Decolonial and post-colonial theories have been embraced by critical data and artificial intelligence (AI) scholars to account for the colonial mechanisms of power that traverse contemporary data relations and explain processes of data extraction and exploitation. This area of research signals the growing significance of viewing the impact of data dynamics through the critical lens of coloniality, decolonial and post-colonial theory. However, to avoid what sociologist Leon Moosavi has called the ‘decolonial bandwagon and the dangers of intellectual decolonisation’, in this intervention I reflect on the key challenges and dangers of decolonization in relation to datafication and data studies in general. Building (among others) on Moosavi (2020), Pappas (2017) and Amrute (2019), I illustrate the difficulties in separating intellectual perspectives and traditions, the tendency to romanticize knowledge from the Global South, and the risk that coloniality may colonize all other categories of analysis of concrete injustices. I conclude highlighting the need for decolonial approaches to critically engage with these challenges and to strengthen the dialogue with other conceptual lenses in pragmatic, flexible and agile ways depending on the research context.

For further reading: Milan, S., & Treré, E. (2019). Big Data from the South(s): Beyond Data Universalism. Television & New Media, 20(4), 319–335. https://doi.org/10.1177/1527476419837739