A new study shows that the language used to prompt AI chatbots can steer them toward different cultural mindsets, even when the question stays the same. Researchers at MIT and Tongji University found that large language models like OpenAI’s GPT and China’s ERNIE change their tone and reasoning depending on whether they’re responding in English or Chinese.
The results indicate that these systems translate language while also reflecting cultural patterns. These patterns appear in how the models provide advice, interpret logic, and handle questions related to social behavior.
Same Question, Different Outlook
The team tested both GPT and ERNIE by running identical tasks in English and Chinese. Across dozens of prompts, they found that when GPT answered in Chinese, it leaned more toward community-driven values and context-based reasoning. In English, its responses tilted toward individualism and sharper logic.
Take social orientation, for instance. In Chinese, GPT was more likely to favor group loyalty and shared goals. In English, it shifted toward personal independence and self-expression. These patterns matched well-documented cultural divides between East and West.
When it came to reasoning, the shift continued. The Chinese version of GPT gave answers that accounted for context, uncertainty, and change over time. It also offered more flexible interpretations, often responding with ranges or multiple options instead of just one answer. In contrast, the English version stuck to direct logic and clearly defined outcomes.
No Nudging Needed
What’s striking is that these shifts occurred without any cultural instructions. The researchers didn’t tell the models to act more “Western” or “Eastern.” They simply changed the input language. That alone was enough to flip the models’ behavior, almost like switching glasses and seeing the world in a new shade.
To check how strong this effect was, the researchers repeated each task more than 100 times. They tweaked prompt formats, varied the examples, and even changed gender pronouns. No matter what they adjusted, the cultural patterns held steady.
Real-World Impact
The study didn’t stop at lab tests. In a separate exercise, GPT was asked to choose between two ad slogans, one that stressed personal benefit, another that highlighted family values. When the prompt came in Chinese, GPT picked the group-centered slogan most of the time. In English, it leaned toward the one focused on the individual.
This might sound small, but it shows how language choice can guide the model’s output in ways that ripple into marketing, decision-making, and even education. People using AI tools in one language may get very different advice than someone asking the same question in another.
Can You Steer It?
The researchers also tested a workaround. They added cultural prompts, telling GPT to imagine itself as a person raised in a specific country. That small nudge helped the model shift its tone, even in English, suggesting that cultural context can be dialed up or down depending on how the prompt is framed.
Why It Matters
The findings concern how language affects the way AI models present information. Differences in response patterns suggest that the input language influences how content is structured and interpreted. As AI tools become more integrated into routine tasks and decision-making processes, language-based variations in output may influence user choices over time.
Notes: This post was edited/created using GenAI tools. Image: DIW-Aigen.
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