Gaining Knowledge in a Digital World
Knowledge in the digital age – how is it generated, how is it used, who benefits from it? This research field connects computer science, mathematics, and the natural sciences with the social sciences and humanities.
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The power of digital knowledge: data, AI, algorithms
How do we use AI and algorithms to generate reliable knowledge from data?
Our world today is shaped by digital data – from the economy and politics, to science and research, to everyday life. Researchers in the strategic research field “Gaining Knowledge in a Digital World” study how we create knowledge based on heterogeneous data that are processed using AI and algorithms.
How can we use AI in responsible ways?
Researchers in this field are developing ways to implement AI responsibly, ethically, and efficiently. They are also looking at how digital communication and AI technologies are changing society and the public sphere. They are also interested in the rules and responsibilities that enable a fair and just use of data and digital communication.
How fair and how logical are decisions made by artificial intelligence?
Researchers across all disciplines are working together to advance algorithmic systems and make them more trustworthy. They investigate to what extent AI is transparent, whether or not AI can be explained, and how mistakes or distortions can best be avoided.
What are researchers focusing on?
- The path from data to reliable knowledge: epistemological research, uncertainty, understandability
- Trustworthy and explainable AI: robustness, fairness, transparency, and accountability
- Digital knowledge infrastructures: data quality, curating data and knowledge, reuse, and Open Science
- Practical use for society and social regulation: disinformation, platform power, algorithmic governance
- Intersectoral data provision and big Real-World Data
- Digital science hub: shared equipment and infrastructure for data processing, artificial intelligence (AI), and high-performance computing (HPC)
Collaborative partners in this research area
- Berlin University Alliance: joint infrastructure and collaborative initiatives for data rich research
- Zuse-Institut Berlin: Partner in the shared development and implementation of equipment and infrastructure for data processing, artificial intelligence (AI), and high-performance computing (HPC)
- Charité / AI4Health: Partnerships working on AI-based analyses and use of health data
- Weizenbaum Institute and Berlin Social Science Center (WZB): Addressing questions of social transformation and governance in connection data-driven systems
- Robert Koch-Institut (RKI): Applied solutions related to real-world data and evidence-based research in the public health context
- Haptic Intelligence – Max Planck Institute for Intelligent Systems: New research methods and concepts for algorithms, learning, and data-driven modeling in the Berlin scientific community
Where is this research being conducted?
At Freie Universität Berlin, FUB-IT and the University Library provide central services for researchers dealing with AI and large amounts of data: from HPC (high-performance computing) and GPU resources (graphics processing units) to storage and secure networks. Their services also include consulting, training, and workflows in research data management. The institutional repository Refubium is a service of the University Library of Freie Universität that makes a wide range of publications and data available for the public. Digital tools for research and teaching are also supported through different platforms available to university members. Plans for a digital science hub will ensure an even stronger connection between data, computers, and AI.