Perspectives on AI-driven systems for multiple sensor data fusion

Artificially intelligent automation has not only impact on sensor technologies, but also on comprehensive multiple sensor systems for assisting situational awareness and decision-making. This is particularly true for integrated Manned-unManned-Teaming (MuM-T), for example. From a systems engineering perspective which does not exclude applications in the defence domain, three tasks need to be fulfilled: (1) Design artificially intelligent automation in a way that human beings are mentally and emotionally able to master each situation. (2) Identify technical design principles to facilitate the responsible use of AI in ethically critical applications. (3) Guarantee that human decision makers always have full superiority of information, decision-making, and options of action. Our discussion of AI-driven systems for multiple sensor data fusion results in recommendations and key results. We are addressing the algorithms needed, the data to be processed, the programming skills required, the computing devices to be used, the inevitable anthropocentric design, the reviewing of R & D efforts necessary, and the integration of different dimensions in a systems-of-systems point of view.