Part I: Responsibility & AI

Resources

GenAI Tools

• ChatGPT — OpenAI’s conversational AI
• Claude — Anthropic’s AI assistant
• Gemini — Google’s AI
• Midjourney — Image generation
• DALL·E — OpenAI’s image generation

Regulatory Frameworks

• EU AI Act — European Union’s comprehensive AI regulation
• NIST AI Risk Management Framework — US voluntary framework
• HKU Guidelines on AI — Institutional policies

Cases to Know

Harm & Safety

• Character.AI incidents — chatbot relationships, user harm
• Chatbot manipulation cases — users tricked into harmful actions

Intellectual Property

• Getty Images v. Stability AI — training data copyright
• New York Times v. OpenAI — content reproduction

Deepfakes & Misinformation

• Political deepfakes — election interference concerns
• Non-consensual imagery — legal and ethical boundaries

On Convergence & Creativity

• Murrell, A. (2023). The Age of Average.
  Source Article: [link]
  A clear and accessible account of algorithmic homogenisation, explaining why optimisation-driven systems tend towards sameness. Useful for framing convergence as a structural outcome rather than a creative failure.

• Chiang, T. (2023). ChatGPT Is a Blurry JPEG of the Web. The New Yorker.
  Source Article: [link] | File Upload: [link]
  Influential and widely cited, but technically contested. Critics argue that large language models are better understood as simulators rather than compressors, and that the JPEG analogy mischaracterises how such systems operate. Read critically, focusing on the implications rather than the metaphor.

Academic Integrity

• HKU Academic Honesty Policy
• Your course syllabus and institutional guidelines

A Note

These resources are starting points, not comprehensive coverage.

The landscape changes fast. Cases from six months ago are already outdated.

Your job is to stay aware — not to memorise a static list.