Ethics in Natural Language Processing

Ethics in Natural Language Processing

Teaching Staff

  • Prof. Dr. Iryna Gurevych
  • Dr. Thomas Arnold
  • Erik Kaiser

We currently do not have fixed office hours, so please contact us by mail to get an appointment.


  • IMPORTANT NOTE: The course will take place in accordance with the adjusted schedule and modalities for the summer term (Covid-19 pandemic effects). Thus, the below dates are subject to change.
  • Lecture: Thursday 09:50-11:30, starting April 23. Lecture videos will be uploaded in moodle course.
  • Practice class: Thursday 11:40-13:20, starting April 30. Practice class organisation will be announced in moodle.

The learning material is available from the Moodle eLeaning platform.


If you plan to participate in this course, please register on Tucan.


To pass, each student has to take the written exam at the end of the semester.

There will also be homework assignments in the practice class which will contribute to your overall grade.


  • Date/Time: (not fixed yet)
  • Room: To be determined

Course content

Machine Learning and Natural Language technologies are integrated in more and more aspects of our life. Therefore, the decisions we make about our methods and data are closely tied up with their impact on our world and society. In this course, we present real-world, state-of-the-art applications of natural language processing and their associated ethical questions and consequences. We also discuss philosophical foundations of ethics in research.

Processing of unstructured web content

  • Introduction
  • Philisophical Foundations, History
  • Bias and Misrepresentation
  • Incivility in Communication
  • Privacy & Security
  • Language of Manipulation


After completion of the lecture, the students are able to

  • Explain philosophical and practical aspects of ethics
  • Show the limits and limitations of machine learning models
  • Use techniques to identify and control bias and unfairness in models and data
  • Demonstrate and quantify the impact of influencing opinions in data processing and news