IS 611: Advanced Topics in Large Language Models

Contents
This course examines advanced topics in Large Language Models with a primary focus on advanced topics, for example the ethical, social, economic, organizational, and governance implications. The course explores how LLMs are deployed, evaluated, governed, and contested in real-world settings.
Particular emphasis is placed on questions such as bias and fairness, trans­parency and accountability, privacy and surveillance, mis­information and manipulation, intellectual property, safety and misuse, inequalities in access and power, the trans­formation of knowledge work, and the role of LLMs in societies and organisations. The course may also address adjacent topics such as regulation, platform power, sustainability, human-AI interaction, cultural effects, and methodological challenges in studying LLMs in society.
The exercises part of the course deepens the material through case discussions, critical reading of current research, applied analyses, and project-based work.

Learning outcomes
Upon successful completion of this course, students:
* can critically assess the ethical challenges arising from the development and deployment of Large Language Models;
* can analyze the social consequences of LLMs for communication, education, work, public discourse, and institutions;
* can assess risks related to bias, fairness, privacy, trans­parency, safety, misuse, and accountability;
* can apply conceptual and critical tools to examine real-world use cases of LLM-based systems;
* can develop well-founded positions on the responsible design, deployment, and governance of LLMs.

Necessary prerequisites
–

Recommended prerequisites
Prior knowledge of natural language processing, including familiarity with core concepts of modern language models!
Knowledge of machine learning, AI, and computer programming.

Examiner Performing lecturer

Prof. Dr. Markus Strohmaier Prof. Dr. Markus Strohmaier, N.N.