Unit Saarbrücken

This ELLIS Unit will research the foundational algorithmic solutions needed to enable systems capable of such new functionalities and design new algorithms for high trustworthiness, controllability, and explainability. Our research approach is characterized by its holistic nature and we will address two major key research objectives: Understanding, Anticipation, and Explanation as well as Privacy, Trust, and Transparency.

The SAM Principal Investigators have agreed to jointly work on both the foundations for enhanced functionalities of Artificial Intelligence and Machine Learning (AIML) systems and the pressing needs for security, privacy, and trustworthiness that arise from the widespread use of Artificial Intelligence and Machine Learning systems. Future Artificial Intelligence and Machine Learning systems will capture reality through a multitude of sensors, interact with humans, derive knowledge, and influence our lives. These systems need to be based on accurate and robust models of the physical and digital worlds as well as on powerful methods for perception and knowledge inference to cope with the complexity of the real world. They will make autonomous decisions and enable enhanced functionalities, e.g., for personalized assistants, immersive multi-person platforms, and autonomous systems. This ELLIS Unit will research the foundational algorithmic solutions needed to enable systems capable of such new functionalities.