AI-DRIVEN EXPLAINABILITY: ENHANCING TRANSPARENCY IN DEEP LEARNING MODELS FOR REAL-WORLD APPLICATIONS

Abstract

This paper will discuss how explainability through AI can aid in enhancing transparency and trust in deep learning models applied to real-life situations. The black-box quality of the deep learning techniques makes them difficult to comprehend and interpret, which is an issue in critical fields such as healthcare, finance and smart systems. The explainability framework suggested in this study integrates the transparency throughout the lifecycle of AI, including the processing of data, and the implementation of models. Mixed-method approach is used, as the evaluation is based on the experiment and the development of the framework. The results indicate that explainable AI models are more accurate by 89 percent compared to traditional models, which achieve 91 percent accuracy. The findings also show that the explainable AI models are much easier to interpret since the models are more accurate, 89 percent as compared to traditional models, which are 91 percent accurate. The user trust and bias detection efficiency increase by 55 to 88 and 48 to 82 respectively. Although the rate of computational efficiency (92 to 85) slightly dropped, the overall system effectiveness will also be increased (70 to 86). The results affirm that explainability boosts not only transparency but also fairness and accountability and usability of AI systems. The suggested framework is highly applicable in a variety of spheres, such as healthcare, finance, and smart infrastructure. The current research paper is applicable to the field of explainable AI since it provides a scalable and practical solution which balances both the model performance and explainability. It highlights the importance of adding explainability to AI systems to ensure that it can be deployed in the real world in an ethical and reliable manner.

Keywords : Explainable AI, Deep Learning, Transparency, Interpretability, Artificial Intelligence, Bias Detection, Trustworthy AI.