Cognitive Extraction and the Neuro-Chilimba Framework: An Indigenous ROSCA-Based Governance Architecture for Neural Data in Zambia

Consumer neurotechnology devices are proliferating into Sub-Saharan African markets, creating conditions for systematic cognitive extraction. The harvesting of communal neural data under legal regimes designed for individual, not collective, data subjects. Zambia's Data Protection Act 2021 and Cyber Security Act 2025 (Act No. 3 of 2025) contain three structural deficits: Absent communal consent authority, absent neural-data classification, and absent benefit-sharing obligations. This conceptual paper develops the Neuro-Chilimba Framework (NCF), an indigenous governance architecture for communal neural data derived from Zambian Rotating Savings and Credit Associations (Chilimba/ROSCAs) and grounded in Ubuntu relational ontology. Employing the novel institutional analogue method, systematic extraction and digital protocolisation of governance mechanisms from culturally legitimate indigenous institutions, the study conducts systematic literature review (1960–2025) across 247 sources, thematic coding of 14 seminal ROSCA ethnographies, doctrinal legal analysis, and CARE-based regulatory gap evaluation. The NCF operationalises seven ROSCA mechanisms into four dimensions: Entry Protocols (Human Firewall), Collective Control (Community Consent Board with 60–75% consent thresholds), Rotational Benefit (minimum 20% Cognitive Dividend), and Relational Justice (Ubuntu-grounded dispute resolution). Three legislative amendments and a Social License to Operate certification pathway are provided. This is the first framework integrating ROSCA ethnography, Ubuntu philosophy, decolonial AI, and Ostrom's common-pool resource principles into a testable, legally actionable neural-data governance architecture. All quantitative thresholds are provisional design parameters requiring participatory calibration.