Wicked Problems

3 Credits · Level: Undergraduate

Wicked Problems: Learning to Plan and Decide in Human-AI Teams This course examines how teams learn to work on wicked problems in an AI-augmented world. Wicked problems are complex challenges defined by uncertainty, competing values, and incomplete information, where progress depends as much on problem framing as on solution choice. Students work in peer and intergenerational teams on live, unresolved challenge problems that require careful problem articulation, structured planning, and defensible decision-making. The course follows a three-phase structure: foundational preparation, challenge lab work, and synthesis and reflection. Students begin with structured training in using AI systems and managing AI agents as part of human-AI teams. In the challenge lab phase, student teams work collaboratively—both with peers and in structured, time-bounded engagement with experienced practitioners—to frame problems, develop and iterate solution plans, and stress-test decisions under real-world constraints. AI is used throughout the course to support problem framing, option exploration, and stress-testing of plans in simulated environments. A distinctive feature of the course is short, intensive collaboration blocks with experienced executive practitioners, exposing students to real decision contexts and constraints and reinforcing learning through practice. Executive participants will engage in time-bounded collaboration with students to introduce real-world constraints and support intergenerational learning and workforce-relevant collaboration in challenge-based problem solving.