Artificial Intelligence is shaping critical areas of society, but ensuring fairness, transparency, and trust remains a challenge. Our master seminar, "Trustworthy AI," explores key issues such as bias detection, intersectional fairness, and explainability in AI systems. We address bias in AI-driven decision-making, particularly in critical areas like credit scoring, which is classified as a high-risk application context by the AI Act, and examine methods to enhance fairness. A crucial focus is on developing transparent AI models and understanding how explanations influence trust in automated systems. Additionally, we analyze large language models, their limitations, and innovative retrieval methods such as GraphRAG, which enhance knowledge representation in AI.

This seminar is offered by the newly established Information Systems III research group headed by Prof. Dr. Jella Pfeiffer at the Institute for Information Systems (WIN). To learn more about us, please visit our website (WIN - Information Systems III).