Course Outline

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.

An overarching objective of this course is to help you develop as a student of the liberal arts. True students of the liberal arts are able to reflect on the context in which they live, and reason about what it means to live a meaningful and happy life. Thus, they are able to be more than just children of their own time. But this means we must be willing to put our ideas to the test, see our own errors, and develop intellectual courage and humility. It also helps not to take ourselves too seriously.

Readings

• Lemoine, Blake. “Is LaMDA Sentient?—An Interview,” Medium, June 11, 2022. Online.
• Nielsen, Michael. Neural Networks and Deep Learning (Chapters 1 and 2). Online.
• Rachels, James. “The Challenge of Cultural Relativism” (Chapter 2, in The Elements of Moral Philosophy), 9th ed. McGraw Hill, 2019.
• Roy, Tony. Truth as Correspondence. Online.
• Russell, Stuart J. and Peter Norvig. Artificial Intelligence: A Modern Approach, 3rd ed (Part 1). London: Pearson, 2009.
• Searle, John. “Minds, Brains, and Programs,” The Behavioral and Brain Sciences, (3) 417–457, 1980.
• Turing, Alan. “Computing Machinery and Intelligence,” Mind, New Series, (59, 236) 433–460, 1950.
• Vallor, Shannon. Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting. Oxford: Oxford University Press, 2016.

Evaluation

• Summaries: Each week before class starts, you will be expected to submit a one-page double-spaced summary of a news article related to artificial intelligence. You may use AI. This will be marked for completeness.

• Précis: Each week before class starts, you will be expected to submit a two-page double-spaced précis of the week’s readings. You may use AI. This will be marked for completeness.

• Neural Network Exercises: The Neural Networks Exercises will be completed in groups, and submitted on Google Sheets.

• Examinations: The examinations are written in class, and are comprehensive.

External Links

1. Class Schedule: Current schedule of readings and assignments
2. Electronic Whiteboard: For information sharing during class

Additional Information

1. This course outline is subject to arbitrary change. I shall announce any changes in class; if you are not present, you are still responsible for finding out what I announce.
2. Late exercises or assignments will not be accepted without a medical or compassionate reason. Exercises or assignments are due according to deadlines articulated in class.
3. The use of notebook computers or mobile devices is not permitted during class, except as allowed by the professor to do work directly related to some activity in class. You are expected to use analogue technologies (e.g., pen, pencil, and paper) to take notes, unless you have a special dispensation to use digital devices in class.
4. Please consult the college policy on class attendance. You must attend classes regularly and on-time. In accordance with the college’s policy on class attendance, credit will not be given to a student who has more than two weeks’ worth of absences.
5. Please consult the college policy on academic and artistic ethics. The use of artificial intelligence in coursework is not permitted, except as explicitly stated in this outline or allowed by the professor. You must fully cite your use of artificial intelligence if you use it.
6. Office hours are first-come-first-serve, unless you have an appointment. If you request an appointment by email, please send me a selection of several times you are available.
7. If you are being graded, your mark in the course will be translated into a letter-grade, according to the following scale: A+ (90–100), A (85–89), A– (80–84), B+ (77–79), B (73–76), B– (70–72), C+ (67–69), C (63–66), C– (60–62), D (50–59), F (0–49). Your grade will not be otherwise curved or adjusted.