Beyond Correlations: Leveraging Generative AI for Causal Machine Learning

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Type and Duration

FFF-Förderprojekt, November 2024 until October 2026

Coordinator

Data Science & Artificial Intelligence

Main Research

Humanities, Cultural and Social Studies

Description

This project seeks to address the significant limitations of deep learning (DL) models in causal explainability and robustness in out-of-distribution contexts by exploring the integration of Generative AI (GenAI) into Causal Machine Learning (CML). The project focuses on leveraging GenAI to identify highlevel, causally relevant variables and formulate causal hypotheses, addressing challenges that currently require expert intervention or costly experimental procedures. Through a series of targeted work packages, the project will develop and evaluate a scalable CML pipeline incorporating GenAI, with applications in diverse domains such as healthcare, policy-making, and finance. The anticipated outcomes include ad-vancements in causal inference methodologies and contributions to both academic literature and practical applications.

Project Manager

Arianna Casanova Flores, Ph. D.

Project Collaborator

Assoz. Prof. Dr. Johannes Schneider