dashi: A Python library for Dataset Shift Characterization to Support Trustworthy AI Development and Deployment

arXiv:2605.31360v1 Announce Type: cross Abstract: The Artificial Intelligence (AI) life cycle requires a thorough understanding of the underlying data dynamics for robust, safe and cost-effective AI development and use. Dataset shifts are defined as changes between train and test data distributions. Whether occurring over time (temporal) or across different sites (multi-source), they can severely degrade model performance and compromise data quality. This is particularly important in health AI,