02.143HT Artificial Intelligence and Ethics
In this course, we will discuss ethical questions raised by contemporary AI technologies. Through cases like deepfakes, recommender and decision algorithms, self-driving cars, large language models, and other applications of AI, students will consider how AI affects individuals and society, and the ethical responsibilities of users, developers, companies, and institutions. We will also discuss AI and the future of work, surveillance and privacy, and human-AI relationships. The course will conclude by considering the moral status of AI itself: could sufficiently sophisticated AI ever have moral rights?
Students will be introduced to two major ethical theories – consequentialism and deontology – as well as basic logic. Weekly cases will also introduce students to ethical concepts like harm, autonomy, responsibility, privacy, bias, manipulation, and moral status. Together, these will provide students with the theoretical tools to evaluate and make arguments about AI ethics.
Learning objectives
- Acquire knowledge of the state of debates surrounding AI ethics.
- Acquire reasoning skills to critically analyse the ethical views presented in these debates.
- Acquire reasoning skills to advance original arguments for one’s own ethical view on these debates.
- Acquire the skills to effectively communicate all the above, verbally and in writing.
Measurable outcomes
- Demonstrating knowledge of the main points of debates surrounding AI ethics (LO1). To be measured via all modes of assessment.
- Demonstrating the ability to critically analyse assumptions at the base of these debates (LO2), and advance original arguments for one’s own position on these debates (LO3). To be measured via all modes of assessment.
- Demonstrating the skills to effectively communicate philosophical ideas and arguments (LO4). To be measured via class participation (verbal skills) and all modes of assessment (written skills).
Course requirement
| Assessment | Percentage |
| WEC – Class participation | 20 |
| WEC – Mid-term paper | 25 |
| WEC – Final paper | 30 |
| WEC – Reading reflections | 25 |
Course map
Week 1: Introduction to AI and Ethics
Week 2: Ethical Theories – Consequentialism; Introduction to Logic
Week 3: Ethical Theories – Deontology
Week 4: Self-Driving Cars
Week 5: Deepfakes
Week 6: Surveillance and Privacy
Week 7: Recess Week
Week 8: Recommender Algorithms
Week 9: Decision Algorithms
Week 10: Large Language Models
Week 11: AI and the Future of Work
Week 12: Human-AI Relationships
Week 13: The Moral Status of AI
Week 14: Review
Instructor
Grace Boey