Through a team-based, experiential, and interdisciplinary learning model, small groups of U-M graduate and professional students work with faculty to explore and offer solutions to emerging, complex problems. This course is offered through the Law School’s Problem Solving Initiative and the topics vary by semester.
Human drivers make conscious and unconscious choices that have invidious discriminatory implications, from which neighborhoods to drive through or avoid, to how to interact with other drivers based on perceived demographic features. Robotic driving may eliminate some social biases but create many others through machine learning. In this class, multi-disciplinary student teams will apply problem solving tools, learn from experts, and explore potential rules, metrics, tests, and safe harbors that could address algorithmic discrimination. Applying tools and insights they learn throughout the term, students will craft innovative solutions informed by law, policy, engineering, information, and other disciplines.
Pathway Associations
Other SW741 Offerings
The course listings below are provided for reference only. These offerings may be subject to changed of cancellation.
| Course Section | Meeting Time | Action |
|---|---|---|
| 003 | 03:15 pm-06:30 pm | View Course |
| 002 | 03:15 pm-06:30 pm | View Course |