AI Evaluation
AI Evaluation is a systematic process for assessing the performance, fairness, robustness, and safety of artificial intelligence models and systems. It involves defining metrics, designing test scenarios, and analyzing results to ensure AI meets specified requirements and ethical standards. This methodology is critical for validating AI in real-world applications and mitigating risks like bias or failure.
Developers should learn AI Evaluation to build trustworthy and reliable AI systems, especially in high-stakes domains like healthcare, finance, or autonomous vehicles where errors can have severe consequences. It is essential for model validation, regulatory compliance, and iterative improvement, helping teams identify issues like overfitting, data drift, or unfair outcomes before deployment.