AI Pluralism and the Worlds It Misses
AI pluralism is often framed as a problem of representing diverse values, preferences, users, or outputs. This paper argues that this framing is incomplete because AI systems also impose ontologies: they define what counts as an entity, relation, feature, harm, benefit, and valid form of evidence. We define ontological flattening as the conversion of situated, contested, and historically specific meanings into a restricted technical category, proxy, aggregation rule, or benchmark target that is
Record details
Published: 15 June 2026
Source: arXiv
Category: Research
Topics: unclassified
Retrieved: 14 July 2026
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ethics.ai (15 June 2026), “AI Pluralism and the Worlds It Misses,” evidence record 980, https://ethics.ai/record/980 (originally published by arXiv).
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