Don't Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agents

TL;DR

This paper introduces AI forensic agents that enhance multimedia authenticity verification by integrating uncertainty calibration, addressing current limitations, and providing a unified framework for more reliable forensic analysis.

Contribution

It presents a novel framework for uncertainty-aware AI forensic agents that improve multimedia forensics beyond existing methods.

Findings

Identifies pitfalls in current forensic solutions.

Proposes a unified framework for better authenticity verification.

Enhances reliability of multimedia forensic agents.

Abstract

AI is reshaping the landscape of multimedia forensics. We propose AI forensic agents: reliable orchestrators that select and combine forensic detectors, identify provenance and context, and provide uncertainty-aware assessments. We highlight pitfalls in current solutions and introduce a unified framework to improve the authenticity verification process.