Psychological Models of Explanatory Reasoning
This contribution contains a set of technical reports on psychological models of explanation, capturing different concepts, methods, and metrics.
Overview and Blogs
The XAI Literature Review
Non-Algorithmic Methods for XAI
Lessons for XAI from Intelligent Tutoring Systems
The AIQ Toolkit
The Discovery Platform
“Eggsplaining” AI: An Analogy for How Deep Nets Work
Actionable Concepts, Methods, and Metrics for Explanatory Reasoning
Validated scales for Explanation Goodness, Curiosity, and Trust
Metrics for Explainable AI
For explanation goodness, satisfaction and curiosity. Includes a review of methods for evaluating user mental models.
The Self-Explanation Scorecard
For evaluating the “explanatory depth” of explanations.
The Stakeholder Playbook
For tailoring explanations to stakeholder groups.
Measuring Trust in the XAI Context
Methodology for eliciting user mental models
Methodology for creating “Cognitive Tutorials” for explaining AI systems
Cognitive Tutorial Authoring Guide
Guidance for experimental design for XAI evaluation
Methodology Requirements
Methodology Recommendations
Developing psychologically plausible models of explanation
Modeling the Explanation Process
The “Plausibility Gap” Model
A Computational Cognitive Model of explanatory reasoning
A system for enabling users to share and discuss their own explanations
CXAI: Collaborative Explainable AI