There is a growing desire to use AI/ML to monitor data quality as evident by the increasing number of presentations on the topic coupled with the demands of autonomous systems employed during data taking (e.g. Streaming Read-Out and triggering systems). The field at large would benefit from an exchanging of ideas, tools, and techniques that have been developed for AI/ML based data quality monitoring. The AI4DQM workshop seeks to provide a forum for the discussion of data quality monitoring both in technical solutions as well as sociological challenges with adoption in a fairly informal, virtual, setting. This one day workshop will consist of a series of quick talks with room for discussions covering 4 main topics:
1. Current workflows and methods of DQM
2. ML techniques for anomaly detection/time series anomaly detection etc
3. Current applications of AI4DQM
4. Human interfacing, Trustworthiness, Interpretability, Utility
