Integrating AI to Assess Community Roles in Environmental Safeguarding During Mining: Implications for ESIA in SSA

This study investigates the role of local communities in environmental safeguarding during mining operations in Sub-Saharan Africa (SSA) and its implications for Environmental and Social Impact Assessments (ESIAs). While mining drives economic development, it often imposes environmental and social costs on local populations. The study critiques existing ESIA frameworks for privileging top-down, technocratic models that marginalize community voices. Using a systematic scoping review of 62 peer-reviewed empirical studies published since 2010, the research analyzes community participation and safeguarding practices through thematic coding and AI-powered tools like natural language processing. The findings underscore that local communities possess unique monitoring capacities, contextual knowledge, and culturally grounded environmental ethics that can enhance ESIA efficacy. These communities often respond more effectively than regulatory authorities to environmental infractions. The study also identifies structural barriers such as tokenistic participation, poverty, and policy exclusion that undermine meaningful engagement. It recommends embedding community-driven perspectives within ESIA processes by strengthening collaborative frameworks, recognizing indigenous knowledge systems, and leveraging AI to ensure inclusive and transparent evaluations. Furthermore, it argues for a shift toward participatory governance models that empower communities as co-regulators of environmental standards. By reframing ESIA as a dynamic socio-environmental negotiation, the study offers practical insights for policy reform, corporate responsibility, and sustainable development in SSA’s mining sectors.