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AI/Analytics Explainability

All Glossary Terms

AI & analytics explainability is the idea that humans should be able to understand and interpret how AI/ML models arrive at their predictions. Explainability occurs when there is transparency that gives humans the ability to question the inner workings of machine learning models. Organizations pursue explainable AI to bring transparency into internal processes and solve common issues, such as identifying AI bias.

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Data Lineage Data Observability ML Pipeline