Fairness in the Latin American platform economy: Assessing labor conditions on digital labor platforms

Abstract

The platform economy, particularly digital labor platforms, has experienced significant growth in Latin American countries. These platforms, which facilitate specific labor relations known as platform work (Aloisi and De Stefano, 2022), have seen a substantial increase in user registrations. A survey (Alvarez et al, 2020) estimated that 16% of the population is registered on these platforms, with 9.4% reporting the provision of services through them. This phenomenon was further accelerated in the wake of the COVID-19 pandemic (Katz et al, 2020; Arreaza et al., 2021), underscoring the growing importance of these platforms in the region.

These companies operate in various sectors, including ride-hailing, delivery, and cleaning and care (Griguera and Nava, 2021). The literature has increasingly shedding light on the region (Miguez, 2023; Huepe, 2023) and specific countries such as Chile (Morris, 2021), Brazil (Rebechi et al., 2023), Argentina (Haidar and Garavaglia, 2022), Colombia (Maldonado and Sánchez, 2020), and Mexico (Ortega Herreguerena, 2023).  Among the growing body of literature, a key aspect that has been consistently highlighted is the precarious conditions posed by digital labor platforms in the region (Hidalgo et al., 2020; Bridi et al., 2023).

This paper takes a unique approach in its analysis of the situation of platform work in Latin America, drawing from studies conducted by the Fairwork Project. The project assessed fairness in the platform economy against five principles: pay, conditions, contracts, management and representation (Graham et al., 2020). The methodological framework involves data collected from publicly available sources, surveys with workers and interviews with platform managers (Heeks et al., 2021). From 2020 until 2024, the project has assessed over x platforms in nine countries. The findings reveal how digital labor platforms in the region engineer relations are characterised by low pay, poor health and safety protections, surveillance and unfair decisions in algorithmic management and barriers to workers’ representation.