Course Outline

Artificial Intelligence and Ethics

Professor Dr K Darcy Otto
Title AI and Ethics
Code CS 2xxx
Credits 4
Term Spring 2025
Times TBD
Location TBD
Delivery Fully in-person
Contact Email
Office Hours TBD

Description

If you had a robot who always tied your shoes for you, would you ever have learned how to tie your shoes yourself? What about if that same agent did all your arithmetic and all your writing, and eventually shaped all your decisions? The promise of AI is fraught with ethical questions that strike at the very heart of what it means to be human and to act as a moral agent in society. It reveals a fundamental tension between what AI can do and what AI should do. In the modern world, that tension is growing.

This course investigates AI Ethics using an interdisciplinary approach. We shall explore AI from the perspective of computer science, where you will learn about neural networks and deep learning; and from the perspective of philosophy, where we will discuss how one ought to act. Our goal is to think deeply about human values in an increasingly technological world, and to inform discussions about ethics with an understanding of how AI actually works.

You do not require a background in philosophy or computer science to take this class. But you must be willing to read and think about both technical and philosophical works, and be comfortable with elementary algebra. Any other background will be provided. By the end of our class, you will discover whether you want a robot that ties your shoes.

Learning Outcomes

  1. Understand and be able to explain deep learning, and how deep learning is related to machine learning and AI in general.
  2. Create a neural network using backpropagation from first principles, without using any libraries of functions.
  3. Understand and be able to explain the study of ethics, and how it is connected to other areas of knowledge.
  4. Articulate how various ethical theories apply to emerging technologies, and artificial intelligence in particular.
  5. Discuss the alignment problem, and how it may play out for future developments in artificial intelligence.

Topics include: computer science, artificial intelligence, machine learning, deep learning, philosophy, ethics