"New study examines how a helpful AI response could become a cultural disaster in Iran. If an Iranian taxi driver waves away your payment, saying, "Be my guest this time," accepting their offer would be a cultural disaster. They expect you to insist on paying-probably three times-before they'll take your money. This dance of refusal and counter-refusal, called taarof, governs countless daily interactions in Persian culture. And AI models are terrible at it."
"New research released earlier this month titled "We Politely Insist: Your LLM Must Learn the Persian Art of Taarof" shows that mainstream AI language models from OpenAI, Anthropic, and Meta fail to absorb these Persian social rituals, correctly navigating taarof situations only 34 to 42 percent of the time. Native Persian speakers, by contrast, get it right 82 percent of the time. This performance gap persists across large language models such as GPT-4o, Claude 3.5 Haiku, Llama 3, DeepSeek V3, and Dorna, a Persian-tuned variant of Llama 3."
"A study led by Nikta Gohari Sadr of Brock University, along with researchers from Emory University and other institutions, introduces "TAAROFBENCH," the first benchmark for measuring how well AI systems reproduce this intricate cultural practice. The researchers' findings show how recent AI models default to Western-style directness, completely missing the cultural cues that govern everyday interactions for millions of Persian speakers worldwide. "Cultural missteps in high-consequence settings can derail negotiations, damage relationships, and reinforce stereotypes," the researchers write. For AI systems increasingly used in global contexts, that cultural blindness could represent a limitation that few in the West realize exists."
AI language models struggle to reproduce taarof, a ritualized Persian pattern of refusal and insistence that signals politeness. Major models handle taarof correctly only 34–42% of the time, while native Persian speakers succeed 82% of the time. The performance gap appears across GPT-4o, Claude 3.5 Haiku, Llama 3, DeepSeek V3, and Dorna. A benchmark called TAAROFBENCH measures AI performance on taarof scenarios. Models tend to default to Western directness, risking negotiation failures, damaged relationships, and reinforced stereotypes in cross-cultural or high-stakes interactions governed by ritual politeness.
Read at Ars Technica
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