Responsible Use of AI in Health Research

The final level focuses on the responsibilities that come with using AI in health research. Learners will consider what information may be shared with AI tools, how privacy and confidentiality should be protected, how bias can affect AI supported work, and how AI use should be documented. The level also covers authorship, acknowledgement, reproducibility and institutional guidance. Learners then apply these principles to a capstone exercise based on a real research project.

Who this level is for

Anyone using AI in health research, including investigators, clinicians, analysts, research managers, ethics committee members, students, journal authors and research institutions. Recommended after Levels 1 to 4.

What you'll learn

• Why responsibility for research decisions and outputs remains with the researcher
• Which types of study information should not be entered into public AI tools
• How privacy, confidentiality and data governance apply when AI tools are used
• How AI systems can reproduce or amplify bias
• How to distinguish appropriate assistance from inappropriate delegation of scientific work
• Principles for authorship, acknowledgement and disclosure of AI use
• How to keep AI supported research workflows reproducible and auditable
• How to develop practical institutional guidance for responsible AI use

You finish with: Your Responsible AI plan + a documented AI use workflow for your own research project.