Year: 2025
Type: preprint
Abstract: Artificial intelligence (AI) systems are increasingly deployed in high-stakes domains, raising concerns over transparency, fairness, and accountability. Explainable artificial intelligence (XAI) aims to address these challenges by providing human-interpretable insights into AI models. This paper reviews the current landscape of XAI methods, highlights their advantages and limitations, and outlines future research directions for trustworthy AI deployment.
Author: Tooba Naz
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4412967031