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AssigneeMicrosoft Technology Licensing, LLC
InventorsAanchal GUPTA, Abhilasha BHARGAV-SPANTZEL
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Methods, systems, and computer storage media for providing bias mitigation management using a bias mitigation engine in an artificial intelligence (AI) system are described. The bias mitigation engine is designed to identify, correct, and prevent biases in AI-generated legal analyses. The bias mitigation engine utilizes synthetic data generation, fairness metrics, and scenario-based training to ensure equitable representation of legal cases. The bias mitigation engine can integrate Retrieval-Augmented Generation (RAG) to dynamically update AI models with landmark cases, evolving regulations, and societal shifts. The bias mitigation engine applies adversarial testing and statistical fairness checks detect systemic biases. Additionally, it leverages progressive learning to refine AI models over time, ensuring context-aware, unbiased decision-making. Explainability tools like SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-agnostic Explanations) provide human-readable rationales. The bias mitigation engine continuously audits and recalibrates predictions to maintain fairness, ensuring legal decisions remain aligned with current ethical and judicial standards.
A computerized system comprising:
One or more computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the processor to perform operations, the operations comprising:
A computer-implemented method, the method comprising:
Dependencies are inferred from the claim text.