Ethical Aspects of Using Generative AI in Healthcare Software Applications

This research investigates the ethical challenges associated with generative AI applications in healthcare. It highlights issues such as data privacy, algorithmic bias, transparency, and accountability, all of which influence both the reliability of AI systems and public trust. We aim to develop a comprehensive ethics framework by incorporating insights from healthcare professionals.

This research aims to collect and analyse the insights, experiences, and perspectives of healthcare professionals, researchers, and software engineers regarding the ethical challenges posed by using Al, particularly generative Al in healthcare software applications.

These insights will inform the development of a comprehensive ethical framework that addresses key issues such as data privacy, algorithmic bias, transparency, accountability and patient safety. The framework will serve as a foundation for improving existing ethical guidelines and ensuring the responsible implementation of Al technologies in healthcare software applications.

Project Lead

Dr Chetan Arora

Project Team

Yutan Huang, Dr Tanjila Kanij, Dr Anuradha Madugalla

Publications

Huang, Y, Arora, C., Huong, W.C. Kanij, T., Madugalla, A., Grundy, J.C. Ethical Concerns of Generative AI and Mitigation Strategies: A Systematic Mapping Study, Applied Soft Computing, Elsevier    PDF