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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.

Platform

Keywords

machine learning ai training image analysis dataset politics data bias

Task

Features

• analysis of training datasets

• investigation of bias and representation

• exploration of ai's societal implications

• open-source software available

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