Preliminary Syllabus
This course is in development. The partial preliminary syllabus here is provided to give you an idea of what to expect in the class, but is likely to change before the semester starts.
Overview
This course explores impacts of AI on humanity, with a focus on understanding and mitigating unintended harms from AI and intended abuses of AI systems. Expected topics include fairness, privacy, copyright infringement, robustness, safety, economic disruption, and cultural diminishment.
Preparation
Official Prerequisite: Completed CS 2100 (DSA1) with a grade of C- or better.
I will make exceptions to the official prerequisite if you have an interest in taking the class and have sufficient background in computing.
Unofficial Prerequisite: Students in the course are expected to have sufficient understanding of computing systems to be able to read technical papers (including research papers) and to understand and discuss the impact of decisions about how computing systems are programmed, trained, and deployed. Since we expect to have a broad range of software engineering experience and machine learning knowledge in the class, we will not have any assignments that depend on this (beyond what we expect from the DSA1 prerequisite), but expect students to work in teams for the project where everyone is using what they already know and learning and developing their computing skills.
We do not assume any particular background or experience in other areas beyond what would be the minimal expectations for a high school graduate, but do expect students in the class to be comfortable reading texts from a variety of perspectives and not afraid of reading a philosophical treatise, legal document, or opinionated blog post. Students should be open minded and willing to engage with difficult questions in a flexible and tolerant way.
Instructor
This is the first time this course has been offered, but you can get some ideas what to expect from previous courses I have taught that have some similarities with this course. In Fall 2025, I taught a course on Law and Artificial Intelligence that was joint with a Law school class (taught by Thomas Nachbar). This course will include some of the topics that were covered in that course such as fairness and privacy, but without the legal emphasis (although we will touch on legal aspects in places). In Fall 2023, I taught a gradaute-level seminar on Risks and Benefits of Generative AI and LLMs. During the pandemic lockdown, I taught a cs3501 course on Everyday Ethics and Quotidian Quandaries for Computer Scientists. Back in 2018, I taught a Pavillion Seminar on How will Artificial Intelligence Change Humanity? which intersects with many of the themes of this course, but was for students without any computer science background (and much has changed in AI since 2018, although not so much about humans). I have also taught courses on Security and Privacy of Machine Learning, Markets, Mechanisms, and Machines, and cryptocurrencies, which might include some of the topics we will touch on in this class.
Email: Students should feel free to email me at evans@virginia.edu anytime and about anything you would like to discuss or think it would be good for me to know. I usually respond to emails quickly and reliably (at least I try to!), so if you don’t hear back within 24 hours, please send a follow-up reminder.
Office Hours and Scheduling Meetings: In Fall 2025, I have office hours on Thursdays 1:30-2:30pm. I will decide on a schedule for Spring 2026 office hours later. You don’t need to schedule an appointment to come to office hours — they are open to everyone. If you would like to schedule a meeting at another time, use https://davidevans.youcanbook.me/ to schedule a time but if you can’t find anything that works there, email me your scheduling constraints.
Student Expectations and Assessments
Readings: Students will be assigned readings and other materials, and be expected to read and think about these before class. The amount of reading will be kept fairly low, with an emphasis on deep and thoughtful reading rather than quantity, but for some topics longer readings will be valuable.
Reflections/Quizzes/Homeworks: Students will be assigned a variety of different tasks to encourage you to think about and reflect on the readings and what we do in class. The exact form of these assessments is not yet determined, and will partly depend on how students do in participating in class and on early assignments, but are likely to be primarily quizzes with questions that expect short answers.
Project: A large part of the course will be a team project in which students will work throughout the semester on a project related to the goals of this course. There will be a large amount of freedom in determining the topic and deliverables for your project, with guidance along the way.
In-Class Presentations: Teams of 2-4 students will be assigned to present topics and lead discussions throughout the semester. Some of these will be weekly discussions on relevant topics in the news. Others will be topics based on selected readings or other sources. Over the course, each student in the class will be expected to be part of the team leading a presentation on at least one news topic and one reading topics.
Midterm: There will be one midterm exam in class on Thursday, 2 April.
Grading
I encourage students to spend your energy focusing on what you are learning and contributing, instead of worrying about your grade. That said, I understand students are often stressed about grading and understandably want to know how grades will be determined. I aim to grade in a way that is useful (provides students with accurate measure of how well they understood what they should), motivating (encourages the desired behaviors, including a reasonable amount of effort), fair (assigns higher grades to more deserving students), robust (arbitrary small perturbations do not have a material impact on someone’s grade), and low stress (for both students and me).
