How to Manage Misinformation in Large Language Models

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How to Manage Misinformation in Large Language Models

Article Published February 25, 2026

This article originally appeared on Tech Policy Press on February 25, 2026.

By Leah Ferentinos, Nonprofits In an Age of Policy Change alum, and Omri Tubiana, Arushi Saxena, J.J. Martinez-Layuno, and Chris Miles

Search engines and other information retrieval tools that utilize large language models (LLMs) are growing rapidly. But their dependence on online data introduces a critical vulnerability: the open internet is now a highly adversarial space, where distinguishing fact from falsehood is incredibly difficult. From state-backed influence campaigns to commercial content farms, many actors are attempting to shape what LLMs “learn,” and thus what they portray as “facts.” These distortions—ranging from fraudulent financial content to coordinated political manipulation—pose growing risks to the epistemic and ethical integrity of AI systems and the greater information ecosystem.

Read the Full Article

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