A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems - Githubissues

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A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems #22

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XAI Design Goals

AI Novices
- G1: Algorithmic Transparency
- G2: User Trust and Reliance
- G3: Bias Mitigation
- G4: Privacy Awareness
Data Experts
- G5: Model Visualization and Inspection
- G6: Model Tuning and Selection
AI Experts
- G7: Model Interpretability
- G8: Model Debugging

Evaluation Measures

M1: Mental Model
M2: Explanation Usefulness and Satisfaction
M3: User Trust and Reliance
M4: Human-AI Task Performance
M5: Computational Measures

XAI Design and Evaluation Framework

Guideline1: Determine XAI System Goals
Guideline2: Decide What to Explain
Guideline3: Evaluate System Outcomes
Guideline4: Decide How to Explain
Guideline5: Evaluate Explanation Usefulness
Guideline6: Design Interpretability Technique
Guideline7: Evaluate Trustworthiness