Explainability in Process Mining: A Framework for Improved Decision-Making

This PhD thesis develops a comprehensive framework for implementing Explainable Artificial Intelligence (XAI) in Process Mining (PM). Through systematic literature review, practitioner studies, and regulatory analysis, it addresses the gap between technical XAI capabilities and real-world needs. The research proposes a multifaceted approach considering technical, organizational, and ethical dimensions, introducing a structured methodology for integrating explanations into PM systems. The framework guides practitioners in developing transparent and understandable solutions while ensuring compliance with emerging regulations and ethical principles.

keywords: Explainable AI, Process mining, Trustworthy AI, AI Governance, AI Policy