Explainability and Transparency in Designing Responsible AI Applications in the Enterprise

This paper delves into the critical role of Explainable Artificial Intelligence (XAI) in ensuring accountability and reliability within the public sector’s deployment of AI systems. With the rapid integration of AI technologies in public services, the imperative for transparency and comprehension in AI decision-making becomes paramount. The paper explores a spectrum of XAI techniques, frameworks, and incorporates users’ roles and perspectives to establish a comprehensive understanding of how these elements contribute to responsible AI deployment. The research emphasizes the pivotal role of XAI in addressing the growing need for explainability in AI systems, especially in contexts where the decisions impact public services and citizen well-being. We propose a novel framework that incorporates various dimensions of explainability and transparency along with users’ roles at different organizational levels. By delving into diverse XAI techniques, the paper elucidates how explainability and transparency can be achieved in different scenarios, fostering trust and accountability.