------ Announcements ------ 

Welcome to Ethics in AI, the first four weeks of classes will be in person in FAB 10. See you then!

Course Information

Instructor: Ameeta Agrawal, PhD, ameeta@pdx.edu

TA: Ekata Mitra, ekata@pdx.edu

Lectures: Tue/Thu, 11am - 12:40pm

Class Location: Please note that this is a 'hybrid' course with some in-person and some online classes.

>> In-person days: FAB 10 (no synchronous Zoom session)

>> Online/remote days: Zoom 

Instructor office hours: Mon 12pm - 1pm on Zoom or by appointment

TA office hours: Wed 4pm - 5pm on Zoom or by appointment

Slack channel: Join our Slack community (#ethicsai_f25) for collaborative learning and communication.

Course Description

This course explores the ethical, social, and philosophical questions raised by the design, deployment, and impact of artificial intelligence. Students will examine topics such as algorithmic bias and fairness, accountability and transparency, privacy and surveillance, autonomous decision-making, and the societal implications of AI systems. Through case studies, debates, and critical analysis, the course emphasizes responsible AI development and governance, preparing students to anticipate ethical challenges and design technology that aligns with human values.

Reference Texts

All required readings will be freely available online. Weekly readings and resources will be posted at the bottom of this page and updated throughout the term.

Coursework and Grading 

course combines collaborative discussion, critical reflection, applied exploration, and creative communication to help students engage deeply with ethical questions in artificial intelligence. Participation and consistent engagement are key components of success.

1.  In-Class Discussions and Presentations - 40%

Students will be assigned to small discussion groups and participate in two class-led presentations during the term. Each presentation will last approximately 30 minutes and include time for Q&A. Groups may choose from various formats, such as panel discussion (presenting multiple perspectives on an ethical dilemma), pro/con debate (exploring opposing viewpoints on an AI topic), teach-a-topic session (introducing a core ethical concept and guiding class discussion), interactive quiz or simulation (engaging classmates in applied ethical reasoning). Presentations will be graded on depth of research, clarity of explanation, engagement of the audience, and quality of discussion questions.

2.  Micro-reflections - (6 x 4% = 24%)

Pop-up “micro-reflections” where students will connect that day’s class discussions to weekly readings and other current events, personal experiences, or media (e.g., news articles, films, podcasts). We will consider your top 6 statements of the term.

3.  Applied Exploration Hackathon - 16%

Midway through the course, students will participate in a collaborative “Ethics Hackathon.” Teams will receive a topic or challenge and will design a practical solution, prototype, or analysis. Teams will present their findings to the class in a short presentation.

4.  Individual Final Project - 20%

The final project allows students to synthesize course concepts and apply them creatively or analytically. Students may choose from one of the following options: public explainer project (create a blog post, podcast, video, or infographic that explains a key AI ethics issue for a general audience) or community engagement project (conduct interviews or surveys with members of the public about their perceptions of AI, and present findings on public trust, ethical concerns, and misconceptions).

Course Prerequisites

• General understanding of AI technologies

Class Schedule (this will be updated as needed)