Computational Universalism, or, Attending to Relationalities at Scale.

Area of Science:

• Social Sciences
• Humanities
• Computational Studies

Background:

• Increasing adoption of computational terminology in social sciences and humanities.
• Risk of obscuring universalizing practices by focusing on vernacular computational objects (e.g., data, algorithms, AI) and specific domains (e.g., finance, health, governance).

Purpose of the Study:

• To problematize the uncritical adoption of computational categories in research.
• To highlight how these categories can act as epistemic traps, naturalizing computational universalism.
• To propose an alternative approach focusing on the labor of translation and commensuration.

Main Methods:

• Critical analysis drawing on intellectual traditions that question universalizing claims.
• Examination of how computational actors establish relationalities across scales and boundaries.
• Focus on the processes of translation and commensuration enabling computational interventions.

Main Results:

• Computational categories can obscure the universalizing ambitions of computation.
• These categories naturalize the expanding reach of computational universalism.
• An alternative approach reveals both the achievements and the exclusions/partialities of computational relationalities.

Conclusions:

• Scholars should move beyond accepting hardened computational categories.
• Attending to the effortful work of translation and commensuration offers a more nuanced understanding.
• This perspective illuminates the labor behind computational universalism and its inherent limitations.