Description: Unifying concepts are general ideas that connect different aspects of explainable artificial intelligence (XAI). These concepts aim to provide a coherent framework that facilitates the understanding and interpretation of AI models, especially those that operate as ‘black boxes’. XAI focuses on making the decision-making processes of algorithms transparent and comprehensible to users, which is crucial in applications where trust and accountability are essential, such as in healthcare, legal systems, and financial services. Unifying concepts allow researchers and professionals to identify common patterns and underlying principles that can be applied to various AI techniques, thus promoting a more holistic and systematic approach to the development and implementation of AI systems. These concepts encompass themes such as interpretability, transparency, fairness, and accountability, and are fundamental to addressing the ethical and technical challenges that arise in the field of AI. By integrating these concepts, the aim is not only to improve the understanding of AI models but also to foster a broader dialogue about their impact on society and the need for appropriate regulations.
