Don't Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agents
arXiv:2512.16614v1h-index: 5
Originality Synthesis-oriented
AI Analysis
This addresses the need for more reliable and explainable AI tools in multimedia forensics, though it appears incremental as it builds on existing forensic detectors.
The paper tackles the problem of unreliable multimedia forensics by proposing AI forensic agents that provide uncertainty-aware assessments, resulting in a unified framework to improve authenticity verification.
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.