Course overview
This course aims to equip students with the knowledge and skills to understand, assess and mitigate the ethical, privacy and security challenges in developing and deploying AI and machine learning systems. Topics covered include bias, transparency, privacy concerns and security risks of AI and machine learning models and techniques, and current legal and regulatory frameworks. The course will also discuss the impact of these challenges and possible mitigating strategies from indigenous perspectives.
- Introduction To Policy
- Ethics
- Introduction To Ai And Ml
- Fundamentals Of Ai And Ml
- Bias
- Transparency And Explainability
- Introduction To Privacy
- Applications Of Privacy
- Security
Course learning outcomes
- Recognise and explain the key ethical challenges such as bias, transparency, privacy and security in the development and deployment of AI and machine learning
- Identify the sources of biases in AI and machine learning systems, select and apply appropriate technologies to eliminate the biases
- Critically evaluate the transparency and explainability of AI and machine learning systems and propose appropriate strategies to enhance the transparency and explainability of the systems
- Examine security vulnerabilities of AI and machine learning systems and select effective defending techniques to safeguard the systems
- Explain and compare different AI ethics principles/frameworks and approaches to AI regulation around the world
Degree list
The following degrees include this course