Data collection inherently differentiates, and applied to social structures it compounds inequality.

Evidence

The purpose of collecting data is always to differentiate: data’s purpose is to generate information that usefully discriminates between entities. Again, discrimination in itself is not bad: we want a heart recorder that correctly distinguishes between a heartbeat and other bodily signals. The issue is how data discriminations are applied within the framework of existing structures of social discrimination. Today’s vast infrastructures of connection, like all forms of power, build on existing inequality. But they also create new forms of inequality through various means: inequalities of data capital, exploitation of the human labor that sustains Machine Learning, and the ability of data-driven categorizations to reinforce those existing inequalities. Just as the capitalization of work through labor relations has over time produced a highly unequal distribution of the profits generated by labor, so over time we can expect the capitalization of life through data relations to introduce new forms of inequality into human life itself. — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 125

Categorization

• XREF: This generalizes toward ‘capitalization of life’ inequality analogous to labor-capital dynamics; parallels surveillance-capitalism critique in Zuboff yet framed as colonial extraction. — connects to: Privately controlled data extraction produces social classifications that entrench inequality — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 443; Data’s core function is differentiation, which compounds existing social discrimination. — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 125; Data collection itself, not just its uses, harms the self’s integrity — Nick Couldry & Ulises A. Mejias, The Costs of Connection: How Data Is…, 473 (+1 more)
• QUESTION: The extension of labor-capital inequality logic to data relations is asserted prospectively — worth testing against whether data-based discrimination actually hardens over time.

Broader Connections

• Privately controlled data extraction produces social classifications that entrench inequality #corroborates (0.95) — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 443
• Data’s core function is differentiation, which compounds existing social discrimination. #corroborates (0.95) — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 125
• Data processes create a new injustice that is simultaneously social and cognitive. #expands (0.75) — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 609
• Data collection itself, not just its uses, harms the self’s integrity #expands (0.72) — Nick Couldry & Ulises A. Mejias, The Costs of Connection, 473