| Week | Day | Type | Topic | Assignees | Papers |
|---|---|---|---|---|---|
| 2 | 09/07 | Discussion | Bias of AI/ML Systems | ||
| 2 | 09/09 | Discussion | Bias of AI/ML Systems | ||
| 3 | 09/14 | Discussion 1 | Bias of AI/ML Systems | ||
| 3 | 09/16 | Lecture | Societal Impact | ||
| 4 | 09/21 | Discussion 2 | Societal Impact | ||
| 4 | 09/23 | Lecture | AI for social good | ||
| 5 | 09/28 | - | Project Description | ||
| 5 | 09/30 | - | Holiday | ||
| 6 | 10/05 | Discussion 3 | AI for social good | ||
| 6 | 10/07 | Guest Lecture | Joanna Bryson | ||
| 7 | 10/12 | Discussion 4 | AI for social good | ||
| 7 | 10/14 | Guest Lecture | Kyunghyun Cho | ||
| 8 | 10/19 | Presentation | Proposal | ||
| 8 | 10/22 | - | Midterm(No Class) | ||
| 9 | 10/26 | Lecture | Detecting bias | ||
| 9 | 10/28 | Discussion 5 | Detecting bias | ||
| 10 | 11/02 | Discussion 6 | Detecting bias | ||
| 10 | 11/04 | Guest Lecture | Dirk Hovy | ||
| 11 | 11/09 | Lecture | AI as Big Brother | ||
| 11 | 11/11 | Discussion 7 | AI as Big Brother | ||
| 12 | 11/16 | Presentation | Progress Update | ||
| 12 | 11/18 | Discussion 8 | AI as Big Brother | ||
| 13 | 11/23 | Lecture | Interpretability, Fairness | ||
| 13 | 11/25 | Discussion 9 | Interpretability, Fairness | ||
| 14 | 11/30 | Discussion 10 | Interpretability, Fairness | ||
| 14 | 12/02 | Guest Lecture | Shakir Mohamed |
Each team consists of two student. The team will be the same when working on a project.
Each team should lead one discussion session which they are assigned.
Everyone should read selected papers before discussion. The team leading discussion should prepare the discussion prompt.
Every discussion consists of two phases:
- Presentation for the papers
- The class divided into small groups(5 people) and do discussion starting from the prompt.
Every team should submit discussion result using google form.