Department of History, University of Ghana.
Research Article
World Journal of Advanced Research and Reviews, 2023, 18(02), 1475-1488
Received on 02 April 2023; revised on 18 May 2023; accepted on 27 May 2023
This study explores the concept of “invisible commerce” by examining the trade networks and mutual aid systems established and maintained by African women between the 1870s and 1950s. While historical narratives of commerce in Africa have often emphasized formal markets, colonial trade policies, and documented transactions, much of women’s economic activity operated outside official structures, circulating through kinship ties, informal credit arrangements, itinerant trade, and cooperative labor exchange. These networks not only sustained households but also shaped local and regional economies, influencing mobility, cultural exchange, and resilience during periods of political upheaval, forced migration, and economic restructuring. With the emergence of Artificial Intelligence, new possibilities arise for analyzing dispersed archival traces such as personal letters, missionary reports, market logs, oral histories, and ethnographic field notes traditionally difficult to synthesize at scale. Using machine learning techniques, this study proposes a framework for identifying patterns of cooperation, trade routes, commodity flows, and relational ties embedded in fragmented historical data. Natural language processing enables the recognition of women’s names, roles, and exchanges across multilingual and colonial-era records, while network analysis visualizes the social infrastructure of trade communities and rotating savings associations. By integrating AI-assisted archival mapping with feminist historiography and African economic anthropology, this study reveals how women acted as logistical coordinators, credit brokers, and cultural intermediaries. These findings challenge economic histories that marginalize women’s agency, illuminate forms of value exchange not captured in monetary records, and reposition women at the center of African commercial innovation. Ultimately, the study demonstrates how AI can recover overlooked historical economies and expand the methodological toolkit for writing more inclusive global economic history.
Invisible Commerce; African Women Traders; Mutual Aid Economies; Historical Network Analysis; Archival AI; Informal Trade Systems
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Clement Tetteh. Invisible Commerce: Using AI to Map African Women’s Trade Networks and Mutual Aid Economies (1870s to 1950s). World Journal of Advanced Research and Reviews, 2023, 18(2), 1475-1488. Article DOI: https://doi.org/10.30574/wjarr.2023.18.2.0861