Excavating AI
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About
Excavating AI explores the political complexities and biases embedded in machine learning training sets through images. It highlights the assumptions derived from datasets like ImageNet and juxtaposes the categorization of people with their inherent characteristics. The authors, Kate Crawford and Trevor Paglen, argue that understanding these biases is critical as AI systems increasingly influence societal decisions.
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Task
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• analysis of training datasets
• investigation of bias and representation
• exploration of ai's societal implications
• open-source software available
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