Summary and Schedule
This course aims to:
- Identify potential ethical and legal issues relating to the use of GenAI platforms for research
- Identify implications relating to IP and copyright relating to GenAI platforms development and use
- Articulate how use of GenAI may interact with research integrity
- Discuss the implications of GenAI for learning and skill building
- State considerations that help to make an informed decision about when, where, or if to use GenAI for coding
- Some exposure to embedded LLMs or chatbots
- An awareness of existing issues
- Unlikely to be aware of licensing and copyright
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. Introduction |
Why might a paper be retracted? How do paper retractions relate to integrity? What do we mean by research integrity? |
| Duration: 00h 33m | 2. Rigour and Transparency |
What is open source AI? What are the limitation on explainability? What do I need to declare about my use of Gen AI when publishing my work? |
| Duration: 01h 23m | 3. Respect and Accountability |
Why is there concern about the environmental impacts of GenAI? What is a data worker? What influences the output from a GenAI tool? What are the IP and data protection considerations when using GenAI tools? |
| Duration: 02h 23m | 4. Implications for Learning |
What is a shallow approach to learning? What is a deep approach to learning? How does the use of GenAI for coding impact learning? How can GenAI be used as a tool to support critical coding rather than a shortcut? |
| Duration: 02h 43m | 5. Summary | What have we learned so far? |
| Duration: 03h 33m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
No setup is needed.