Translation: Reproducibility means that an AI system's results can be obtained again by someone else using the same data, the same settings, and the same steps. When a system is reproducible, its outputs are consistent and can be checked or verified by others. This helps build confidence in the system and facilitates the identification of errors or unexpected behaviour because reproducible results establish clear reference points, enabling deviations from expected outputs to be detected more effectively.