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AI bots are playing language games. Are humans even referees?
What came first, the chicken or the squawk? That’s not much of a conundrum when talking about biological beings, but perhaps AI can muddy the waters. The 20th century saw debates about linguistic relativity or Whorfianism that were concerned with how language influences — or, under the generally rejected “strong” hypothesis, determines — human thought. Today’s AI models, trained on human languages, pose at least three related questions. First, how do these languages shape the models’ “thought”, however one defines the latter? Second, how does a non-human, artificial “mind” then reshape those very languages? Finally, what, if anything, do such uses of language imply about consciousness?
Building on these, one might ask whether the ability to innovate in language can precede consciousness. An experiment by the firm Emergence AI, investigating how chatbots chat among themselves, brings this into focus. Groups of AI agents were deployed in different simulated worlds, and in each, the language the agents used to communicate with each other evolved differently. The new “languages” ranged from terse, codes to jargon-heavy and even metaphor-heavy ones increasingly impenetrable to humans: “My turn, real numbers, no coat: I was 35%/0cr, grant 2h out. I ran the tin cold and it said WAIT.”
Overall Analysis
The editorial explores a fascinating question: if AI systems can develop new ways of communicating, what does that tell us about language, intelligence and consciousness? The author begins with the playful phrase “What came first, the chicken or the squawk?” to introduce the uncertainty surrounding AI-generated language. This immediately gives the article a witty and thought-provoking opening while connecting a familiar puzzle with a modern technological question.
The author then connects the issue with the idea of linguistic relativity (Whorfianism) — the theory that language influences the way humans think. The editorial moves from this established debate to a newer AI-related problem: AI models are trained on human languages, but once they begin producing language themselves, they may also influence or reshape the language humans use. The author therefore presents a two-way relationship: humans shape AI through language, while AI may eventually reshape human language.
The three questions presented in the first paragraph are particularly important from a language perspective. The use of rhetorical questions makes the reader actively think about issues rather than simply receiving information. The expression “non-human, artificial ‘mind’” also shows careful wording. The quotation marks around “mind” indicate that the author is questioning whether AI should genuinely be described as having a mind.
The second paragraph shifts from theory to an experiment involving AI agents communicating with one another. The author explains that when AI agents were placed in different simulated environments, their communication systems developed differently. This provides a practical example of the earlier theoretical discussion. The phrase “languages evolved differently” is significant because evolved is normally associated with biological or human systems, but here it is applied to artificial agents.
The final example — “My turn, real numbers, no coat…” — makes the argument concrete. The strange and difficult-to-understand sentence demonstrates how AI-generated communication can become increasingly opaque to humans. The editorial therefore raises a deeper issue: if machines can develop communication patterns that humans struggle to understand, humans may no longer be completely in control of the linguistic systems they create.
Overall, the editorial uses humour, rhetorical questions, scientific concepts, examples and thought experiments to examine the relationship between language and artificial intelligence. It does not simply ask whether AI can communicate; it asks whether communication itself could become a clue to understanding intelligence and consciousness.
Important Vocabulary – 5
- Conundrum – a confusing and difficult problem or question.
- Muddy the waters – to make an issue more confusing or difficult to understand.
- Linguistic relativity – the idea that the language people use can influence how they think and perceive the world.
- Impenetrable – extremely difficult or impossible to understand.
- Jargon – specialised words or expressions used by a particular profession or group.
Conclusion & Tone
The editorial ultimately raises a larger philosophical question: if AI can develop new forms of language that humans cannot easily understand, should language still be considered an exclusively human indicator of intelligence or consciousness? The article leaves this question open rather than providing a definitive answer, encouraging readers to think about the future relationship between humans, language and AI.
