Visual Orientalism in the AI Era: From West-East Binaries to English-Language Centrism

Text-to-image AI models systematically encode geopolitical bias through visual representation. Drawing on Said's Orientalism and framing theory, we introduce Visual Orientalism -- the dual standard whereby AI depicts Western nations through political-modern symbols while portraying Eastern nations through cultural-traditional symbols. Analyzing 396 AI-generated images across 12 countries and 3 models, we reveal an evolution: Visual Orientalism has shifted from traditional West-versus-East binaries to English-language centrism, where only English-speaking core countries (USA and UK) receive political representation while all other nations -- including European powers -- face cultural exoticization. This algorithmic reconfiguration of Orientalism operates through automated framing mechanisms shaped by the material conditions of AI development: English-language training data dominance and the concentration of AI development in English-speaking tech companies. Our findings demonstrate how AI systems function as agents of cultural representation that perpetuate and intensify historical power asymmetries. Addressing Visual Orientalism requires rethinking of algorithmic governance and the geopolitical structures embedded in AI training data.