From Features to Actions: Explainability in Traditional and Agentic AI Systems

By: Sindhuja Chaduvula, Jessee Ho, Kina Kim, Aravind Narayanan, Mahshid Alinoori, Muskan Garg, Dhanesh Ramachandram, Shaina Raza

Published: 2026-02-09

View on arXiv →
#cs.AI

Abstract

This research delves into the critical area of explainable AI (XAI), comparing and contrasting explainability in traditional AI models with that in more complex agentic systems. Enhancing XAI is vital for building trust and ensuring responsible deployment of AI in sensitive applications.

FEEDBACK

Projects

No projects yet

From Features to Actions: Explainability in Traditional and Agentic AI Systems | ArXiv Intelligence