Introduction to AI tools in human health research

Date: tbc

Modality: In-person

Duration: One day, 9:00am-2:30pm

Price: $276 (incl. GST).  If you are eligible for the UoA Staff discount, please email shortcourses@auckland.ac.nz.

Delivered as part of the 2026 Human Health Research Week (HHRW), this practical, in-person course helps researchers confidently and safely bring AI into their daily work.

While new AI tools offer exciting ways to speed up health research, they also require a fresh set of skills to use responsibly.  This session guides participants through the process of choosing the right AI tools for their specific research goals, identifying and addressing risks, and navigating the regulatory and approval pathways. 

By learning how to set up simple "human-in-the-loop" safety checks, participants will leave equipped to keep humans firmly in control, ensuring their research always protects patient safety and maintains the highest standards of accuracy.

Course structure and topics covered:

• Why AI literacy is essential in health research.
• Introduction to the types of AI and how these can be used to support health research.
• Exploration of the technical and ethical differences between different types of AI models.
• Consideration of risks of AI in research and identification of strategies to mitigate these.
• Navigating the current national and international frameworks, policies, and laws that impact health data and the use of AI in research.
• Design of "Human-in-the-Loop" Safety Protocols.

Learning outcomes:

By the end of the course, you will be able to:

• Critically evaluate AI models in health research: Analyse the technical and ethical differences between various types of AI to determine the most appropriate tool for specific health research objectives.
• Appraise and mitigate algorithmic bias and data inequity: Identify potential sources of bias within training datasets or health research datasets, and strategies to mitigate these to ensure research outputs are equitable.
• Navigate the legal and regulatory landscape: Apply current national and international frameworks, policies and laws to the lifecycle of an AI-driven research project.
• Design "Human-in-the-Loop" safety protocols: Develop robust validation frameworks to detect and correct AI errors to ensure that the integration of AI in research maintains the highest standards of patient safety and data integrity.

Who should attend?

Anyone interested in the use of AI in health research, including researchers of all levels.

Payment for short courses is normally by credit card. If you need to pay by invoice or require assistance, please email shortcourses@auckland.ac.nz. Please note the University does not issue individual invoices for amounts less than $500 New Zealand dollars. 

By enrolling in a Short Course at the University of Auckland you agree to the Short Course Terms and Conditions