AIBearisharXiv – CS AI · 9h ago6/10
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Geographic Bias and Diversity in AI Evaluation
A comprehensive literature review examines geographic bias in AI systems, revealing that foundation models encode structural imbalances in training data that disproportionately favor certain regions while underrepresenting others. The research identifies representation gaps, regional factual recall disparities, and the tendency of generative AI to default to prototypical Western places, establishing measurable benchmarks for evaluating geographic diversity across different model parameters and output types.