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Volume 648 Issue 8092, 4 December 2025
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Volume 648 Issue 8092, 4 December 2025

Photo realism

From autonomous vehicles to facial recognition, computer vision is key to many applications involving artificial intelligence. But the visual data used to train AI models are frequently problematic — many data sets use images scraped from the Internet without consent, which often feature inaccurate metadata and show poor diversity. To address this issue, Alice Xiang and colleagues at Sony AI present an image data set created using best practices for consent, privacy, compensation, safety, diversity and utility. Called the Fair Human-Centric Image Benchmark (FHIBE, pronounced ‘Feebee’), the data set includes 10,318 images of 1,981 people from 81 distinct countries or regions. Because FHIBE has comprehensive annotations for a wide range of attributes, from demographics to hair and skin colour, the researchers say it can be used to evaluate fairness and bias in AI models.

Cover image: Sony AI.

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