Journal article published on AI & Society on labour exploitation in AI training

New article published on open access licence on Springer’s AI & Society journal. In the article we analyse the exploitative practices of technology companies that exploit the labour of unwitting workers to train AI systems.

The unwitting labourer: extracting humanness in AI training
Fabio Morreale, Elham Bahmanteymouri, Brent Burmester, Andrew Tzer-Yeu Chen, Michelle Thorp

Many modern digital products use Machine Learning (ML) to emulate human abilities, knowledge, and intellect. In order to achieve this goal, ML systems need the greatest possible quantity of training data to allow the Artificial Intelligence (AI) model to develop an understanding of “what it means to be human”. We propose that the processes by which companies collect this data are problematic, because they entail extractive practices that resemble labour exploitation. The article presents four case studies in which unwitting individuals contribute their humanness to develop AI training sets. By employing a post-Marxian framework, we then analyse the characteristic of these individuals and describe the elements of the capture-machine. Then, by describing and characterising the types of applications that are problematic, we set a foundation for defining and justifying interventions to address this form of labour exploitation.