Important Course Caveats
Contents
Before we dive into the exciting world of generative AI for research, it's essential to establish some ground rules and expectations. These caveats will help frame how you should approach the course content and apply what you learn to your own research practice.
The ideas here are helping map out a landscape of possibilities and shouldn't be seen as the rules that you should follow.
You need to abide by the regulations of your department, your course and your supervisor.
Things change day by day in this field, so this is going to be a co-creation project.
You are going to need to stay actively involved to make this really productive.
Remember: This course is a pilot, and we're navigating uncharted territory together. Bring your questions, your skepticism, and your curiosity. Challenge assumptions, share what works (and what doesn't), and help shape how AI can be used responsibly and effectively in research.
Drafted with Claude (Anthropic) and reviewed by Jonathan Shock before publication. AI-generated errors are possible — if you spot one, please email jonathan.shock@uct.ac.za. Full detail: AI Content Disclaimer.
© 2026 Jonathan Shock · MAM5020F: Generative AI for Research · CC BY 4.0