible by convergence of new technologies, but achieving comprehensive monitoring of the multiple interactions in their organization and functions along their life cycles, in missions and/or safety critical contexts, still challenges system (of systems) engineering practices. This paper considers the main gaps towards trusted systems of systems, including human-AI collaboration, human-machine teaming and solution effectiveness monitoring in a life cycle perspective. These gaps call for an inter-disciplinary sociotechnical approach in engineering towards Adjustable Human Autonomy Collaboration (DUAL), whose justification is outlined in this position paper.