Responsible AI blog - Fall-24

This repository is intedned to contain a collection of notes and paper summaries for each class of the Reponsible AI course tought at UVA in the Fall-24. The course is organized around six topics:

• Fairness
• Safety
• Privacy
• Evaluation
• Unlearning
• Misuse of AI and Governance

Each topic is associated with the corresponding folder in this repository.

Students should should write the report on the papers and topics reviewed in their class by modifying the associated ".md" file.

Syllabus

This is a tentative calendar and it is subject to change.

Date	Topic	Subtopic	Blog
Wed Jan 31	Fairness	Intro and bias sources	Group 1
Mon Feb 5	Fairness	Statistical measures	Group 2
Wed Feb 7	Fairness	Tradeoffs	Group 3
Mon Feb 12	Fairness	LLMs: Toxicy and Bias	Group 4
Wed Feb 14	Fairness	LLMs: Fairness	Group 5
Mon Feb 19	Fairness	Policy aspects	Group 6
Wed Feb 21	Safety	Distribution shift	Group 1
Mon Feb 26	Safety	Poisoning	Group 2
Wed Feb 28	No class (AAAI)
Mon Mar 4	Safety	Adversarial Robustness	Group 3
Wed Mar 6	Spring break
Mon Mar 11	Spring break
Wed Mar 13	Safety	Adversarial Robustness	Group 4
Mon Mar 18	Safety	LLMs: Prompt injection	Group 5
Wed Mar 20	Safety	LLMs: Jailbreaking	Group 6
Mon Mar 25	Privacy	Differential Privacy 1	Group 1
Wed Mar 27	Privacy	Differential Privacy 2	Group 2
Mon Apr 1	Privacy	Auditing and Membership inference	Group 3
Wed Apr 3	Privacy	Privacy and Fairness	Group 4
Mon Apr 8	Privacy	LLMs: Private issues in LLMs	Group 5
Wed Apr 10	Privacy	LLMs: Privacy in LLMs	Group 6
Mon Apr 15	Evaluation	Model cards	Group 1
Wed Apr 17	Evaluation	LLMs: evaluation	Group 2
Mon Apr 22	Unlearning	Unlearning 1	Group 3
Wed Apr 24	Unlearning	LLMs: Targeted unlearning	Group 4
Mon Apr 29	Misuse of AI and Governance		Group 5

Expectations:

• Each group will reivew all paper from the provided list, and they may propose additional ones for approval.
• Summaries should be written in Markdown format (supporting images and formulas) and committed to the course's GitHub repository.
• The summary should include the following sections: Introduction and Motivations, Methods, Key Findings, and Critical Analysis.
• The Critical Analysis section should evaluate the strengths, weaknesses, potential biases, and ethical considerations of the paper.
• Summaries must be submitted four days prior to the presentation for review and potential feedback.

Assessment Criteria:

• Clarity and coherence of the written summary.
• Depth of critical analysis and understanding of the paper's content.
• Proper use of formatting and adherence to submission guidelines.
• Timeliness of submission.