Sören Auer (TIB – Leibniz Information Centre for Science and Technology and University Library), “Neuro-symbolic AI for Open Science”

Abstract: We explore how neuro-symbolic AI, i.e., combining neural networks with symbolic knowledge representation, can drive the next generation of open, transparent, and responsible scientific research. By combining the adaptability of machine learning with the interpretability of structured knowledge, neuro-symbolic approaches offer powerful tools for enhancing reproducibility, semantic interoperability, and trust in AI-driven science. With examples such as the Open Research Knowledge Graph and TIB’s AI research assistant, we highlight how these methods support machine-readable research outputs, facilitate cross-disciplinary collaboration, and align with the core values of open science, ultimately shaping a more inclusive and accountable research ecosystem.

The talk is part of the 2025 Berlin Summer School on Artificial Intelligence and Society, jointly organized by the Berlin Institute for the Foundations of Learning and Data (BIFOLD), the Weizenbaum Institute for the Networked Society, and Science of Intelligence (SCIoI), will focus on a timely and critical topic: “Open Science and AI – Shaping the Future of Responsible Research.”

Taking place from 15 to 18 September 2025, this year’s Summer School invites early-career researchers and advanced Master’s students to explore how open data, open collaboration, and responsible practices can help build more transparent, fair, and trustworthy AI systems.

Image created with DALL-E by Maria Ott.