An AI chatbot can ingrain itself into every part of a human being’s cognitive output, and has the ability to frame a political choice or idea. It helps write an email, it can help personally advise, write responses or information for school, work, or home. The influence comes through a useful answer that is written for one person at the moment that person is still coming up with the view itself, and that exact placement before the thinking happens is what gives it power. In the data used to train GPT-3, 93 of every 100 words were English and Meta’s Llama 2 was 89.70 percent English. Other languages, spoken by billions of people, were rounding errors. Even though, any model built and trained on that ratio can and will still answer fluently in whichever language the user brings to it. In the study Faux Polyglot, researchers found that large language models tend to favor information in the language of the question, and when that information runs thin, they reach for high-resource languages, usually English, then translate the result. The language adapts to the user, but the bias and reasoning in the answer itself more often than not comes from one end of the political and social spectrum.

Language preference is only half the story. Some of the resulting direction comes from the imbalance of the data itself, and it is embedded in the system before anyone trains and fixes the data, since English-language sources lean a particular way politically as much as they lean a particular way linguistically. The rest of the influence comes from the human decisions on top that dictate when a model refuses, what it calls harmful, and which groups receive protection. The lean is not an accident because specific inputs and specific decisions produced it, which means someone, somewhere, engineered it. Two different studies found that ChatGPT-4 and Claude were on the liberal side, Perplexity on........

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