11.06.2025
Better Data, Smarter AI: Why Quality Matters – With Frauke Kreuter
Research Film
How does data quality shape the future of AI? Frauke Kreuter, Professor at the Chair of Statistics and Data Science at LMU Munich and MCML PI, shares her insights on the fundamental role of data quality in the development and deployment of AI.
«We can train a system to predict an outcome perfectly, however if the data it’s trained on is not perfect, we’re predicting the wrong thing.»
Frauke Kreuter
MCML PI
In the video, she explains how data influences not only the technical performance of machine learning models, but also their real-world consequences — from the accuracy of navigation apps to fairness in automated decision-making.
This disconnect between training data and real-world application is a critical challenge in AI. Machine learning systems optimise based on the data they receive, but when that data is incomplete, biased, or unrepresentative, the consequences can be far-reaching.
In this video series you can learn how researchers at MCML are working to improve data quality, enhance fairness, and shape more inclusive machine learning systems.
©MCML
The film was produced and edited by Nicole Huminski and Nikolai Huber.
Related
22.07.2026
MCML Welcomes Student Delegation From HEC Montréal
MCML welcomed students from HEC Montréal for discussions on AI research, ethics, and international academic collaboration.
21.07.2026
Timo Heiß Receives Best Student Paper Award at XAI 2026
Timo Heiß receives the Best Student Paper Award at XAI 2026 for research on improving feature effect estimation in explainable AI.
21.07.2026
The Learning Rate Does More Than Set the Pace
New ICML 2026 research by Gitta Kutyniok and her team shows how learning rates balance competing biases that shape neural network generalization.
