In using new technologies to manage health crises, personal data is potentially collected and used to either make better informed decisions directly or as an input for a machine learning environment. The collection and processing of such personal data raises many ethical questions, such as protection of private information, fairness, accountability and interpretability. This research aims to develop an ethical and legal framework and possible machine learning strategies that can be used in managing health pandemics such as COVID-19 or HIV.

Key research questions undertaken in this one-year exploratory project are: What are the socio-ethical considerations when generating and processing personal data in health-related settings in terms of privacy, fairness and agency? What are the shortcomings of current approaches? What are the elements of a legal framework for AI-based epidemic management models and how could this be used in different jurisdictions in the world? Moreover, what are possible machine learning strategies that could be applied in managing major health crises based on an ethical and legal framework acceptable within a constitutional democracy?

Research Output:

TRAIF – Parallel Session: AI & Covid-19