The Efficiency Costs of Information Assurance in AI-Enabled Labor Markets: Evidence from LinkedIn's Policy Changes
arXiv:2511.01923v2 Announce Type: replace Abstract: Generative artificial intelligence (GenAI) systems rely heavily on user-generated data for training. As governments and platforms impose increasing restrictions on the use of personal data, an important question is whether limiting access to user data for AI training affects the performance of AI-enabled economic systems. We examine this question in the context of labor-market matching. Our setting exploits a unique sequence of LinkedIn policy
Record details
Published: 16 July 2026
Source: arXiv cs.CY
Category: Research
Topics: Regulation · Jobs & economy
Retrieved: 16 July 2026
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How to cite this record
ethics.ai (16 July 2026), “The Efficiency Costs of Information Assurance in AI-Enabled Labor Markets: Evidence from LinkedIn's Policy Changes,” evidence record 10548, https://ethics.ai/record/10548 (originally published by arXiv cs.CY).
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