AI in the Name of the Common Good -
 Relations of data, AI and humans in health and public sector

In the era of big data and AI, a pressing issue concerns how to implement technologies which holds an enormous potential of improving lives and services for humans and society, while preserving and promoting equality and civil rights of citizens. The possible advantages of AI for medicine, the health and public sector, and the people it serves, are vital. However, the need for accountability is great. Hence, it is crucial to gain understanding of how core values of fairness, accountability and transparency are mediated as well as integrated in the use of AI-supported tools in healthcare or in the public sector in general. A diffused digital society of multiple data sources and data transfers could also affect concepts as transparency, accountability and fairness as well as power relations of actors involved. For technology to fulfill legal and ethical principles and gain societal acceptance, be adopted and trusted, it is of importance to investigate what, and how, information on the use of AI should be provided.

Main questions:

What kind of transparency is envisioned for the use of AI in health sector and medicine and how well could it serve increased knowledge amongst health professionals and patients? What sort of information and explainability is needed to promote implementation?
How does different notions of transparency, accountability and fairness correspond with power relations between data subjects, data collectors and data analysts in the context of health and public sector? Are there specific challenges of transparency, accountability and fairness when applied to the use of registers?

Fairness is crucial for equality of health care - how are inequalities risking to taint register data and hence AI models and their outcome? Are different grounds for discrimination risking to reinforce one another in the use of AI and how can an intersectional framework be deployed to AI in healthcare?