ELSA AI lab Northern Netherlands (ELSA-NN)

ELSA AI lab Northern Netherlands

Responsible development and implementation of human-centric AI in healthcare
Responsible development and implementation of human-centric AI in healthcare
The ELSA AI lab Northern Netherlands (ELSA-NN) is committed to the promotion of healthy living, working and ageing. By investigating the ELSA (Ethical, Legal and Societal), cultural and psychological aspects of the use of AI in different decision-making contexts and integrating this knowledge into an online ELSA tool, ELSA-NN aims to contribute to knowledge, development and implementation of trustworthy human-centric AI.

ELSA-NN will be integrated within the Data Science Center in Health (DASH)AI hub Northern-NetherlandsHealth Technology Research & Innovation Cluster (HTRIC) and Population Health Data NL. They offer a solid base and infrastructure for the ELSA-NN consortium. ELSA-NN is a quadruple-helix consortium consisting of knowledge institutions, societal partners, business partners and patient and public organisations. ELSA-NN will be set-up as a learning health system in which much attention will be paid to dialogue, communication and education.

Specific focus will be on investigating low social economic status (SES) perspectives, since health disparities between high and low SES groups are growing world-wide, including in the Northern region and existing health inequalities may increase with the introduction and use of innovative health technologies such as AI.


Use cases and work packages

By focusing on 3 use cases, ELSA-NN will examine the use of AI in different decision-making contexts. The four use cases (genetic data, monitoring data, personal health data, synthetic data) encompass different forms of data and AI applications in different contexts in the field of healthy living, working and aging. In this way, ELSA-NN expects to generate a broad overview of ELSA aspects.

The ELSA-NN objectives, including generating an overview of ELSA aspects concerning the implementation of AI in healthcare, will be achieved through a number of interconnected and synergistic activities, which are divided in work packages (WP), with their own deliverables and milestones.

    • This use case focuses on the improvement of programmatic newborn screening (NBS) using genetic data. 
    • The huge number of samples (~170,000/year) and the need to report results within hours, make the use of AI-based variant interpretation programs neccessary.

    Use case leaders: Imke Christiaans and Marielle van Gijn

    • This use case focuses on the use of AI during the working period of the life course and in an employee-employer decision-making context.
    • ELSA aspects of the AI application developed in the project ‘healthy living as a service’ will be investigated. 

    Use case leaders: Claudine Lamoth and Bart Verkerke

    • The synthetic use case will investigate the development and implementation of synthetic data in healthcare.
    • Specific focus will be on three medical imaging applications currently under developed in the UMCG. 

    Use case leaders: Peter van Ooijen

  • 01-06-2022 - 01-06-2027

    • Engage public and patients from the Northern region in the development of ELSA-NN activities
    • Explore the needs, knowledge, (digital) health literacy, attitudes and values of the public and patients regarding AI.

    Work package leaders: Mirjam Plantinga and Petra Steenbergen.

  • 01-06-2022 - 01-06-2026

    • Enhancing ethical competency/literacy of all stakeholders involved in applying AI tools in healthy living, working and ageing decision-making contexts. 
    • Developing input for ethics by design guidelines and principles by generating and mapping a practical overview of moral understandings of different stakeholders developing and using AI and by identifying stakeholders’ responsibilities to ensure reliable and trustworthy AI in healthcare.

    Work package leaders: Els Maeckelberghe and Christoph Jedan 

  • 01-06-2022 - 01-06-2022

    • Perform a data-protection impact assessment (DPIA) for the proposed processing of personal data for each use case. 
    • Develop input for privacy by design guidelines and principles by generating and mapping the legal frameworks that apply in the different use cases, identify the validity, completeness and quality of datasets, algorithms and AI outcomes, and terms and conditions for decision-making, interventions and self-management by patients versus automated decision making and profiling.

    Work package leader: Jeanne Mifsud Bonnici 

  • 01-06-2022 - 01-06-2026

    • Investigate socio-political and regulatory considerations in countering health and digital disinformation, with specific focus on low SES perspective.
    • Provide input for how (different) socio-political factors and regulatory incentives may influence: trust in AI, willingness to participate in health research, and digital health literacy and health disparities at individual and societal level, therewith contributing to an increase in understanding regarding willingness to share data, trust in AI, digital health literacy and health disparities.

    Work package leaders: Jeanne Mifsud Bonnici and Ritumbra Manuvie

  • 01-06-2022 - 01-06-2022

    • Investigate use and performance of AI from a psychological perspective by examining (drivers of) acceptance of AI by end users (patients, health care professionals and the general population) and evaluating AI applications from the perspective of end users (patients, employees, health care professionals) including its role in decision making. 
    • Enhance understanding of which information should be offered to potential users of AI applications (and how) including which information should be included in training of professionals on the use of AI.

    Work package leaders: Adelita Ranchor and Maya Schroevers 

    • Study the use of art as a means to engage with AI.
    • Enable, organise and evaluate art-scientific collaboration within the context of different ELSA-NN use cases to explore, understand and extend existing research processes integrating computer-based technologies, especially AI applications.

    Work package leaders: Anke Coumans and Judith van der Elst

  • 01-06-2024 - 01-06-2027

    • Integrate the knowledge related to the concepts of availability, use and performance in an online ELSA tool for trustworthy and human centred AI.
    • Test the ELSA tool for trustworthy and human centred AI within the use cases and among stakeholders in the Northern region to evaluate if the developed ELSA tool sufficiently guides users to the process of AI and ELSA aspects, in different decision-making contexts in the fields of healthy living, working and ageing.

    Work package leaders: Claudine Lamoth and Hilbrand Oldenhuis

  • 01-06-2024 - 01-06-2027

    • To disseminate the ELSA-NN results in order to enhance knowledge about the ELSA issues involved when developing and implementing trustworthy AI to promote healthy living, working and ageing.

    Work package leaders: Peter van Ooijen and Frank Schröer

  • 01-01-2023 - 01-01-2026

    • Learn from and integrate knowledge from international use cases in ELSA-NN. 
    • Stimulate international cooperation between researchers from ELSA-NN, CPM and CELS.

    Work package leaders: Anneke Lucassen and Lisa Ballard

  • 01-03-2022 - 01-06-2027

    • To contribute to and learn from the ELSA-labs learning community and disseminate the ELSA knowledge generated in ELSA-NN to the ELSA-labs learning community and integrate the knowledge generated in other ELSA-labs within ELSA-NN.

    Work package leaders: Mirjam Plantinga and Frank Schröer



Mirjam Plantinga
Mirjam Plantinga Doctor of Economics, Ethics and Sociology, Project Leader ELSA lab Northern Netherlands, Data Science Center in Health

If you have any questions, queries or requests, please contact Mirjam Plantinga ([email protected]), project leader of ELSA-NN.