AI tools expose structural, historical, and cultural drivers of radicalization beyond individual pathology
Original framing: “AI explored as tool for unraveling radicalization's complex drivers” — Phys.org
Including testimonies from diaspora youth, women activists, and religious minorities enriches training data with lived experiences of exclusion and state trauma. Participatory data collection ensures that AI does not amplify only dominant narratives. This democratizes the knowledge production process and improves predictive equity.
AI can illuminate the tangled web of structural inequities, historical grievances, and cultural narratives that fuel radicalization, but only if the technology is co‑designed with the very communities it seeks to understand.
By embedding Indigenous restorative principles, historical continuity, and marginalised testimonies into transparent, open‑source models, we can shift from a surveillance‑centric paradigm to one of preventive, community‑empowered resilience. Cross‑cultural calibration prevents the export of Western bias, while trickster awareness warns against the paradox of technology becoming a new instrument of control. Together, these dimensions point toward a systemic architecture where policy, science, and art collaborate to defuse radical pathways before they erupt into violence.