Human-AI Agreement Measure

A Human-AI Agreement Measure is an agreement measure that is a human-machine interaction measure.

• AKA: Human-Machine Concordance Metric, AI-Human Alignment Score, Human-AI Consistency Measure.
• Context:
  • It can typically quantify Human-AI Decision Alignment between human judgments and AI predictions.
  • It can typically calculate Human-AI Precision Agreement through human-AI precision formulas.
  • It can typically compute Human-AI Recall Agreement through human-AI recall calculations.
  • It can typically determine Human-AI F1 Agreement through human-AI F1 scores.
  • It can typically measure Human-AI Cohen's Kappa through human-AI kappa statistics.
  • ...
  • It can often assess Human-AI Correlation Coefficient through human-AI statistical correlations.
  • It can often evaluate Human-AI Matthews Correlation through human-AI MCC calculations.
  • It can often track Human-AI Acceptance Rate through human-AI approval metrics.
  • It can often monitor Human-AI Override Rate through human-AI rejection frequencys.
  • ...
  • It can range from being a Simple Human-AI Agreement Measure to being a Complex Human-AI Agreement Measure, depending on its human-AI metric complexity.
  • It can range from being a Binary Human-AI Agreement Measure to being a Multi-Class Human-AI Agreement Measure, depending on its human-AI classification type.
  • It can range from being a Point Human-AI Agreement Measure to being an Interval Human-AI Agreement Measure, depending on its human-AI confidence scope.
  • It can range from being a Static Human-AI Agreement Measure to being a Dynamic Human-AI Agreement Measure, depending on its human-AI temporal nature.
  • ...
  • It can support Human-AI Performance Evaluation through human-AI benchmark standards.
  • It can enable Human-AI Quality Control through human-AI threshold settings.
  • It can facilitate Human-AI Model Selection through human-AI comparison metrics.
  • It can guide Human-AI Trust Calibration through human-AI reliability indicators.
  • It can inform Human-AI Resource Allocation through human-AI efficiency measures.
  • ...
• Example(s):
  • Classification Human-AI Agreement Measures, such as:
    • Binary Classification Human-AI Agreement Measure for binary decision agreement.
    • Multi-Class Classification Human-AI Agreement Measure for multi-category agreement.
    • Hierarchical Classification Human-AI Agreement Measure for hierarchical category agreement.
  • Regression Human-AI Agreement Measures, such as:
    • Continuous Value Human-AI Agreement Measure for numerical prediction agreement.
    • Ordinal Human-AI Agreement Measure for ranked outcome agreement.
  • Domain-Specific Human-AI Agreement Measures, such as:
    • Contract Policy Detection Agreement Measure for legal contract agreement.
    • Medical Diagnosis Human-AI Agreement Measure for healthcare decision agreement.
    • Financial Risk Human-AI Agreement Measure for financial assessment agreement.
  • Behavioral Human-AI Agreement Measures, such as:
    • Human-AI Trust Measure for trust level quantification.
    • Human-AI Reliance Measure for dependence level assessment.
  • ...
• Counter-Example(s):
  • Human Inter-Annotator Agreement Measures, which lack human-AI machine component.
  • AI Performance Measures, which lack human-AI human comparison.
  • General Accuracy Measures, which lack human-AI agreement focus.
• See: Agreement Measure, kappa Measure of Agreement Statistic, Inter-Rater Reliability (IRR) Score, Human Inter-Annotator Agreement (IAA) Measure, Precision Metric, F-Measure, Cohen's Kappa.

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