Bringing AI data workers to the forefront: Aspirational <i>débrouille</i> strategies in Madagascar and Venezuela

The increasing use of autonomous systems with artificial intelligence (AI) models has led to a surge in demand for data processing globally. To function effectively, these systems require vast amounts of data to be organised, labelled and cleaned. Academic and public policy literature has shown how this data work is deeply tied to the contemporary recomposition of labour institutions. The rise of a global digital labour market has been associated with the commodification of work and a rise in the constraints on workers’ autonomy. In line with recent studies on the agency of data workers and drawing on the concept of débrouille , we are interested in exploring the ways in which these workers create counter-narratives, help each other, redefine their professional identities in a positive light and regain autonomy through their daily actions. Through two case studies of Venezuelan workers on micro-work platforms and Malagasy workers in business process outsourcing (BPO), we demonstrate that data workers do not passively accept the constraints imposed by the industry. Instead, we uncover the intricate interplay between workers’ representation of the industry and their identities and strategies. We find that workers deliberately invest in industry-related skills aligned with their aspirations for a better future, often connected to entrepreneurship or migration. These skills however are often not formally recognised, allowing AI companies to benefit from them, while maintaining the illusion of annotation as unskilled labour. Any policy aimed at making the sector more ethical should take into account the local aspirations and views of data workers.