Explainable ai is a research field and methodological approach concerned with developing techniques and frameworks that render the internal mechanisms, decision processes, and predictions of artificial intelligence systems comprehensible to human users. It investigates methods to provide transparency, interpretability, and trustworthiness in AI outputs, addressing the 'black box' problem to facilitate debugging, regulatory compliance, and responsible deployment across critical applications.