Beyond the Black Box: Human-AI Collaboration and Algorithmic Accountability in Arabic-Language Fact-Checking

This study examines how Artificial Intelligence (AI) is integrated into Arabic-language fact-checking ecosystems through semi-structured interviews with 12 practitioners and comparative case analysis of four organizations: Sanad, Fatabyyano, Sawab, and Misbar. Drawing on practitioner-reported routines and organizational practices, we analyze how AI supports verification under dialectal variation, geopolitical sensitivity, and uneven digital literacy. Results reveal a shift toward hybrid human-in-the-loop configurations in which AI assists triage and pattern detection while interpretive judgment and verification authority remain human-led. Organizations consistently prioritize procedural transparency, contextual accuracy, and institutional independence over speed and scale. These findings advance debates on algorithmic accountability and human oversight while contributing to scholarship on verification systems in the Global South. This study highlights the need for culturally aligned approaches to automated fact-checking in politically complex and multilingual information environments.