Where does AI come from? A global case study across Europe, Africa, and Latin America

TL;DR

This study explores the global organizational and geographical factors shaping AI data work supply chains across Europe, Africa, and Latin America, highlighting inequalities and structural differences in employment conditions.

Contribution

It provides a comparative analysis of AI data work supply chains in France, Madagascar, and Venezuela, integrating sociological and economic theories to reveal patterns of inequality and organizational structures.

Findings

AI supply chains use a mix of marketplace and embedded firm structures.

Exclusionary practices disproportionately affect Global South workers.

Different supply chain structures impact remuneration and job security.

Abstract

This article examines the organisational and geographical forces that shape the supply chains of artificial intelligence (AI) through outsourced and offshored data work. Bridging sociological theories of relational inequalities and embeddedness with critical approaches to Global Value Chains, we conduct a global case study of the digitally enabled organisation of data work in France, Madagascar, and Venezuela. The AI supply chains procure data work via a mix of arm's length contracts through marketplace-like platforms, and of embedded firm-like structures that offer greater stability but less flexibility, with multiple intermediate arrangements. Each solution suits specific types and purposes of data work in AI preparation, verification, and impersonation. While all forms reproduce well-known patterns of exclusion that harm externalised workers especially in the Global South, disadvantage manifests unevenly in different supply chain structures, with repercussions on remunerations, job security and working conditions. Unveiling these processes of contemporary technology development provides insights into possible policy implications.