As cited
Copy frozen at (site build).
ai security
18 ways to check whether data can be trusted for AI
ETSI released technical report TR 104 180, which establishes 18 metrics for evaluating data quality before use in artificial intelligence (AI) applications. The metrics, organized into four categories, address data completeness, accuracy, consistency, deduplication, and additional quality dimensions, each with calculation formulas provided.
Why it matters: Organizations deploying AI systems need a standardized framework to validate training and operational data quality; practitioners should reference ETSI TR 104 180 to establish baseline data governance before model development.
- Source published
- First seen by Cybersecurity Tracker