Recent advances in natural language processing (NLP), especially around large pretrained models, have enabled extensive successful applications. However, there are growing concerns about the negative aspects of NLP systems, such as biases and a lack of input from users. This course gives an overview of human-centered techniques and applications for NLP, ranging from human-centered design thinking to human-in-the-loop algorithms, fairness, and accessibility. Along the way, we will cover machine-learning techniques which are especially relevant to NLP and to human experiences.
3 units · Letter or Credit/No Credit
Recent advances in natural language processing (NLP), especially around large pretrained models, have enabled extensive successful applications. However, there are growing concerns about the negative aspects of NLP systems, such as biases and a lack of input from users. This course gives an overview of human-centered techniques and applications for NLP, ranging from human-centered design thinking to human-in-the-loop algorithms, fairness, and accessibility. Along the way, we will cover machine-learning techniques which are especially relevant to NLP and to human experiences.
Offered in Autumn 2026 at Stanford University.