
Interdisciplinary Problem Solving
Fall 2020 Courses:
Fixing Foster Care
Each year, roughly 250,000 children enter the foster care system. Studies show lengthy stays in foster care harm children, yet they continue to languish in the system for too long. Kids who leave the system often experience instability in the homes of their birth parents, adoptive parents, and guardians, or on their own if they age out of the system. In this class, multidisciplinary student teams will hear from leading state and national foster care experts, and they will incorporate insights from law, social work, policy, and other fields. Students will also examine systems that contribute to the problem, including courts and child welfare agencies. At the conclusion of the course, students will present identified solutions to key stakeholders who can implement reforms.
Obstacles to Providing Social Services in Michigan
In the U.S., the federal government funds key social services for the poor. However, individual states — which are rarely the focus of policy debates about social services — are often responsible for overseeing the provision of those services. In this class, multi-disciplinary student teams will focus on challenges to the delivery of social services in Michigan, including programs like Medicaid, SNAP, WIC, and cash assistance. Students will apply problem-solving skills, learn from stakeholders and experts, and draw on insights from health sciences, public policy, law, and other fields to develop solutions that improve the delivery of social services to vulnerable populations.
Connected and Automated Vehicles: Algorithmic Discrimination
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.