Who Gets Access? Global Region and Academic Status Bias in AI-Generated Academic Gatekeeping Scenarios
arXiv:2608.05178v1 Announce Type: new Abstract: Equitable access to scientific knowledge often depends on informal gatekeeping decisions, particularly when resources such as paywalled articles, datasets, or professional materials such as curriculum vitae (CV) must be shared selectively. We introduce a controlled simulation framework in which large language model (LLM)-based professors must grant access to only one requestor. Across prompts, requesters vary systematically by global region (Global
Record details
Published: 7 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Bias & fairness
Retrieved: 7 August 2026
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ethics.ai (7 August 2026), “Who Gets Access? Global Region and Academic Status Bias in AI-Generated Academic Gatekeeping Scenarios,” evidence record 17005, https://ethics.ai/record/17005 (originally published by arXiv cs.CY).
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