This comprehensive chapter on ethical considerations in NLP with Transformers explores critical issues such as bias and fairness, privacy concerns, and responsible AI practices. It delves into theoretical concepts like disparate impact metrics for measuring bias, privacy-preserving techniques in NLP models, and practical implementations using the transformers library. By emphasizing transparency, accountability, and ethical guidelines, the chapter aims to foster responsible AI development and deployment in NLP.

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