Generative AI in Public Policy

Project Goals

Through Generative AI in Public Policy, we aim to introduce students to the meaningful and responsible use of Generative AI in public policy analysis while strengthening their quantitative research skills. We seek to improve learning outcomes by offering personalized and AI-supported learning experiences, encouraging self-directed learning, and fostering collaborative and problem-based approaches. At the same time, we place strong emphasis on critical reflection, enabling students to assess the reliability, limitations, and ethical implications of AI-generated outputs. 

Project Funding

In 2025, Dr. Hasnain Bokhari, Head of Digital Policy and AI at the Brandt School, was awarded a state grant by the Thuringian Ministry of Education, Youth and Sport through the program "Fellowships for Innovation in Digital Higher Education in Thuringia." This program aims to incentivize the development and testing of digitally supported teaching and examination formats, such as MOOCs, blended learning, games, simulations, e-exams, and the use of AI. It also encourages the redesign of modules and study sections with the integration of digital technologies to facilitate cross-university exchange on innovative university teaching practices.

Activities

The project combines digital teaching formats with hands-on learning experiences. These include:

• interactive workshops on Generative AI, large language models, and prompt engineering

• developing Moodle-based self-study courses supported by instructional video tutorials for R programming. 

• Datathons 

In project-based learning settings, students critically evaluate AI-supported analyses and actively contribute by producing their own digital learning materials. These activities are complemented by exchanges with external partners working in the field of generative AI, connecting academic learning with practical applications.