Responsible Innovation and Social Knowledge in Artificial Intelligence
RISK-AI
The project involves five partners from Norway, Denmark, Finland and Latvia, including universities, research centres and hospitals.
Funders
Project information
Project duration
-
Funded by
Other International
Project funder
Funding amount
320 525 EUR
Project coordinator
Other university or unit
Contact information
Project leader
- Professor, 6G enabling sustainable society, Digital Health
Contact person
Other persons
- Doctoral Researcher
- ProjektikoordinaattoriElina Salla
Researchers
Project description
RISK-AI is a Nordic–Baltic collaboration about using artificial intelligence responsibly in healthcare. In a highly digitalised region facing pressures such as ageing populations and resource constraints, the project responds to the new EU AI Act and the push to bring AI into everyday clinical practice.
We introduce the concept of Responsible Risk to help organisations understand and manage the clinical, social and organisational risks associated with AI tailored to both the organisation and the maturity of each AI tool.
Main project website: RISK-AI
Project actions
Through two clinical use cases in Norway and Latvia, using the validated MAS-AI framework, and through targeted training of healthcare professionals and other stakeholders, RISK-AI aims to support trustworthy and safe adoption of AI in healthcare.
Project results
- Conceptualise “Responsible Risk” as a way to connect responsible AI principles with risk-based regulatory requirements in healthcare RISK-AI.
- Map and analyse governance models in the Nordic–Baltic region to understand how organisations respond to the AI Act and manage AI-related risks.
- Define thresholds for acceptable clinical risk and identify coping strategies for healthcare professionals and organisations when implementing AI tools in practice.
- Extend and update the MAS-AI framework (Model for Assessing the value of AI) by integrating Responsible Risk into its ethical and legal dimensions.
- Pilot the updated MAS-AI framework in real-world clinical use cases in Norway and Latvia, assessing AI technologies at different stages of their lifecycle.
- Build capacity and competence among policymakers, clinicians and other stakeholders through training, co-design workshops and practical tools for AI risk assessment and governance.