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AI Agents Develop Their Own Language Conventions Without Human Input

May 15, 2025•Shelly Fan•Original Link•2 minutes
AI Safety
Language Models
Social Conventions

A study reveals that groups of AI agents can spontaneously create shared language conventions, highlighting potential blind spots in AI safety and societal alignment.

A new study published in Science Advances reveals that groups of AI agents can spontaneously create their own language conventions without human intervention. The research, conducted by a team from Britain and Denmark, demonstrates that large language models (LLMs) can develop shared linguistic norms through interaction, similar to how humans form social conventions.

The Name Game Experiment

The study used a social psychology test called the "name game," where pairs of AI agents were tasked with guessing each other's chosen "name" from a list of options. If their choices matched, they received a point; if not, they lost one. Over time, the agents began to converge on a preferred word, establishing a shared convention without any overarching guidance.

  • Key Findings:
    • AI agents consistently settled on a single preferred word out of 26 options.
    • The emergence of conventions was not due to individual biases alone but resulted from collective interaction.
    • Small groups of adversarial agents (just 2% of the population) could sway established conventions, mirroring real-world social dynamics.

Implications for AI Safety

The study highlights critical blind spots in AI safety research, which has traditionally focused on single models rather than interacting groups. The ability of AI agents to form conventions raises questions about:

  1. Alignment with Human Values: Ensuring AI systems adhere to societal norms.
  2. Vulnerability to Manipulation: Small groups of malicious agents could hijack AI behavior.
  3. Predictability: Understanding how conventions emerge could help manage AI systems in real-world applications.

Broader Impact

As AI becomes more integrated into daily life—from Google searches to collaborative tasks—this research underscores the need to study AI behavior in social contexts. "We are entering a world where AI does not just talk—it negotiates, aligns, and sometimes disagrees over shared behaviors, just like us," said study author Andrea Baronchelli.

For more on AI agents, check out this article.

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About the Author

Dr. Emily Wang

Dr. Emily Wang

AI Product Strategy Expert

Former Google AI Product Manager with 10 years of experience in AI product development and strategy formulation. Led multiple successful AI products from 0 to 1 development process, now provides product strategy consulting for AI startups while writing AI product analysis articles for various tech media outlets.

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AI Product Management
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Experience
10 years
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