Are you an XAI expert?

Study Notes

Explainable Artificial Intelligence (XAI) is a field of machine learning focused on developing and analyzing tools to understand ML models.
ML models are often difficult to understand due to their automatic generation and large number of parameters.
XAI has seen an increase in techniques proposed for various data modalities due to the rise of ML models in high-risk decision-making.
Good explanations balance model fidelity with human interpretability and offer meaningful insights.
Different stakeholders have different perspectives on what constitutes a good explanation, including end-users and regulators.
XAI techniques must be tailored to the appropriate data method.
XAI techniques are not a magic solution and must be evaluated in conjunction with human interpretation.
Human factors are emphasized in XAI, as explanations must be appropriately visualized and interpreted.
This book provides a comprehensive overview of XAI techniques and their practical application.
Readers are advised to appreciate the unique strengths of different XAI techniques rather than relying on a single "magic" method.