Bias Mitigation

Browse all content tagged with Bias Mitigation

Glossary

Explainability

AI Explainability refers to the ability to understand and interpret the decisions and predictions made by artificial intelligence systems. As AI models become more complex, explainability ensures transparency, trust, regulatory compliance, bias mitigation, and model optimization through techniques like LIME and SHAP.

AI Explainability Transparency +4
• 5 min read
Glossary

Synthetic Data

Synthetic data refers to artificially generated information that mimics real-world data. It is created using algorithms and computer simulations to serve as a substitute or supplement for real data. In AI, synthetic data is crucial for training, testing, and validating machine learning models.

Synthetic Data AI Machine Learning +3
• 2 min read

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