Caption: The heading row descibes the categories of information about the course,
while the row in the table body holds the course information itself.
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Course Prefix
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Course Number
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Course Title
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Lecture/Lab Hours
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Credit Hours
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PHI
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130
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Applied Ethics for Artificial Intelligence
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3 Lecture/Demonstration Hours
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3 Credit Hours
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Course description
Examines central ethical questions posed by the design and implementation of artificial
intelligence (AI). Students draw on leading ethical frameworks and perspectives to
navigate challenges posed by the introduction of AI to a variety of morally significant
contexts, such as public safety, medicine, and criminal justice.
Topical outline
- Algorithmic bias and algorithmic fairness
- AI opacity and stakeholder transparency
- Introduction to ethical frameworks (Kantian deontology, utilitarianism, virtue ethics,
etc.)
- Ethics-first approach in the AI project cycle
- Trust and reliability in the context of AI
- Machine learning algorithms in criminal justice
- Data privacy and surveillance
- Public safety and facial recognition technology
- Medical AI and clinical decision-making
- Copyright and intellectual property
- Environmental impact of AI
- Deep fakes and online manipulation
Method of presentation
- Class Discussion
- Lecture
- Laboratory
Student outcomes
The student should...
- identify and articulate current regulatory practices in the governance of distinct
AI types (concerning, e.g., privacy, data mining, surveillance, facial recognition,
etc.).
- examine at least three domains of central ethical significance being impacted by emerging
AI and machine learning algorithms (e.g., in criminal justice, medical research and
practice, the environment, copyright and intellectual property, ethics of warfare,
etc.).
- examine normative questions and challenges surrounding the use of AI to support human
decision making (e.g., algorithmic bias, AI opacity, trust versus reliability, moral
agency).
- examine normative questions and challenges surrounding considerations of justice and
equity (impact of automation on private sector, inequitable access, wealth inequality,
education).
- examine the implications of misinformation and disinformation in the age of generative
AI (deepfakes and synthetic media).
- identify and articulate multiple normative concepts including at least one from outside
the Western philosophical canon.
- identify ethical issues at stake in individual and collective decisions.
- apply different ethical perspectives to issues we encounter in our everyday lives.
- form and evaluate arguments for ethical judgments.
- critically assess support for their own moral beliefs.
- demonstrate the use of three primary texts in the service of above outcomes.
- write a total of at least ten pages (of approximately 300 words each) of college level
writing in the service of the above outcomes.
- engage in philosophical conversations with others.
Method of evaluation
Typical classroom techniques
- Projects
- Class participation
- Final exam
- Essays/Term papers
Course content learning outcomes
- Quizzes
- Group participation
Additional assessment information (optional)
None
Textbooks
Required
- Rubeis, Giovanni. Ethics of Medical AI. Springer Verlag, 2024
Optional
- Boddington, Paula. AI Ethics: A Textbook Springer Singapore, 2023
- Vallor, Shannon. Technology and the Virtues: A Philosophical Guide to a Future Worth
Wanting Oxford University Press., 2016
Supplementary materials
None
Software
None
Updated: Fall 2025
