Learning Outcomes:
Students will immerse themselves in the complex intersection of AI and ethics through engaging online lectures and activities. This will include:
1. Engagements with multimedia presentations covering key AI ethics and auditing topics, incorporating videos, audio clips, and interactive elements to enhance learning.
2. Asynchronous online discussion forums to facilitate peer-to-peer interaction and debate on ethical issues in AI, allowing students to share perspectives and engage in critical dialogue.
3. Modularised content to allow students to progress through the course at their own pace, accessing materials and completing assignments according to their schedules.
4. Scheduled virtual office hours with instructors to allow students to seek clarification, ask questions, and receive personalised guidance.
5. Access to online resources such as scholarly articles, books, and websites to supplement course materials and support students’ independent research.
Indicative Module Content:
Divided into three components, the module will begin by focusing on ethical considerations in AI development, addressing privacy, bias, and discrimination issues, and exploring solutions such as regional regulations and technical approaches.
The second component delves into AI’s societal impact, discussing its effects on democracy, education, the economy, and the environment while addressing concerns about job displacement and economic inequalities.
The final section emphasises auditing AI systems for transparency, accountability, and ethical use, providing practical skills in defining audit scopes, assessing data quality and biases, evaluating model performance, and understanding regulatory frameworks.