Rejecting data fundamentalism is central to decolonizing social knowledge

Evidence

Decolonizing data’s role in explaining the social world means rejecting the assumption that only data can explain data—that is, that only quantitative methods based on Big Data methodologies can accurately describe the world from now on. While it should not reject the idea of gathering data as such (for example, for clearly defined social purposes), the evolving project to think together about the consequences of data colonialism must insist on close attention to those “aspects of social life that remain unseen, unheard, uncounted or unacknowledged within prevailing understandings of capitalism,” as Johnna Montgomerie argues. Put differently, our understanding of the social world needs to be rescued from a narrow understanding that equates it with large data sets and abstract models with “only fantastical links to actual human experience or observation.” — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 639

Categorization

  • DEFINE: Defines the anti-data-fundamentalist position at the heart of the decolonial approach to social explanation.
  • XREF: Connects to the attention/surveillance schools’ shared suspicion of quantification, but notes data colonialism’s distinctive insistence on structural/capitalist analysis. — connects to: Social science complicity weakens resistance to data colonialism — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 580; Decolonial data critique can reframe current social realities beyond commodified inputs. — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 352; Unaccountable abstract social knowledge functionally serves data-colonialist capitalism. — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 453 (+4 more)
  • SEED: Could feed an essay comparing data-colonialist critique of data fundamentalism with the attention economy’s critique of surveillance metrics.

Broader Connections