Natural Language Processing for Law and Social Science

This course explores the application of natural language processing (NLP) techniques to texts in law, politics, and the news media.

NLP technologies have the potential to assist judges and other decision-makers by making tasks more efficient and consistent. On the other hand, language choices could be biased toward some groups, and automated systems could entrench those biases.

We will explore the use of NLP for social science research, not just in the law but also in politics, the economy, and culture. We will explore, critique, and integrate the emerging set of tools for debiasing language models and think carefully about how notions of fairness should be applied in this domain.

Students will be introduced to a broad array of tools in natural language processing (NLP). Topics include text classification, topic modeling, transformers, model explanation, and bias in language.

Requirements:
Some programming experience in Python is required, and some experience with NLP is highly recommended.

Course Project:

This is the optional course project for "Natural Language Processing for Law and Social Science".

Please register only if attending the lecture course or with consent of the instructor.

Some programming experience in Python is required, and some experience with text mining is highly recommended.