Postgraduate Course: Ethics of Artificial Intelligence (PHIL11186)
Course Outline
School | School of Philosophy, Psychology and Language Sciences |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
SCQF Credits | 20 |
ECTS Credits | 10 |
Summary | Artificial intelligence (AI) is developing at an extremely rapid pace. We expect to see significant changes in our society as AI systems become embedded in various aspects of our lives. This course will cover philosophical issues raised by current and future AI systems, with a special focus on normative concerns. Questions we consider include:
- What larger sociotechnical systems, historical forces, cultural values, and power relations have shaped the design, development and use of AI systems, and how might these be shaped by AI in the future?
- What sort of ethical rules, principles, rights or norms should govern AI systems and decisions?
- How do we prevent learning algorithms from acquiring morally objectionable biases?
- Should autonomous AI systems ever be used to kill in warfare, or to make other decisions with irrevocable and morally grave consequences?
- How will AI systems affect human dignity, skills, virtues, purpose, and work?
- What kinds of social roles (e.g. teacher, friend, supervisor, caregiver, lover) are ethically permissible for AI systems to occupy?
- Should AI systems be allowed to deceive or manipulate people, even if for beneficial rather than malicious purposes? Should they be allowed to imitate human emotions?
- Can an AI system suffer moral harm, or be a morally responsible agent?
- Does the future of AI pose an existential threat to humanity? Can we keep the values of AI systems safely aligned with our own?
- How should the power, benefits and risks of AI systems be distributed in societies and globally? |
Course description |
The aim of this course is to introduce students to a range of ethical issues that arise regarding current and future artificial intelligence (AI). The main questions we will consider are listed in the course summary. No previous familiarity with the literature on AI will be assumed.
The classes will be primarily discussion based, so students are expected to have done the reading in advance of class. During class, students will work in small teams to answer a question (approximately 1 per team) based on the reading for the week. They may be instructed to argue for a particular case (pro or contra). They may be asked to assess the merits of a given view. They may be asked to look for counterexamples to a generalisation or fallacies with a specific argument. In second part of the class, we will come together to discuss what each group has achieved to see how it helps us to answer our questions.
Topics covered in class:
- Ethics of AI in government, health, education, transportation, media, finance, and warfare
- Ethics of AI prediction, classification, manipulation, and surveillance of humans
- Ethics of social robots
- AI and the future of work
- Justice, bias and human rights in AI decision-systems
- AI safety, reliability and existential risks
- AI agency, responsibility and moral status
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
Pre-requisites | None |
High Demand Course? |
Yes |
Course Delivery Information
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Academic year 2020/21, Available to all students (SV1)
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Quota: 0 |
Course Start |
Semester 2 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
176 )
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
5% Participation Grade
40% midterm writing assignment (1500 words)
55% end-of-semester essay (2500 words) |
Feedback |
Not entered |
No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- demonstrate knowledge of philosophical issues involved in ethics of artificial intelligence
- demonstrate familiarity with relevant examples of AI systems
- demonstrate ability to bring philosophical considerations to bear in practical contexts
- demonstrate ability to work in a small team
- demonstrate skills in research, analysis and argumentation
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Reading List
Representative reading list; specific readings change year to year
Lin, P., Abney, K. and Jenkins, R. (2019) Robot Ethics 2.0, Oxford University Press
Wallach, W., Allen, C. (2009) Moral Machines, Oxford University Press
Dubber, M.D., Pasquale, F. and Das, S. eds. (2020), The Oxford Handbook of Ethics of AI, Oxford University Press.
Liao, M., ed. (2020) Ethics of Artificial Intelligence, Oxford University Press. |
Additional Information
Graduate Attributes and Skills |
- Reading, understanding and critically engaging with complex texts
- Critical thinking
- Team work
- Interdisciplinary thinking
- Evaluating arguments and theories
- Working to deadlines
- Ability to articulate and defend positions in a debate |
Keywords | applied ethics,artificial intelligence,existential risk,data science,moral responsibility |
Contacts
Course organiser | Prof Shannon Vallor
Tel: (0131 6)50 3886
Email: svallor@ed.ac.uk |
Course secretary | Ms Becky Verdon
Tel: (0131 6)50 3860
Email: Rebecca.Verdon@ed.ac.uk |
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