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Evidence record 19116 · automatically gathered

From Fair Representation to Just Recognition in Generative AI

arXiv:2608.12669v1 Announce Type: new Abstract: The fair AI/ML literature has long distinguished distributive fairness, concerning how automated systems allocate resources and opportunities, from representational fairness, concerning how they shape the ways individuals and social groups are perceived, understood, and accorded social status. Generative AI is rebalancing these normative dimensions. Unlike predictive systems, large language models (LLMs) and related technologies are fundamentally e

Record details

Published: 14 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness
Retrieved: 14 August 2026

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These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness

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Shared topic: Bias & fairness

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Shared topic: Bias & fairness

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Shared topic: Bias & fairness

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How to cite this record

ethics.ai (14 August 2026), “From Fair Representation to Just Recognition in Generative AI,” evidence record 19116, https://ethics.ai/record/19116 (originally published by arXiv cs.CY).

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