Paper Contents
Abstract
This review consolidates recent advances in Explainable Artificial Intelligence (XAI), exploring its methodologies, applications, and emerging challenges based on an analysis of four foundational papers. XAI aims to address the opacity of black-box AI models, fostering transparency, trustworthiness, and accountability in their decision-making processes. By synthesizing findings from healthcare, finance, manufacturing, and transportation, this paper highlights current trends and provides a roadmap for future interdisciplinary research.
Copyright
Copyright © 2024 Abhishek Sain . This is an open access article distributed under the Creative Commons Attribution License.
Paper ID:
IJPREMS41200014474
ISSN:
2321-9653
Publisher:
ijprems