GenAI Tools in Empirical Research

About

Large Language Models (LLMs) and Generative Artificial Intelligence (AI) provide unprecedented opportunities for research and business practice. However, how to integrate them to stimulate research processes is not always straightforward.

This course is dedicated to the use of AI-powered tools in research. It offers an overview of the background of existing LLM models for scientific research and how they can be integrated at different stages of the research process. We will put a specific focus on integrating AI in empirical data collection, namely integrating AI tools in survey-based research and experiments. We will also discuss limitations and caveats of using AI tools for scientific research (ethics, reliability, validity).
This is not a programming course. Specifically, we will not train, develop, or finetune own LLM models, but discuss how existing models can be leveraged for pursuing own research projects. We will practice minimal-coding approaches using LLMs to support multimodal data collection in surveys and experiments

Course leader

Melanie Clegg, Moritz Jörling

Target group

Master | PhD | Postdocs | Professionals

Fee info