This document is a patent application (EP4711992A1) published by the European Patent Office (EPO) concerning systems and methods for detecting and correcting data set drift. The application describes a process where data sets are classified, and two classifiers are trained on data from multiple data sets, each associated with a distinct classification. Drift is identified when the performance of either classifier surpasses a set threshold. Some embodiments may utilize these trained classifiers to determine which data elements from one data set should be combined with another for training purposes.

While this is a patent application and not a regulatory rule, it outlines novel technical approaches relevant to AI and machine learning development. Companies involved in AI model training, particularly those handling large and evolving data sets, may find these techniques of interest for ensuring model accuracy and reliability. There are no immediate compliance obligations or deadlines associated with a patent application, but it signifies potential future technological standards or patented solutions in the field of data drift management.