The proliferation of Artificial Intelligence, particularly Machine Learning and Deep Learning, has reached the space sector, given the method's high computational performance. However, the integration of AI-based systems in spacecraft operations or onboard spacecraft has not moved further than being researched. One of the reasons is that many non-AI-expert users state that the complexity and black-box behavior is leading to a lack of understandability and trust in such AI systems. Hence, for the end-users, in this case, the spacecraft operators, the utilization of ML and DL models comes with the uncertainty of how those models operate and make decisions. To build trust, AI-based concepts must be evaluated based on their explainability and interpretability, their computational performance and robustness, as well as their testing-concept and general verifiability, considering both the needs and knowledge of the developer and the end-user. The aim of this study is to understand and showcase the rationales of why \ac{AI}-based space systems are not trusted and what tools, techniques, or guidelines and standards need to be established to increase their usability and enable the utilization of AI-based space systems outside of the research field. For this purpose, a questionnaire was conducted among space operations professionals of the German and European space ecosystem to understand the concerns and apprehensions towards the deployment of AI-based space systems. The preliminary results of the evaluation of the questionnaire together with indications on concepts and processes for increased explainability of \ac{AI}-based space systems are presented in this study. The focus is laid on users and applications in the field of spacecraft operations.     «

The proliferation of Artificial Intelligence, particularly Machine Learning and Deep Learning, has reached the space sector, given the method's high computational performance. However, the integration of AI-based systems in spacecraft operations or onboard spacecraft has not moved further than being researched. One of the reasons is that many non-AI-expert users state that the complexity and black-box behavior is leading to a lack of understandability and trust in such AI systems. Hence, for the...     »