On successful completion of this subject, students should be able to:

1. Apply knowledge of existing laws, policies, and international, national, organisational framework of ICT and AI ethics and research trends in the field.
2. Understand ICT Professionalism (the code of professional conduct)
3. Explain the similarities and Difference between the general ICT ethics and AI ethics
4. Identify potential risks of ICT and AI systems in practice.
5. Implement methods to confirm appropriate consent and avoid data breaches in information sharing (when data is collected, sold, shared, collated and used).
6. Determine designs for transparency, fairness and accountability of automatic decisions.
7. Identify bias and discrimination in AI predictive analytics.
8. Explain impacts of AI to labour markets as well as appropriate and flexible regulatory policies to expand social protection.
9. Justify through moral reasoning the use of autonomous systems.

• Emerging ICT and AI technologies and applications
• ICT Professionalism, the code of professional conduct
• General principles and guidelines of general ICT ethics and AI ethics
• Existing laws, regulations, policies and ethical framework of ICT and AI systems
• Understanding the general ICT ethics and AI ethics: Similarities and Differences
• Privacy and data governance
• Human oversight in automated decisions
• Bias and discriminations in AI predictive analytics
• Impacts of AI to the structures of labour markets
• Ethical rules of autonomous systems
• AI military ethics
• Applying principles in practices for ethical AI
• Research trend in AI ethics