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This lecture explores the ethical considerations in designing Natural Language Processing (NLP) systems, focusing on biases, toxicity, and privacy concerns. It delves into the potential harms of language models, such as leaking private information and spreading disinformation. The instructor discusses the classification of harms from language models, including discrimination, exclusion, and misinformation. Moreover, the lecture addresses the challenges of bias amplification, model training, and the implications of hidden biases in large-scale NLP models.
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