Enhancing Fairness in digital health by improving representation in healthcare data

Over the last 20 years, Artificial Intelligence (AI) has increasingly been applied in healthcare to enhance diagnosis, patient monitoring, and personalized care. However, there is growing concern that AI might worsen existing socio-economic inequalities and biases. This research focuses on improving AI fairness by fostering real-world data collection in Africa, specifically addressing breast and general cancer care in Nigeria.

The study seeks to understand under what conditions patients are willing to share personal data, emphasizing factors like perceived benefits, stigma, and transparency. It also investigates how AI and digital tools can enhance healthcare access and where these technologies can be integrated into patient care. A mixed-method approach is used: interviews and desk research in phase one, followed by quantitative surveys in phase two.

Initial findings reveal significant barriers in Nigeria, including limited AI awareness, poor healthcare access, mistrust, and stigma. Successful initiatives, such as collaborative frameworks between public and private sectors, NGOs, and digital health providers, highlight the potential for enhancing healthcare access and improving data representation.

Researchers

Prof. Yash Raj Shrestha, University of Lausanne HEC (PI),
Prof. Öykü Isik, IMD,
Dr. Zeynep Erden Özkol, ZHAW School of Management and Law,
Katharina Demmel, ZHAW School of Management and Law