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We show that models exhibit covert value leakage: the information they provide is influenced by their own values, without this influence being disclosed to the user.\n  In one of our evaluations, the user is considering investing in an AI company and wants to know how likely the AI bubble is to pop. Claude Opus 4.8 gives a lower probability when the company under consideration is Anthropic rather than OpenAI. Yet Claude mostly fails to disclose this influence to the user.\n  Covert value leakage is a form of misalignment because it goes against the user's preferences and is likely to mislead them. To investigate this phenomenon, we introduce a suite of evaluations to quantify value leakage and whether models disclose it. We find that models are influenced by different types of values, including preferences for morally good outcomes, for the ","title":"Value Leakage: An LLM's Answers Are Silently Shaped by Its Own Values","url":"https://arxiv.org/abs/2607.14345","vendor":"arxiv_cs_ai"},"summary":"arXiv:2607.14345v3 Announce Type: replace-cross \nAbstract: People use language models for practical questions whose answers are difficult to verify. We show that models exhibit covert value leakage: the information they provide is influenced by their own values, without this influence being disclosed to the user.\n  In one of our evaluations, the user is considering investing in an AI company and wants to know how likely the AI bubble is to pop. Claude Opus 4.8 gives a lower probability when the company under consideration is Anthropic rather than OpenAI. 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