NLP-CS: Case Studies in Responsible Natural Language Processing
Welcome to Case Studies in Responsible Natural Language Processing
Learning Outcomes
On completion of this course, the student will be able to:
- critically evaluate the literature on legal, social, and ethical aspect of NLP
- working with partners, analyse legal, social, and ethical implications of deploying NLP technology across various application domains
- design potential solutions to legal, social and ethical problems, combining engineering and design thinking
Course Outline
This course will enable students to practice responsible research and innovation in action. They will reflect on their learning in areas of legal, social, and ethical aspects of AI and NLP and put this learning into practice by working on case studies on responsible NLP. The course will have an interdisciplinary outlook, and the case studies will be provided by the industry partners of the CDT. Example topics include:
- fairness and bias
- social issues of model deployment
- impact of AI and NLP technology on the workplace
- data privacy, copyright, and other legal implications of NLP
- translation of ethical and moral values to technical systems
- political influence and manipulation with the help of AI and NLP
- generative AI and the creative industries
The students will engage in two main activities: (1) student-lead seminars in which students present topics in responsible NLP based on the courses they've taken in year 1; (2) partner presentations introducing case studies on responsible NLP; each student will select one of these case studies and work with the partner on an analysis of that case study, drawing on their knowledge from the first part of the course.
This is a course-work only course; the students will be assessed on their seminar presentations and on a report of their case study analysis.