AI chatbots struggle with dialect fairness
As AI spreads into public services and commerce, studies warn that dialect speakers may receive poorer responses and unfair treatment from chatbots compared with standard language users.
Researchers are warning that AI chatbots may treat dialect speakers unfairly instead of engaging with them neutrally. Studies across English and German dialects found that large language models often attach negative stereotypes or misunderstand everyday expressions, leading to discriminatory replies.
A study in Germany tested ten language models using dialects such as Bavarian and Kölsch. The systems repeatedly described dialect speakers as uneducated or angry, and the bias became stronger when the dialect was explicitly identified.
Similar findings emerged elsewhere, including UK council services and AI shopping assistants that struggled with African American English.
Experts argue that such patterns risk amplifying social inequality as governments and businesses rely more heavily on AI. One Indian job applicant even saw a chatbot change his surname to reflect a higher caste, showing how linguistic bias can intersect with social hierarchy instead of challenging it.
Developers are now exploring customised AI models trained with local language data so systems can respond accurately without reinforcing stereotypes.
Researchers say bias can be tuned out of AI if handled responsibly, which could help protect dialect speakers rather than marginalise them.
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