Photography and the Framing of the Orient

Photography arrived in the Middle East almost immediately after its invention. By the 1840s, European travelers and colonial officials were carrying cameras to Egypt, Palestine, and the Ottoman Empire, producing images that would define Western perceptions of the region for generations. But these were not neutral documents. The photographers chose what to include and what to exclude, what to stage and what to ignore. Markets were made to look timeless. Women were posed as exotic. Ancient ruins were framed as evidence of civilizational decline. The “Orient” that emerged in these photographs was a construction — a visual argument about backwardness, mystery, and otherness that served the political interests of European empires.

What made photography so powerful as a tool of Orientalism was its claim to objectivity. Unlike painting, which everyone understood as interpretation, photography presented itself as mechanical truth. The camera, the argument went, simply recorded what was there. This made photographic representations of the Middle East enormously difficult to contest. If the photograph showed a veiled woman in a dusty alley, then that must be what the Middle East looked like. The ideological work of framing — the choice of subject, angle, lighting, caption — was hidden behind the apparatus.

This history is directly relevant to how AI image generation systems operate today. When Midjourney or DALL-E produces an image of a “Middle Eastern city,” it draws on training datasets that are themselves saturated with these inherited visual tropes. The AI does not see the Middle East — it reproduces the Middle East as Western archives have represented it. Kate Crawford’s work on excavating AI training data reveals how these datasets encode the biases of their sources, creating feedback loops that amplify historical misrepresentations rather than correcting them.

The question is not whether AI image generators are biased — of course they are. The question is whether we can see the framing at work, or whether the technology’s claim to computational objectivity makes its biases, like those of the nineteenth-century camera, invisible.