Study Finds LLMs Create Uneven Visibility for Urban Businesses
A new arXiv preprint audits restaurant recommendations from three major large language models (LLMs) across 304 neighborhoods in five U.S. cities, revealing that these models often fabricate venues and systematically overlook many real establishments. The study finds that nearly half of actual restaurants are never recommended, and that higher-income users tend to receive pricier suggestions. These patterns suggest LLMs may reinforce existing inequalities in urban visibility and economic opportunity.
Why it matters: The findings highlight how widespread use of LLMs for local recommendations could unintentionally amplify urban inequality and reshape economic flows.
Full story at: arXiv Computers and Society ↗