AI safety tests lag behind for African languages
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Researchers created TUKABENCH, a new test to check how safely AI language models respond to prompts in seven African languages.
Current AI safety checks mostly focus on English, leaving other languages, especially those with fewer digital resources, less studied. The team tested models with prompts translated from an existing English benchmark, prompts adapted to fit African cultures, prompts created directly by people, and prompts mixing English and African languages.
They found that AI models were more likely to respond to harmful prompts in African languages than in English. Culturally adapted prompts triggered the most responses. The researchers also identified problems with how well the AI understood the prompts and with using AI itself to judge the responses in these languages.
To address these issues, the team introduced a new way to measure when a model avoids answering a question, and they used people to verify the AI’s judgements, finding less agreement between human reviewers and the AI in African languages.
