Course objectives, learning outcomes, learning strategy
Explore the contemporary ethics of computer science and engineering with thought experiments, discussion, and case studies. Students will learn the central ethical principles guiding today’s information technology, and apply the theory in the real world.
Ultimately, students will be equipped to to develop ethical understandings of their own work. They will also be able to respond to ethics committees, and to produce AI ethics evaluations, sometimes referred to as AI ethics audits / Algorithmic impact statements.
This is a learning-by-doing course. It is designed for participation, collaboration, and to be taken in-person.
Entrance requirements
None
Contents
- Ethics principles. Principles employed in today's Computer Science, Engineering, and AI ethics.
- Individual principles: Autonomy, Human Dignity, Privacy
- Social principles: Fairness, Solidarity, Sustainability/Social wellbeing
- Technical principles: Performance, Safety, Accountability
- Ethics theories. The underlying theory of applied ethics.
- Deontological ethics: Kant, Rights, Fairness (Aristotle/Rawls)
- Consequentialist ethics: Utilitarian, Enlightened Egoism (Adam Smith & Silicon Valley)
- Culturalist ethics: Post Nietzscheanism
- Selected contemporary debates in the philosophy and ethics of computer science and artificial intelligence.
- Privacy versus social wellbeing, User autonomy, freedom and authenticity, Statistical fairness, Causal AI, Explainable AI, Data ownership, Digital twins, and similar.
- Full list here
Teaching and learning methods and activities
As ethics is learned by doing, students will be asked to contribute to class discussion, to participate in a group presentation on an issue in applied ethics, and finally to present an ethical evaluation of their own work.
Most of the course hours will be lecture and case study discussion led by the professors.
The remainder will be student presentations. There will be two kinds of presentations. In one, students will work in groups to learn about selected ethical debates in computer science and engineering, and then they will present their findings to the class. The second presentation will occur at the end of the semester, and students will individually describe an ethical evaluation of their own work.
Tests and assessment criteria
Attendance to at least 75% of the classes is mandatory for being admitted to the exam.
Assessment will be based on two presentations. In the presentations, students will be graded on their ability to locate the ethical dilemmas that arise around technology, and their ability to discuss the dilemmas knowledgeably. (There are no right or wrong answers in ethics, but there are better and worse understandings of the human values that guide and justify decisions.)
Presentations should center on the values discussed in the seminar: Autonomy, Human Dignity, Privacy, Fairness, Solidarity/Equity, Social wellbeing, Performance, Safety, Explainability/Accountability. Typically, a strong presentation will curate and focus on a few of the principles most applicable to the case.
Group presentation
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The group presentation may investigate a publicly known artificial intelligence application (a Covid tracking app, for example, or facial recognition technology, or an AI medical tool, or driverless cars, or similar.) Or, the subject may be a larger review of the ethical status of a technology company. This might be a startup company or an established enterprise. For example, Meta's use of recommendation algorithms may be investigated. Regardless, the many cases discussed during the seminar serve as examples for the kind of subject that should be investigated.
Individual presentation
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At the end of the semester, students will individually discuss an ethical dilemma. The criteria for choosing a dilemma are similar to the ones above, for group presentation.
Grading
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The final grade will be a weighted average of the Group presentation (30%) and of the Individual presentation (70%). Both the Group presentation and the Individual presentation are required.
Tests and assessment criteria: Non-attending students
Requirements for being admitted to the exam
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No minimal attendance is required for being admitted to the exam.
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Students must write 1 page reflections and comments (not a summary) for each of the information technology papers assigned as part of the exam’s subject matter (Parts 1 to 4 of the course bibliography). This material must be submitted via web site or email at least one week before the exam date. This material will not be graded for the final mark but used as filter for admission to the exam. Admission will be communicated via email at least two days before the exam.
Subject of exam
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Applied ethics and information technology ethics.
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Students will be required to familiarize themselves with the basic tenets of applied ethics, and the common dilemmas and approaches to information technology ethics, which is a subfield of applied ethics.
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Materials for general applied ethics - see Part 4 of the "Bibliography/Study materials" Section for the required textbooks.
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Materials for information technology ethics - see Part 1-3 of the "Bibliography/Study materials" Section for the required papers and readings.
Written exam
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The written exam is a closed-book exam. No material (online or offline) can be used during the written exam. The exam consists of 2-3 pages handwritten response to two questions. The questions will require students to respond to a recent ethical issue in technology. The questions assume students has knowledge of all the material listed in the "Bibliography/Study materials" Section.
Oral exam
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The oral exam will cover all materials. It will probe knowledge of general applied ethics and of information technology ethics. The written work done by the student will also be reviewed.
Grading
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The final grade will be a weighted average of the Written exam (50%) and of the Oral exam (50%). Both the Written exam and the Oral exam are required.
Bibliography/Study materials
Part 1. Principles commonly employed in today’s Computer Science, Engineering, and AI ethics
- European Commission: Ethics Guidelines for Trustworthy AI
- European Commission: Assessment List on Trustworthy Artificial Intelligence
- German Data Ethics Commission: Opinion of the Data Ethics Commission
- GAO (US): Artificial Intelligence: An Accountability Framework for Federal Agencies and Other Entities
- Whittlestone et al: The Role and Limits of Principles in AI Ethics - Towards a Focus on Tensions
Part 2. The underlying theory of applied ethics
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Brusseau, Ethics Workshop, selections provided by instructor
Part 3. Selected debates in the contemporary philosophy and ethics of computer science and artificial intelligence
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Clusters of publicly available readings from journals and books that define contemporary debates in technology ethics, selected by professors and students. Material will be determined and made available during the course.
Part 4. Textbooks for non-attending students.
- The elements of moral philosophy, James Rachels, McGraw-Hill, 2003
- Ethics for A-Level, Mark Dimmock, Andrew Fisher, Cambridge, 2018 (Part I, all chapters, and Part III, Chapter 13)