Syllabus |
Schedule |
Assignments |
Term Paper |
Instructor
Hallmarks of AI are systems that exhibit human-like behaviors, and that they rely on continuous preparation and deployment of data resources as new tasks emerge. In this course, students develop their conceptual, applied, and critical understanding about (1) experimental principles and methods guiding the collection, validation, and deployment of human data resources for AI systems; (2) human-centered AI concepts and techniques including dataset bias, debiasing, AI fairness, humans-in-the loop methods, explainable AI, trust, and (3) best practices for technical writing and presentation about AI research. As a milestone, based on research review, students will write and present an experimental design proposal for dataset elicitation followed by computational experimentation, with description and visualization of the intended experiment setup, as well as critical reflection of benefits, limitations, and implications in the context of AI system development and deployment.
Students completing this course are expected to
- Conduct independent research.
- Understand basic challenges and techniques for human-centered AI.
- Develop the ability to solve real-world problems using machine learning.
The course uses Github for assignment submission, discussion, questions. Slides, assignments, and recorded videos will be posted here.
Prerequisites: IDAI-610 and IDAI-700 or equivalent courses are required before taking this course. Also note that GitHub are required for submitting assignments and Assignment 0 provides learning materials to help students with those.
Grading: Evaluation will be based on the following distribution: 10% quizzes/attendence, 30% assignments, 60% term paper. A detailed grading policy can be found at the end of the description of each assignment and project.
| Grade | Points | Grade | Points | |
|---|---|---|---|---|
| A | 93 or above | B- | 80 – 82 | |
| A- | 90 – 92 | C+ | 77 – 79 | |
| B+ | 87 – 89 | C | 70 – 76 | |
| B | 83 – 86 | F | Below 70 |
Late work policy: The TA will start grading assignments after the due date. Late work in assignments will not be graded. Exceptions to this policy will be made only in extraordinary circumstances, almost always involving a family or medical emergency---with your academic advisor or the Dean of Student Affairs requesting the exception on your behalf. Accommodations for travel (e.g., for interviews) might be possible if requested at least 3 days in advance.
Team work: Discussions between students are welcomed but each student should complete their assignments and project independently. Identical or extremely similar submissions will still be considered as cheating. Questions that cannot be resolved between students should be posted as a new issue on this repo for discussion.
Academic Integrity: Students are encouraged to discuss the assignments and projects with each other, especially in their study group. But do not copy finished assignments or projects from other students' Github repos. Up to 90% of the learning in this course comes from completing the assignments and the term paper. Skipping the assignments and the project is a huge waste to your effort spent on this course. In the meantime, students need to confront the TA or the instructor if their submissions were found too similar.
Generative AI tools: Coding solutions must be your own work, which means you cannot use generative AI tools in any manner to write your programs. When learning fundamental skills, you need to ensure that you master the basics. If I doubt authorship, I may ask you to explain the code or re-create aspects of the code in one of our labs – you must show that you have mastered the fundamentals. However, you can use any opensource resources for your term paper (as long as it does not require any external dependency that the grader may not have) including generative AI tools (but not using it to WRITE the paper).
In short:
- Homework assignments: generative AI ☒
- Term paper: generative AI ☑
Accommodations for students with disabilities: If you have a disability and have an accommodations letter from the Disability Resources office, we encourage you to discuss your accommodations and needs with us as early in the semester as possible. We will work with you to ensure that accommodations are provided as appropriate. If you suspect that you may have a disability and would benefit from accommodations but are not yet registered with the Office of Disability Resources, we encourage you to contact them at dso@rit.edu.
A note on self-care: Please take care of yourself. Do your best to maintain a healthy lifestyle this semester by eating well, exercising, avoiding drugs and alcohol, getting enough sleep and taking some time to relax. This will help you achieve your goals and cope with stress. All of us benefit from support during times of struggle. You are not alone. There are many helpful resources available on campus and an important part of the college experience is learning how to ask for help. Asking for support sooner rather than later is often helpful. If you or anyone you know experiences any academic stress, difficult life events, or feelings like anxiety or depression, we strongly encourage you to seek support. Counseling and Psychological Services (CaPS) is here to help: call 585-475-2261 for urgent matters or email caps@rit.edu for non-urgent cases. Please also consider reaching out to a friend, faculty, or family member you trust for help getting connected to the support that can help.