Course Information


This page will be updated regularly. Check back often for updates.

Overview

We will study the foundations of trustworthy AI, including privacy, robustness, generalization, uncertainty quantification, alignment, copyright protection, and incentives, with the specific mix of topics shaped by students' interests. For each topic we will see a mix of more classical theoretical work and more recent research trying to apply these ideas to practice. The primarily deliverable will be a final course project and presentation.

Instructor

Meetings

Time: TF 9:50–11:30am
Location: 296 Ryder Hall

Students are expected to attend and participate actively in all class meetings within reason. Occasional absenses due to illnesses or work obligations are inevitable and that is completely fine, but please notify me about more extended absenses. Meetings will be recorded and the recordings will be available on request, but these are not a substitute for attendance.

Final Project

The main course deliverable is a final project and a final in-class project presentation. The project can be on any topic related to the course content, and it is OK for your project to connect to your existing research agenda as long as the project itself is original work. Projects can be done solo or in a team of two, and groups of three or more may be allowed for especially ambitious projects. More information about project expectations and milestones will be shared in the first few weeks.

AI Policy

This is a Ph.D. level course, which means students have a wide range of backgrounds and learning objectives. You will get out of this course what you put into that, so please keep that in mind when you think about AI use.

The main deliverable is a final research project. You may use AI tools to help with your research project, as you likely already do in your own reserch. You are ultimately responsible for all the work you submit or present, which means I will be holding you to high standards for the quality of your research, writing, and presentation, as well as your ability to engage with questions. And you are unlikely to meet these standards if you are completely reliant on AI tools. If there are other course deliverables, the policy on AI use will be communicated clearly in advance.