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| Activity title | AI for Military ISR Decision Makers | Activity Reference | SET-290 | Panel | SET | Security Classification | NATO UNCLASSIFIED | Status | Awaiting Publication | Activity type | RLS | Start date | 2020-05-10T00:00:00Z | End date | 2022-12-20T00:00:00Z | Keywords | AI, applications, autonomy, data fusion, multiple hypothesis analysis, probabilistic reasoning decision making, resources management | Background | Recent advances in AI have enabled the design of powerful Multisensor Fusion Engines that are already and will increasingly be among the very backbones of NATO’s situational awareness capabilities (SA). They seamlessly embed mature AI algorithms in overarching C5(J) ISR systems. Exploiting advanced communications links, fusion engines have to be cyber-safe and jamming resistant and are to be integrated into manned-unmanned teaming with intuitive human-machine interfaces. In this context, the RSM SET-262 on “Artificial Intelligence for Military Multisensor Fusion Engines”, held in autumn 2018 in Budapest, HUN, has addressed scientific results and technologies with a clear focus on military SA. | Objectives | In order to able to be more specific, the lecture series is clearly focused on AI for multiple sensor SA and autonomously operating multisensor platforms. The RLS team will present, in a tutorial fashion, core methodologies and proven algorithms of artificial intelligence that solve the various aspects in the context of military SA. Emphasis will also be placed on data integrity aspects of Multisensor Fusion Engines. Besides classical electronic warfare issues, this comprises navigation and cyber warfare. Counter AI, i.e. deliberately deceiving AI systems by adversarial examples and designing deception robust AI, will also be a topic. In addition, the team will address strategic and operational aspects as well as insights into expected capabilities of AI-empowered adversaries that will have an impact on technical systems design and CONOPS. Written notes and presentation slides will be delivered. | Topics | In a systems-of-systems point of view, the participants from the military domain will receive guidelines to assess chances and limitations of AI-empowered fusion engines to be embedded into overarching C5(J) ISR systems. Disruptive effects on military situational awareness, decision-making and Concepts of Operations are expected and need to be evaluated. The most important and expressly intended achievement of the RLS is a contribution towards critical judgement in dealing with artificially intelligent and technically autonomous systems that are currently or in the near future under development. | | Contact Panel Office |
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