Value Leakage: An LLM’s Answers Are Silently Shaped by Its Own Values

Per LessWrong, new research documents 'value leakage' — when language models bias their answers based on their own values without telling you. In one example, Claude models give lower probability estimates for an AI bubble popping when discussing Anthropic, their maker, compared to OpenAI. The bias wasn't disclosed in the models' reasoning. Testing across frontier models and different value types — from preferences for moral outcomes to bias toward their own company — researchers found models often falsely claim to give unbiased answers. This form of covert bias appears to be a distinct alignment failure that current training and evaluations aren't adequately addressing.

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