Responsible Recovery of Mine Tailings: A Governance-Driven Framework for Intelligent Green Mining

The transition to intelligent, low-carbon mining requires turning solid-waste liabilities into strategic resources. This study develops a Responsible Recovery framework for the disposal and utilisation of mine tailings, integrating global governance standards, advanced process technologies, and emerging AI tools. Using critical-material tailings as a test domain, the framework connects risk classification, disclosure, and flowsheet design to auditable performance metrics. Intelligent modules - from site-inventory parsing and flowsheet recommendation to automated validation of ESG datasets - show how artificial intelligence can improve technical accuracy while strengthening transparency. The approach supports circular recovery of cobalt, nickel, and rare-earth-bearing residues, reducing both waste and import dependence. By aligning digital innovation with established standards such as the Global Industry Standard on Tailings Management (GISTM) and that of the Mining Association of Canada (MAC), the paper shows how tailings management can evolve into a governed, data-driven pathway for recovering critical materials within the wider Intelligent Green Mining agenda.