Data Science, Maschinelles Lernen und Künstliche Intelligenz
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Data Science, Machine Learning and Artificial Intelligence

Data Science describes the application of statistical techniques of Artificial Intelligence (AI) and Machine Learning (ML). These techniques have enabled important advances in areas such as machine translation, automated recognition of text and objects in images, and news and video recommendation. At the same time, they have created new risks of influencing users or discrimination against them.

Data Science, Maschinelles Lernen und Künstliche Intelligenz

Exploring socio-technical systems

ifib combines a deep understanding of data science techniques with a comprehensive sensitivity for socially responsible technology design. In addition to developing new algorithms and new ML-based systems, a major focus lays therefore on critically exploring the interactions of AI and ML with societal developments.

Analyzing big data

Our research includes, among other things, the automated analysis of screen videos, the investigation of learning paths (learning analytics), and the automated recognition of specific points in texts. In the process, we analyze how data science methods can support research data management in collaborative projects.

Designing user experiences in AI systems.

Another focus of our work is how ML-based systems can be explained and visualized in the best possible way. In addition to critically reflecting on the opportunities and risks, ifib investigates what in the user experience of these systems matters. The focus is on how recommendation systems for news and videos can be improved and how users can be supported in recognizing misinformation, such as fake news.