Research Programme: AI driven Nordic Health and Welfare

Published: 19.01.2021 / Research

AI driven Nordic Health and Welfare is a research programme where AI solutions are applied to social and health care within the Nordic welfare and social design framework, using a transdisciplinary and user driven approach.

The focus in the new research programme

AI driven Nordic Health and Welfare is a research programme where AI solutions are applied to social and health care within the Nordic welfare and social design framework, using a transdisciplinary and user driven approach. We aim to explore ethically sustainable, evidence based, trustworthy and user-friendly AI driven solutions as well as theoretical knowledge in AI as a basis for applying AI in different care contexts.  The focus is on two major global societal issues: functional ability for elderly and work ability for persons with mental health problems. The outcomes of the AI supported and smart solutions, applications, models and services will be assessed from both a quality and user perspective as well as an economic and society level perspective.

AI methods and technical solutions provide new solutions for the health care sector

We aim to develop user-centered approaches to health and welfare technology, using AI methods and technical solutions to health promotion. These technologies will help to maintain or increase safety, activity, participation and independence for a person who has, or runs an increased risk of  health problems.  

We will explore the human aspects on the possibilities of using AI methods and technical solutions in health care services including attitudes, knowledge, promotion, and skills among health care and welfare professionals.  

As a backdrop to the project, we will employ a holistic approach and explore the ethical, economical, organisational and societal aspects on health and welfare technology, i.e. how can we assess the quality and sustainability of health technology and its consequences. This overall framework is called the Nordic welfare and design model.

Expected results of the research programme

The research programme will run until the autumn 2023 and we expect to achieve the following results:

  • developed a transdisciplinary approach in RDI, which utilizes knowledge from various disciplines to establish smart AI solutions in social and health care
  • developed a framework for and strengthened Nordic co-operation in order to become a stronger actor in European and global research          
  • strengthened Arcada's research competence and societal impact through the creation of a long-lasting network with selected universities and organizations
  • created a model for in-depth collaboration with affiliated and visiting researchers and professors as well as experts in working life and thereby strengthened Arcada's RDI network
  • created a model for collaboration with doctoral schools and networks and enabled doctoral studies for our teachers and strengthened our post doc networks. 

 

The research programme consists of six working packages

Each work package has its own focus and work package leader:

Title: Trustworthy AI in Health and Well-being. Focus: Explore ethically sustainable, evidence based, trustworthy and user-friendly AI driven solutions with a transdisciplinary approach. Work Package leader: Magnus Westerlund

Title: Efficient and privacy enabled AI research in different domains. Focus: Develop theoretical knowledge in AI as a basis for applying AI in different care contexts. Work Package 2 leader: Kaj-Mikael Björk

Develop AI-supported and smart solutions, applications, models, services and interventions in the area of health and welfare from different perspectives.

Work Package 3: Leonardo Espinosa, Jukka Surakka; Dennis Biström, AI enabled social robots.

Work Package 4: Jonny Karlsson, Thomas Hellstén, Annikki Arola; Ira Jeglinsky. AI enabled health promotion. Work Package 5: Jonas Tana, Pauleen Mannevaara, Ira Jeglinsky, Camilla Wikström-Grotell, AI enabled health behavior change.  

Work Package 6: Management and dissemination. Camilla Wikström-Grotell, Henrika Franck, Elina Sagne-Ollikainen.

 

Teaching and learning of practical skills in social and health care in challenging times

When communities worldwide were closed in the spring of 2020 as the COVID-19 disease pandemic hit the world, the consequences for higher education in Europe were extensive. In a flash, higher education activities were moved online without enough time for neither preparation nor planning. Both students and the universities' staff had to adapt to major changes in daily life. Follow-ups and evaluations showed that the universities coped with the change surprisingly well, but also that the challenges in teaching and learning were many, both for students and staff – this shows the newly Arcada and Ditepract published Best Practice Guide on the topic.

Pedagogical development work

Can Machine Learning aid in finding key factors to improve the Finnish healthcare system?

Finland is in the process of change in our health care system. The Nordic well-fare system is challenged in Finland, for instance, due to difficulties in attracting nurses, changing demographics in Finland, and a general pressure to reduce costs in the whole public sector. This poses severe challenges for the entire healthcare sector. Can Machine Learning (i.e., the subfield of Artificial Intelligence, which focuses on having a machine imitate intelligent human behavior) be used to understand relationships between different critical properties of our healthcare system? Yes, it can! An excellent example of how this can be done is found in a scientific paper by Hu et al. (2020), where the authors investigated nurses' willingness to report errors in a specific geographical area of the US.

Publication