Topics in Language and Artificial Intelligence

More generally, students will develop the ability to work with theoretical and empirical research questions, analyze and evaluate partial answers to these questions, while concurrently devising novel hypotheses and methodologies to test these. In addition, students will further develop their skills of reading research literature, and academic presentation and writing. 

A 'topics' course is a course where students acquire specialized knowledge concerning a specific topic within a wider theme and where they acquire the specific skills needed to conduct research concerning this topic. 

‘Topics in Language and AI’ provides in-depth inter-disciplinary discussions of areas where linguistic theory is relevant to AI and/or approaches in AI are relevant to linguistic theory. The focus will be on acquiring theoretical and technical knowledge, as well as developing the appropriate digital skills, to enable doing research in this area. 

Representative topics for this course include: data annotation, for instance for a specific linguistic topic or phenomena, as relevant for quantitative training or evaluation of models, syntax or semantics and parsing, qualitative analysis and evaluation of current AI models. Contact the course coordinator if you want information about this year's topic in advance.