Trustworthy ethics review of medical AI research protocols: developing a research ethics practical guide for ethics review committees

Background

Research Ethics Committees are responsible for assessing the appropriateness of research protocols. The main focus of the reviewing process is to ascertain whether the proposed research meets a set of ethical standards and criteria, such as justice, respect for person and their autonomy, and beneficence, set out in a number of existing ethics research codes and guidelines (e.g. Declaration of Helsinki, CIOMS).

In recent years, and with the acceleration of research to develop medical AI software and applications, RECs are asked to review an ever increasing number of research protocols aimed to develop AI tools for healthcare. However, it is not immediately obvious whether and how existing ethical principles and guidelines ought to apply to AI research projects, and how the review ought to function. This results in RECs either being overcautious with AI research project arbitrarily raising the ethical standards for researchers in this field. Or, they might miss important and ethically sensitive aspects, which could lead to break of trust between the research community, patients/public, and RECs, as well as to reputational damage to responsible institutions (e.g. Universities) if and when things go wrong.

Therefore, there is an urgent need to investigate what a trustworthy medical AI ethics review process should look like. This includes examining whether existing ethical guidelines are appropriate for the ethical review of medical AI research projects, and how ethical guidelines should be understood and applied by RECs on the ground.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

This project will involve review of existing research ethics codes and guidelines, ethical analysis regarding the similarities and differences of medical AI research to other types of data-driven medical research, ethical argumentation to propose relevant ethical principles and develop guidelines for RECs for the appropriate review of medical AI research protocols. The project could also involve some empirical research (e.g. expert interviews), to add to the body of evidence regarding the theoretical and philosophical analysis described above.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

The DPhil candidate will have access to training in basic principles in research ethics, and in empirical research methods.

PROSPECTIVE STUDENT

The ideal candidate will have a Masters degree in bioethics, or other closely related field (e.g. philosophy, ethics), and an interest in research ethics and ethics governance.