Evidence Faithfulness Measure

An Evidence Faithfulness Measure is an interpretability metric that is an explainability evaluation metric quantifying how faithfully a model's classification decisions align with the evidence spans it identifies.

• AKA: Faithfulness Score, Evidence-Decision Alignment Metric.
• Context:
  • It can typically quantify Decision Change when evidence removed.
  • It can typically measure Prediction Stability with only evidence present.
  • It can typically detect Unfaithful Explanations through behavioral tests.
  • It can typically assess Evidence Importance via ablation scores.
  • It can typically identify Gaming Behavior in explanation systems.
  • ...
  • It can often incorporate Comprehensiveness Components measuring necessity.
  • It can often include Sufficiency Components measuring adequacy.
  • It can often utilize Gradient-Based Analysis for importance verification.
  • It can often employ Statistical Tests for significance assessment.
  • ...
  • It can range from being a Binary Faithfulness Measure to being a Continuous Faithfulness Measure, depending on its score granularity.
  • It can range from being a Local Faithfulness Measure to being a Global Faithfulness Measure, depending on its evaluation scope.
  • ...
  • It can evaluate Evidence-Based NLP System faithfulness.
  • It can guide Model Selection for interpretable applications.
  • It can detect Goodhart's Law Effects in optimized models.
  • It can support Explainable AI Research and development.
  • ...
• Example(s):
  • Comprehensiveness Score, measuring confidence drop without identified evidence.
  • Sufficiency Score, measuring confidence level with only evidence.
  • AOPC Score (Area Over Perturbation Curve) for incremental removal.
  • Deletion-Insertion Score for bidirectional faithfulness.
  • Correlation Faithfulness Score between importance weights and impact.
  • ...
• Counter-Example(s):
  • Plausibility Measures, which assess human agreement not model behavior.
  • Accuracy Metrics, which evaluate prediction correctness not evidence reliance.
  • Efficiency Metrics, which measure computational cost not faithfulness.
• See: Interpretability Metric, Explainability Measure, Model Faithfulness Score, Evidence Quality Metric.

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