Work

Fairness in crowdwork: Making the human AI supply chain more humane

Year: 2024

Type: article

Abstract: The vast quantities of data required to build artificial intelligence (AI) technologies are often annotated and processed manually, making human labor a critical component of the AI supply chain. The workers who input this data are sourced through digital labor (“crowdwork”) platforms that often are unregulated and offer low wages, raising concerns about labor standards in AI development. Using the results of a survey, this article aims to shed light on the experiences and perceptions of fair treatment among workers in the AI supply chain. The study reveals significant variability in workers’ experiences, identifies potential drivers of fairness, and highlights how design choices by labor platforms can significantly affect worker welfare. Drawing on lessons from physical supply chains, this article offers practical guidance to managers on how to enhance worker welfare within the AI supply chain and how to ensure that AI technologies are responsibly sourced.

Source: Business Horizons

DOI: 10.1016/j.bushor.2024.09.003

Authors: Martin Gonzalez-Cabello, Auyon Siddiq, Charles J. Corbett, Catherine Hu

Institution: University of California, Los Angeles

Language: English

Topic: Digital Economy and Work Transformation

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDGs: Decent work and economic growth, Reduced inequalities

Open Access status: hybrid

Estimated APC paid: $3,410