Data quality checks and provenance data in detecting problematic executions of AI tools used for data curation tasks
Date:
Invited talk at the European Institute for Innovation through Health Data (i~HD) Annual Conference 2023, in the AI track on bias and transparency.
The talk covered how the AIDAVA project enhances data quality and establishes quality checks for results generated by automated AI curation tools, and the significance of provenance information for trustworthiness of AI systems in clinical and healthcare settings.