Project: Ethical Artificial Intelligence

Artificial intelligence (AI) in general and natural language processing (NLP) in particular are often employed in real-life scenarios that deal with sensitive data about humans. The decisions and behavior of respective AI systems therefore may have ethical consequences, such as a potentially unfair treatment related to a potentially unfair treatment of individuals or groups of people. This lab deepens the practical understanding of statistical methods from AI and NLP for ethically sensitive problems, such as the analysis and mitigation of social bias and media bias as well as the computational framing of argumentative and explanatory text. Participants will develop, implement, and evaluate respetive computational methods, in order to learn how to work towards more ethical AI systems in real-life scenarios.

• Recap of general python programming concepts
• Sophisticated development and evaluation tasks on NLP methods to ethical-AI problems
• In between, introduction and discussion of the problems

• Basics of statistics
• Knowledge of programming, ideally Python
• Any course on machine learning or artificial intelligence
• Bachelor's course: Introduction to Natural Language Processing

• Daniel Jurafsky and James H. Martin. 2009. Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics. Prentice-Hall, 2nd edition. Free draft of third edition: Speech and Language Processing

• The maximum number of participants is 30.