Artificial Intelligence, Machine Learning, and Robotics have seen dramatic progress in the last several decades. There is increasing excitement and apprehension about the impact of these technologies, deployed in our world and our human society.
Ethics is the discipline within philosophy that considers which actions we humans see as right or wrong, or as good or bad. As we design intelligent artifacts that make their own decisions about how to act, and as they act within the human world, we ask how we can ensure that they will act ethically.
Two important questions arise.
First, like any other powerful technology (e.g. nuclear power, genetic engineering), there are important ethical questions about how AI and robotics technology can and should be deployed, and what its impact will be on society. This topic includes regulations, and the processes by which regulations are proposed, adopted, and enforced.
Second, unlike other technologies, AI (and thus intelligent robotics) involves creating agents that make their own decisions about how to act in the world. Ethics is a kind of foundational knowledge that humans use to decide how to act. We need to understand the structure of that knowledge, so the AIs we create will have the knowledge they need to act appropriately.
Do we mean that humans must be ethical as we design and deploy intelligent systems? Do we mean that the systems we design and deploy must be capable of deciding what is ethical for them to do? Most likely, the answers to both questions will turn out to be “Yes!” The follow-on question is “How do we do that?”
The semester will be organized around several major topic areas:
In the course of discussing research on these problem areas, we will draw on concepts from philosophical ethics, and from engineering design, law, economics, evolution, history, human development, etc.
An important question for researchers in artificial intelligence and robotics is how the knowledge relevant to making ethical decisions can be represented computationally in a knowledge base, and how it can be acquired.
Lectures: two each week, 80 minutes each (MW 4:30 - 6:00 pm). Discussion: one each week, 50 minutes (F 3:00 - 4:00 pm). (Attendance will be taken, and counted toward the Participation grade.)
We anticipate having a number of guest lecturers.
The lectures will include opportunities for class discussion. The Discussion meeting will go into further depth on issues that come up in lectures, but may also explore important issues in current news. Some discussions will involve the entire class, but we may also break into small groups.
Current University of Michigan policy requires all classes to be held in person, and all students, faculty, and staff to be fully vaccinated. Furthermore, the ventilation of all classrooms has been upgraded.
Each student will attend the classes, participate in the discussions, and write two papers. Attendance and participation will have significant weight (20%) in the course grade.
Pick a topic for your two term papers by the end of January (). Don't restrict yourself to what we've already covered in the course. Look ahead in the schedule, or come up with something else. Submit for comments and advice, but not counted toward the course grade.
In the first paper, due at mid-term (), you will formulate a question and review the available literature related to that question. The goal of your paper is to identify, clarify, and summarize the major positions on that question. Counts for 40% of the course grade.
In the second paper, due at the end of the term (), you will pick a question, take a position on how it should be answered, and justify your position, responding clearly to anticipated arguments from critics of that position. Counts for 40% of the course grade. Focusing either or both papers on the topic submitted in January is not required, but it will obviously make both papers stronger.
The following paper is a good example of a literature review, and it is also highly relevant to the content of the course. Read it before the start of the course.
When you write your own literature review, it need not match this in length or style, but it is an aspirational target. For your paper, imagine that you are providing detailed help on a particular focused topic, to a friend who wants to get started doing research on that specific topic.
There will be extensive assigned readings, and you will need to find and read additional papers and possibly books as part of your literature review and final term paper.
Be sure that you know how to use Google Scholar and the UM Library's Online Journal collection for tracking down references.
We will try to meet the needs of several distinct audiences with overlapping courses.
This course describes and discusses the ethical issues raised by AI and Robotics, reading and analyzing arguments from a number of disciplines, identifying and posing ethical questions, evaluating potential solutions, and formulating future research questions. The course will include guest lectures from experts in computer science, philosophy, cognitive science, psychology, public policy, law, etc.
For the undergraduate course (EECS 498-001), the two papers should demonstrate that you can search, find, and review good quality references beyond those handed out in class, and that you can put your own creative and critical insights into formulating a good problem and exploring solutions to it.
The expectation for the graduate course (EECS 598-001, ROB 599-004) will be (a) a deeper and more analytical literature review that identifies more related work beyond what has been handed out in class, and (b) a deeper and more thoughtful final term paper, anticipating and responding more effectively to critics.
EECS 598 has been approved to satisfy the following CSE Graduate Program requirements: depth (not cognate) requirement for the CSE PhD, and the 500-level and technical elective requirements for the CSE MS (confirmed: 11/19/2021).
EECS 498 has been approved to satisfy the College of Engineering Intellectual Breadth requirement for the CS-Eng, DS-Eng, CE, and EE majors (confirmed: 11/19/2021). (Since this is a special topics course, it doesn't yet show up on the degree audit, but it is manually added after the Drop/Add deadline.)
Students learn more when they collaborate actively with each other. But you also learn more when you take responsibility for doing your own work. Be prepared to teach each other, and to learn from each other, but not to do each others' work.
Discuss all the topics in the course, but especially the topics of your papers, with each other. Recommend papers to each other. Read and comment on each others' drafts as alpha and beta readers. But formulate and defend your own opinions, and write your own papers.
It is not a course requirement that you publish your paper in a conference or journal, but that's certainly a great outcome! After the course is over, it is entirely reasonable to combine and revise closely related papers into a joint submission for publication.
In the past, we have used Piazza for online discussion outside of class. Some people have recommended Slack. We have tried Canvas/Discussion, but that did not seem successful. Do you have an opinion? Feel free to let me know.
Anyone working in this area should understand the lesson of this children's poem.
Nonzero describes human biological and cultural evolution in a framework provided by game theory.
Burn-In is a novel, written to demonstrate possible social impacts of AI and robotics technology over the next decade or two. Many end-notes giving citations for the reality of the technology. It vividly illustrates the potential for serious problems, and the technological extrapolations are well researched, but remember that this is only one of many possible futures.
The Ministry for the Future is another novel of a possible future, showing how humanity might respond to the threat of climate change over the next several decades. AI and robotics have only a small role, but the need and the difficulty of establishing trust and cooperation are central.
Evil Geniuses discusses the political economics of the last half-century, leading up to the current level of economic inequality. The author has a strong and clearly stated political position. Even if you disagree, you should understand and respond to his arguments.
My chapter in the Oxford Handbook of Ethics of AI and my article in Frontiers in Robotics and AI provide overviews of some of the topics we will cover in the course.
To appreciate the urgency of this area of study, watch these two videos. Then read the information on the web site:
Links to other resources and recommended books.