Explainable AI (XAI) is a field of research that seeks to make AI models more transparent and interpretable. By improving the explainability of AI, XAI aims to enhance trust, accountability, and ethical considerations in AI development and deployment. XAI techniques can be applied to a wide range of AI models and applications, including natural language processing, image recognition, and predictive modeling.