The Role of Explainable AI (XAI) in Forensic Investigations
Yara Shamoo · Advances in digital crime, forensics, and cyber terrorism book series · 2024
The increasing reliance on Artificial Intelligence (AI) in digital forensic investigations has brought forward significant advancements in the identification, analysis, and interpretation of digital evidence. However, one of the major challenges remains the “black-box” nature of many AI models, which often hinder trust, accountability, and transparency. Explainable AI (XAI) emerges as a critical solution, providing clarity into the decision-making processes of AI systems. In the context of digital forensics, XAI facilitates investigators' understanding of AI-driven tools, ensuring that conclusions drawn from automated analyses are interpretable, verifiable, and legally admissible. This chapter explores the role of XAI in digital forensics, highlighting its potential to enhance the reliability and transparency of AI-based forensic systems, while addressing key challenges and ethical considerations. We examine the integration of XAI in forensic workflows, discuss various techniques for explainability, and evaluate real-world case studies where XAI has contributed to improved forensic outcomes.