The Evolution and Ethics of NLP

This chapter explores the major advancements in natural language processing (NLP) from 2017 to 2019, particularly the shift from LSTM models to transformer architectures. It delves into the ethical implications surrounding large pre-trained models, including accessibility, fairness, and the environmental impact of AI research. Additionally, the chapter critically examines attention mechanisms in neural networks, questioning their reliability in providing explanations for model predictions.