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DRPS : Course Catalogue : School of Philosophy, Psychology and Language Sciences : Philosophy

Postgraduate Course: Ethics of Artificial Intelligence (PHIL11186)

Course Outline
SchoolSchool of Philosophy, Psychology and Language Sciences CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryArtificial 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. Questions we consider include:

- How do we align the aims of autonomous AI systems with our own?
- Does the future of AI pose an existential threat to humanity?
- How do we prevent learning algorithms from acquiring morally objectionable biases?
- Should autonomous AI be used to kill in warfare?
- How should AI systems be embedded in our social relations? Is it permissible to fall in love with an AI system?
- What sort of ethical rules should a self-driving car use?
- Can AI systems suffer moral harms? And if so, of what kinds?
- Can AI systems be moral agents? If so, how should we hold them accountable?
- Which ethical norms should we program into our AI, if any?
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:

- Robot rights
- AI existential threats
- Biases in learning algorithms
- Ethics of AI in warfare
- Ethics of AI in self-driving cars
- Moral harms to AI
- Falling in love with AI
- AI and future of human jobs

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2023/24, Available to all students (SV1) Quota:  26
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 22, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 174 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
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:
  1. demonstrate knowledge of philosophical issues involved in ethics of artificial intelligence
  2. demonstrate familiarity with relevant examples of AI systems
  3. demonstrate ability to bring philosophical considerations to bear in practical contexts
  4. demonstrate ability to work in a small team
  5. demonstrate skills in research, analysis and argumentation
Reading List
Representative reading list; specific readings change year to year:

Bostrom, N. (2014), Superintelligence: Paths, Dangers, Strategies, 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.
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
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
Keywordsapplied ethics,artificial intelligence,existential risk,data science,moral responsibility
Course organiserMr Mike Gregory
Course secretaryMrs Ida Conlin
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