Excavating AI
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About
Excavating AI is an online tool and research project that explores the political and social implications of datasets used to train AI systems. It focuses on the biases and assumptions embedded in image datasets, demonstrating how these datasets reflect and perpetuate societal inequalities. The tool includes ImageNet Roulette, an interactive experiment allowing users to upload images and see how they are classified by an AI model trained on ImageNet's 'person' categories, highlighting the problematic and offensive labels present. The research explores several datasets such as ImageNet, JAFFE, UTKFace, and IBM's Diversity in Faces, analyzing their taxonomies, categories, and individual labeled images to reveal underlying biases. The project serves as a critical examination of AI's inherent social and political dimensions.
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Task
Features
• data analysis
• image classification
• face detection
• archeological analysis of datasets
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