COMP4901M Artificial Intelligence Ethics, Spring 2020, HKUST

Dekai Wu |

Course organization



All lectures and tutorials will be held ONLINE LIVE INTERACTIVELY at the regularly scheduled times until further notice due to university coronavirus measures.

You can find the recurring Zoom meetings for the lectures in Canvas. You are highly recommended to join the meetings from there. Note that these Zoom meetings only admit authenticated users with ITSC accounts (with domain or You can only join the meetings via either of the two paths above.You must register for the lectures at the following links. After registering, you will receive a confirmation email containing information about joining the meeting.

After you are registered, you may use the following links to join the lectures:

If you haven’t done so, please watch this video to get your HKUST Zoom account ready as soon as possible, not just for this course but also for all other courses at HKUST:

Times and places

Lecture 1: M 12:00-14:50, G009B (CYT Bldg).

Office hours: M 15:00-16:00. The TA's office hours are posted at


Course: is the master home page for the course.

TA: contains all information from the TAs.

Forum: is where all discussion outside class should be done. Always read before asking/posting/emailing your question. Note that you must register for your account at the first lecture, tutorial, or lab.


Course description

This course critically surveys the fast moving, urgent, emerging area of AI ethics. AI is explosively disrupting every sphere of our work and lives. Cambridge Analytica and fake news bots. AI driven social media displacing traditional journalism. Drone warfare. Elimination of traditional jobs. Privacy-violating advertising. Biased AI decision/recognition algorithms. Deepfakes. Autonomous vehicles. Automated hedge fund trading. No area remains untouched. Policy think tanks, governments, and tech companies around the world have started paying serious attention to AI ethics. How will human civilization survive the rise of AI? What are the new rules? What are the ethical frameworks needed to avoid extinction? What are engineers’ and entrepreneurs’ ethical responsibilities?

Learning objectives

At the end of the Artificial Intelligence Ethics course, you will have achieved the following outcomes.

  1. Be able to demonstrate comparative understanding of frameworks for AI ethics, including IEEE Ethically Aligned Design
  2. Be familiar with the many types of misuse of AI technology
  3. Be able to analyze the limits of deontological rule-based AI ethics in newly arising scenarios
  4. Be conversant with consequentialist AI ethics, well-being metrics, and AI for social good
  5. Be familiar with the role of virtue AI ethics
  6. Be able to demonstrate critical understanding of embedding values into autonomous systems and artificial moral cognition
  7. Be able to articulate the ethics of emotional AI, empathetic AI, and affective computing
  8. Be conversant with the foundations of responsibility and accountability of AI and machine learning systems
  9. Be able to contrast alternative views on transparency and explainability in AI systems
  10. Be alert to the dangers of weaponization of information and exploitation of unconscious biases
  11. Be able to design systems to avoid algorithmic bias and discriminatory outcomes
  12. Be familiar with approaches of personal data rights and individual access control, and the risks of surveillance capitalism
  13. Be able to articulate issues within autonomous weapons
  14. Be conversant with issues of AI safety in coming eras of strong AI and artificial superintelligence



Honor policy

To receive a passing grade, you are required to sign an honor statement acknowledging that you understand and will uphold all policies on plagiarism and collaboration.


All materials submitted for grading must be your own work. You are advised against being involved in any form of copying (either copying other people's work or allowing others to copy yours). If you are found to be involved in an incident of plagiarism, you will receive a failing grade for the course and the incident will be reported for appropriate disciplinary actions.

University policy requires that students who cheat more than once be expelled. Please review the cheating topic from your UST Student Guide.

Warning: sophisticated plagiarism detection systems are in operation!


You are encouraged to collaborate in study groups. However, you must write up solutions on your own. You must also acknowledge your collaborators in the write-up for each problem, whether or not they are classmates. Other cases will be dealt with as plagiarism.


Course grading will be adjusted to the difficulty of assignments and exams. Moreover, I guarantee you the following.

Grade guarantees
If you achieve 85% you will receive at least a A grade.




Your grade will be determined by a combination of factors:

Grade weighting
Exams 0% (due to university coronovirus meaures)
Pop quizzes
Class participation ~15%
Forum participation ~10%
Assignments ~65%


No reading material is allowed during the examinations. No make-ups will be given unless prior approval is granted by the instructor, or you are in unfavorable medical condition with physician's documentation on the day of the examination. In addition, being absent at the final examination results in automatic failure of the course according to university regulations, unless prior approval is obtained from the department head.


Science and engineering ⁠— not only ethics and humanities⁠ — is about communication between people. Good participation in class will count for approximately 15%, and good participation in the online forum will count for approximately 10%.


All assignments must be submitted by 23:00 on the due date. Assignments will be collected electronically using the automated CASS assignment collection system. Late assignments cannot be accepted. Sorry, in the interest of fairness, exceptions cannot be made.

Assignments will account for a total of approximately 65%.

Required readings

Any linked material (unless labeled "Supplementary references") is required reading that you are responsible for.


Each week we cover a different aspect of AI ethics and society, with the class structured in two halves.

The first half begins with a short provocation such as a TED talk, to create a controversial context for discussion and debate. We then review the relevant literature, illuminate major concepts, and critique them. The first half finishes with a questionnaire/quiz that tests your understanding and poses self-reflection challenges.

The second half exercises these concepts. We may do case studies, breakout groups, collaborative mind mapping, and other interactive work to help concretize, explore, and internalize the issues and challenges. Individual contributions to these exercises over the course of the semester are a large part of the assessment for the course.


wk date topics IEEE goals assignment notes
The soft side of software
Course organization
IEEE goal of accountability: what's the responsibility and accountability of an ML designer, an ML professional teacher, an ML end user teacher, and an ML end user operator? IEEE objective of legal frameworks for Stuart Russell, Don Howard, Patrick Lin and George Bekey

20200302 The biggest fear in AI Ethics is fear itself
Information disorder and social disruption

How does AI know good from evil?
Unconscious bias, inductive bias, and algorithmic bias

20200316 Artificial children
AI ethics methodologies
IEEE foundation of methodologies to guide ethical research and design

20200323 Can an AI really relate?
Weak AI, strong AI, and superintelligence

20200330 Artificial mindfulness
Conscious AI
IEEE goal of transparency, IEEE objective of transparency and individual rights

20200406 Why rule-based AI ethics will fail
Prescriptive/descriptive and deontological/consequentialist/virtue AI ethics
IEEE goal of human rights

20200413 The illusion of explainability
Artificial moral cognition
IEEE foundation of embedding values into autonomous systems

20200420 Artificial gossips
Privacy, safety, security
IEEE objective of personal data rights and individual access control

20200427 Artificial storytellers
AI framing and narratives

20200504 Are machines more creative than humans?
Constructive and creative AI

20200511 Artificial intimacy
Empathetic AI
IEEE future technology concern of affective computing

20200518 Extinction, zoo, upload, merge?
AGI safety
IEEE future technology concern of safety and beneficence of artificial general intelligence (AGI) and artificial superintelligence; IEEE future technology concern of mixed reality