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Course Information

AI Content Disclaimer

Transparency about how these course materials were created

How These Materials Were Made

The course materials for MAM5020F 2026 have been designed, written, and structured with substantial assistance from AI tools — primarily Claude (by Anthropic). This page explains what that means, what steps have been taken to ensure quality, and what you should do if you find an error.

What AI Was Used For

AI tools were used across the creation of these materials, including:

What Has Been Done to Ensure Quality

Known Risks

Despite thorough review, AI-generated content can contain subtle errors that are difficult to catch. The most common issues include:

  • Hallucinated citations: References that look correct but point to papers that do not exist, or that misattribute findings to the wrong authors or journals.
  • Incorrect statistics: Numbers, percentages, or dates that are plausible but inaccurate — sometimes drawn from the AI's training data rather than verified sources.
  • Broken links: URLs that were valid at the time of creation but may have changed or expired.
  • Oversimplified explanations: Technical concepts that are presented in a way that sacrifices important nuance for clarity.

Why We Are Transparent About This

This course is about generative AI in research. It would be inconsistent — and ironic — to use AI in creating the course materials without being open about it. We believe that:

A Note on Practicing What We Teach

Week 5 of this course covers the hallucinated citation crisis and teaches students to verify every AI-generated reference. The creation of these very materials encountered exactly this problem — several statistics and citations generated by AI during the drafting process turned out to be incorrect and had to be corrected. This experience directly informed the content of the verification exercises we ask students to complete.

Found an Error?

If you spot a broken link, an incorrect citation, a wrong statistic, or any other error in these materials, please email jonathan.shock@uct.ac.za. Corrections are welcomed and will be made promptly. You are also welcome to open an issue on the course GitHub repository.