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AI LEARN aims to address the complexities of hybrid intelligence by combining theoretical and empirical research on how humans interact with AI. The centre will develop interdisciplinary knowledge and insights to promote responsible and trustworthy human–AI interactions aligned with Nordic sociocultural values.

By developing frameworks for designing and evaluating human–AI interaction models and critically examining emerging moral and ethical dilemmas in the context of hybrid intelligence, the centre will drive sustainable innovation and enable democratic participation in the evolving AI society.

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Leads: Professor Ìý(Centre for the Science of Learning & Technology - SLATE, ÐÒÔË·Éͧ¼Æ»®) and Professor (NTNU).

Local authorities, news media, engaged citizens and researchers are all essential to a healthy local democracy. With growing financial pressure and some signs of declining public trust, both public administration and the press are turning to AI. However, they face major obstacles: technological limitations, complex regulations, and a shortage of specialised expertise.

Led by Professor (Department of Information Science and Media Studies), the Insight centre proposes groundbreaking AI research to support local governance and empower citizens to hold decision-makers accountable—while maintaining a strong focus on privacy and trust.ÌýRead more about Insight.

Algorithmic decision-making (ADM) is already used in areas such as medical diagnostics and fraud detection. While highly effective, ADM processes — like all software — are limited to processing raw facts and lack societal context. Human decisions, on the other hand, involve moral judgement, cultural sensitivity, and empathy. Relying solely on automated systems could therefore lead to unforeseen long-term consequences.

SEAIR will explore ADM processes and tackle key questions around:

• Algorithms used to train predictive models
• Uncertainty and causality
• ADM in the form of AI agents interacting with humans
• Digital twins for testing, integration, and monitoring
• Value-oriented design of algorithms, models, and agents

The centre aims to expand the research frontier and establish a leading hub for AI research that puts people first. It also seeks to attract students and professionals to Norway’s AI landscape. Read more about SEAIR.

Leads: Professor (Department of Information Science and Media Studies) and Professor (Department of Informatics).

Artificial intelligence and machine learning have the potential to transform how we understand and respond to climate change. By integrating physical models with data-driven approaches, AI can improve the accuracy of weather and climate forecasting, reduce computational costs, and make climate data more accessible to decision-makers. It can also deliver robust and explainable tools for extreme weather prediction.

Understanding how and why algorithms produce specific results is essential for trustworthy climate-related decisions, says Associate Professor (Geophysical Institute and the Bjerknes Centre for Climate Research), who will lead the centre in collaboration with partners from both the public and private sectors, in Norway and abroad.ÌýRead more about RAISE-UP.

By combining traditional climate science with cutting-edge AI, the centre aims to provide faster, more accurate, and locally tailored information — crucial for climate adaptation and extreme weather preparedness.

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