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Explore the practical application of Responsible AI principles using the open-source LangTest library in this 32-minute conference talk from MLOps World: Machine Learning in Production. Learn how to address three common challenges in building safe, fair, and reliable AI models: robustness, bias, and data leakage. Discover techniques for testing and improving a model's ability to handle input variations, ensuring equal performance across diverse population groups, and mitigating risks associated with personally identifiable information in training data. Gain insights into generating tests, running evaluations, augmenting data, and integrating these assessments into MLOps workflows. Designed for data science practitioners and leaders, this talk provides actionable knowledge for developing AI and LLM applications that operate safely and dependably in real-world scenarios.
