60 https://www.uni-bremen.de/en/csl/projects/current-projects/finance-meets-artificial-intelligence Finaces meets artificial intelligence en University of Bremen Thu, 13 Aug 2026 08:01:17 +0200 Thu, 13 Aug 2026 08:01:17 +0200 University of Bremen content-636774 Tue, 25 Feb 2025 14:05:37 +0100 https://www.uni-bremen.de/en/csl/projects/current-projects/finance-meets-artificial-intelligence#c636774 <p>How can millions of pieces of data be automatically bundled and processed to train algorithms while protecting sensitive content and preserving the privacy of those affected? <br /> We would like to address these tasks with the topic of AI-based text processing while preserving privacy and data protection (privacy-preserving natural language processing), because a large proportion of user data comes from natural language, such as search and chatbot queries, call centers, call notes, (automatic) transcriptions of telephone calls, voice assistants, as well as text-based information such as emails, documents and websites, to name just a few. It is therefore essential to curate NLP datasets that preserve user privacy and train machine learning models that only store non-identifying user data.</p> <p>The main methods and challenges here are:</p> <p>1. Personal information detection, i.e. how to automatically find those words or phrases in texts that contain personal user information</p> <p>2. Privacy-preserving text analysis, i.e. how to integrate differential privacy methods and homomorphic encryption methods into automatic text analysis</p> <p>3. Privacy-enhancing technologies, i.e. how to integrate and improve data protection and privacy in current AI methods.</p> <p>Host: Prof. Dr.-Ing. Tanja Schultz</p> <p>Contact person: Lily Meister</p> Content