For this reason, I don’t prescribe a singular mathematical formula for quantitatively assigning letter grades but do provide a formula that can be used to compute a lower bound on the grade you receive in the course:
| Item | Standard Weighting |
|---|---|
| Project | 40% |
| Quizzes and Homeworks | 20% |
| Midterm Exam | 15% |
| Class Presentations (Topic, News) | 15% |
| In-Class Contribution | 10% |
With the exception of cases of academic dishonesty or inappropriate behavior, your grade will not be below the grade that would result from computing your score using the percentages in the table, where your score for each item is the ratio of the score you received to the target score for that item, and the grading scale is based on the standard decades (e.g., 0.87 = B+, 0.9 = A-, 0.93 = A).
This is a minimum grade, though, and I want to assign a grade that reflects the best possible interpretation of all you have done during the semester. This means we consider your performance throughout the course, and in cases where performance varries across the different assignments or will examine grades using a variety of different methods that weights different aspects differently and rewards performance improvements, but also allows consistent performance to make up for one slip-up.
Honor Expectations
We believe strongly in the value of a community of trust, and expect all of the students in this class to contribute to strengthening and enhancing that community. The course will be better for everyone if everyone can assume everyone else is trustworthy. I start with the assumption that all students at the university deserve to be trusted.
Collaboration and Resource Policy: For some assignments in this class you will given broad latitude to collaborate and use external resources (including AI tools); for other assignments, you will be required to work on your own and with limited and restricted resources. For any given assignment, it should be clear what the rules and expectations are, and you are expected to follow both the spirit and the letter of these policies. I aim to make the language describing the policy as clear and unambiguous as possible, but if anything is ever unclear about the stated policy for an assignment, please clarify with me. The penalty for policy violations will be considered on a case-by-case basis, with a penalty commensurate the severity of the offense.
Additional Information
This is similar to information that applies to most classes at UVA.
Special Circumstances: The University of Virginia strives to provide accessibility to all students. If you require an accommodation to fully access this course, please contact the Student Disability Access Center (SDAC) at (434) 243-5180 or sdac@virginia.edu. If you are unsure if you require an accommodation, or to learn more about their services, you may contact the SDAC at the number above or by visiting their website https://studenthealth.virginia.edu/sdac
Accommodations: It is the University’s long-standing policy and practice to reasonably accommodate students so that they do not experience an adverse academic consequence when serious personal issues conflict with academic requirements. Although University policy only recognizes religious accomodations, the course instructor believes they are many other valid reasons for accomdations that are at least as justifiable as ones for religious observance and consider family obligations, personal crises, and extraordinary opportunities to all be potentially valid reasons for accomodations. Students who wish to request accommodations should submit their request to Prof. Evans as far in advance as possible.
If you have questions or concerns about the University policy on academic accommodations for religious observance or religious beliefs, visit https://eocr.virginia.edu/accommodations-religious-observance or contact the University’s Office for Equal Opportunity and Civil Rights (EOCR) at UVAEOCR@virginia.edu or 434-924-3200.
Safe Environment: The University of Virginia is dedicated to providing a safe and equitable learning environment for all students. To that end, it is vital that you know two values that we and the University hold as critically important:
- Power-based personal violence will not be tolerated.
- Everyone has a responsibility to do their part to maintain a safe community on grounds (including in virtual environments).
If you or someone you know has been affected by power-based personal violence, more information can be found on the UVA Sexual Violence website that describes reporting options and resources available: https://www.virginia.edu/sexualviolence.
As your professor and as a human, know that I each care about you and your well-being and stand ready to provide support and resources as much as I can. As a faculty member, I am classified as a responsible employee, which means that I am required by University policy and federal law to report what you tell us to the University’s Title IX Coordinator. The Title IX Coordinator’s job is to ensure that the reporting student receives the resources and support that they need, while also reviewing the information presented to determine whether further action is necessary to ensure survivor safety and the safety of the University community. If you would rather keep this information confidential, there are Confidential Employees you can talk to on Grounds (see https://eocr.virginia.edu/chart-confidential-resources). The worst possible situation would be for you or your friend to remain silent when there are so many here willing and able to help.
Well-being: If you are feeling overwhelmed, stressed, or isolated, there are many individuals here who are ready and wanting to help. The Student Health Center offers Counseling and Psychological Services (CAPS) for all UVA students. Call 434-243-5150 (or 434-972-7004 for after hours and weekend crisis assistance) to get started and schedule an appointment. If you prefer to speak anonymously and confidentially over the phone, Madison House provides a HELP Line at any hour of any day: 434-295-8255.