Explanation Representation Format

Explanation representation formats are crucial for making artificial intelligence (AI) models more transparent and understandable. Current research emphasizes developing methods that not only accurately reflect the AI's decision-making process but also provide insights into feature importance and causal relationships, often combining model-dependent and model-agnostic approaches. This focus on improving the clarity, completeness, and accuracy of explanations aims to enhance trust, usability, and ultimately, the responsible deployment of AI across various scientific and practical applications.