The current document is a white paper that reflects all the work that is executed in task 5.2 of the JARVIS project. The task focuses on Human-AI teaming (HAT). It contains a literature survey which describes the state of the art on the topic of HAT. Further knowledge exchange between this task and the different JARVIS solutions is described and also fundamental human in the loop experiments that were designed and executed to learn more about the relationship between human and AI as teams are described.The perspective on AI is changing over time and becoming more detailed. Despite all clever technology and scientific research that enable and develop AI, there are still differences between humans and AI, and those differences should be respected in order to reach the most optimal teaming between the two. The JARVIS project, a SESAR Joint Undertaking initiative (Grant 101114692), ran from 2023 to 2026 and developd three digital assistants for airborne, air traffic control and airport operations. Within workpacke 5 (WP 5) lessons learned on foundational AI challenges dataset creation, AI design assurance and Human-AI teaming were collected.
Centre et al. (Mon,) studied this question.
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