The importance of Explainable AI and how to achieve it

A blog article by the Organisation for Economic Co-operation and Development (OECD) discusses the growing need for transparency and trustworthiness in artificial intelligence (AI) as the technology reshapes critical societal sectors, including healthcare, finance, and justice. The article points out that AI decision-making, which can range from diagnosing diseases to approving loans and influencing judicial outcomes, deeply affects human lives. Yet, significant challenges remain concerning the opaque nature of these systems, often perceived as black boxes due to their complex computational models, like deep neural networks, making their inner workings hidden.

The article focuses on Explainable AI (XAI) as a set of techniques designed to clarify how AI models operate, fostering trust, verification, and responsible use of these advanced technologies. Consequently, it concludes that for AI to become a trusted technology in decision-making processes, its decisions must be understandable, verifiable, and accountable—a need that Explainable AI aims to address by bridging the gap between AI performance and human understanding of its behaviour.