The Korea Times

Using AI to test policy language

WASHINGTON, DC — Earlier this year, researchers at Anthropic made a remarkable discovery. Studying the internal mechanisms of Claude Sonnet 4.5, the company’s large language model (LLM), they identified what they called “emotion concepts”: internal patterns that correspond to dozens of emotional states and measurably influence the model’s responses in ways that resemble human behavioral patterns. The implications for economic policymaking could be far-reaching. By offering a new way to study how language shapes emotional and behavioral responses, LLMs could help policymakers test how investors, political coalitions, and households are likely to react to policy announcements. Policymakers have long understood that language affects how information is processed. That is why central banks carefully calibrate their forward guidance, while government officials pay great attention to how fiscal-policy and tariff announcements will land with markets and voters. But until recently, there were few tools capable of systematically analyzing how language itself functions as an instrument

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