AURA - Advanced Understanding and Development of AI for Regional Advancement 

In fall 2024 SpareBank 1 SMN announced that they are investing 40MNOK into AI research at NTNU. Over the next five years the funds will support research on responsible AI, combating financial crime, and developing expertise for businesses in Central Norway.

Main goals

1. To create values of artificial intelligence (AI) for the society and the Central Norway region
2. To contribute to innovation within AI systems
3. To increase competence within AI in industry and the public sector in the Central Norway region and among their customers through education, research and outreach

Work packages

The project consists of three work packages: 1. AI for Safety, 2. Responsible AI, and 3. Innovation Hub. Read more about them below.

AI for Safety

Research focus: AI for prevention of white collar crime

Tasks

• Develop a data platform for data generation using generative AI techniques to produce high quality synthetic data.
• Use real-time anomaly detection to highlight activities indicative of money laundering.
• Research detection of generative AI. We will mostly focus on LLMs, but also consider multimodal systems. Further, both white-box and black-box will have a role.
• Dissemination, targeting both the general public as well as NTNU master students.

Potential societal impact

By developing a data platform that generates synthetic data, researchers can share information without exposing sensitive details, promoting faster iterations and innovative research. Existing systems often lack real-time capabilities and suffer from data silos and limited collaboration. New methods using synthetic data can improve the detection of suspicious transactions, preventing financial crimes and reducing risks for financial institutions. Advances in AI, particularly generative AI, can be exploited by fraudsters, making it crucial to stay informed about new threats and educate the public on recognizing manipulation attempts.

You can find more information about our work on AI for Safety here 

Responsible AI

Modern AI systems often make decisions that are difficult to understand. This work package focuses on developing explainable AI (XAI) methods to uncover what AI systems have actually learned, and to identify where they may be relying on shortcuts or flawed reasoning.
By making AI more transparent, trustworthy, and fair, our research supports more responsible and robust use of AI in real-world applications. The goal is to create practical approaches that help both researchers and industry professionals better understand and improve the behavior of AI systems, especially in high-stakes decisions like loan approvals or hiring.
 

Potential societal impact

This research ensures AI systems operate as intended, making it easier to understand and explain their decisions, which helps prevent biases and protect users. XAI research often focuses on making AI understandable for experts rather than laypeople. As AI becomes more integrated into everyday functions, it's crucial for the public to have a basic understanding to make informed decisions about its use. Developing advanced academic subjects is necessary to drive innovation, support research-based teaching, and produce industry-ready graduates.

You can find more information about our work on responsible AI here

Innovation Hub

The Innovation Hub is our bridge between AI research and the people who will use it. By engaging directly with business leaders and employees across the Midt-Norge region, we aim to understand their hopes, concerns, and perceptions of AI. Through surveys, workshops, and collaboration, we explore whether these concerns can be addressed, or if they reveal real challenges that need tailored, Norwegian solutions.
Our work includes an annual AI adoption survey, interactive workshops, and practical tools to help companies measure value and guide AI integration. By combining local insight with research-based strategies, we strive to make AI adoption both effective and culturally grounded, strengthening the competitiveness of regional businesses.
 

Potential societal impact

Annual reports summarizing key trends and developments are crucial for guiding collaboration and providing regional ownership of issues. Through iterative processes like evaluations and co-creation workshops, the goal is to generate research-based knowledge to facilitate AI innovation for local businesses. Involving students in this process will enhance their education and improve recruitment opportunities for local businesses. Developing a roadmap for AI services and understanding AI-driven transformation will help inform organizations and decision-makers.

You can find more information about our work with the Innovation Hub here