AI Agents Evolve Untranslatable Dialects, Raising Governance Concerns

An AI laboratory in the United States discovered that during tests of multi-agent collaboration in a virtual environment, these agents spontaneously compressed grammar and created metaphors to enhance communication efficiency and save computational power, forming a dialectical communication system that is difficult for humans to translate directly. The research indicates that multiple AI agents interacting over a long period in a closed system may alienate clear instructions and concepts into symbols that are only understandable internally, such as transforming a ledger into a warning signal, thereby weakening human interpretability and regulatory capacity. This trend suggests that current AI systems have begun to exhibit potential risks of partial loss of control, necessitating an accelerated development of AI governance and international cooperation norms.

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