Agentic AI Reference Architecture

Model Adaptation · Data artifact

Fairness-Rebalanced Dataset

Data artifactModel AdaptationModelsarc:FairnessRebalancedDataset

A training dataset whose demographic representation has been balanced by resampling or augmentation, or annotated with per-instance weights, for fairness-aware training.

Responsibility. Supplies representation-balanced training examples or instance weights.

Also known as: Balanced training data, Reweighted training set

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Sources

  1. Ch9.4: T. Nguyen, "Fairness and Bias Mitigation," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 9.4. ISBN: 9798244538229.
  2. Ch10.5: T. Nguyen, "Human-over-the-Loop," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.5. ISBN: 9798244538229.
  3. Ref9.02: "Responsible AI and Ethical Principles," unpublished reference note (02-Responsible-AI-Ethical-Principles.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note