Professor: Margot Gerritsen

4.00 credits

• CRN 32271: Tuesday, 2:00-3:50 PM / Thursday, 3:00-3:50 PM @ ∗LIB 122

∗Tuesday meetings remote in weeks 1, 3, 5, 7, 9; in-person weeks 2, 4, 6, 8, 10 / Thursday meetings always remote

Imagine a country (Costa Rica in this case), which used to tax imported new cars at 400%, lowering the import tax down to 100%. Still high, but now allowing many more citizens to own and drive a car, leading to a massive increase in car density and subsequent breakdown of infrastructure in many places, increased pollution, and gridlock. The measure was passed without allocating the necessary increase in infrastructure needs. The negative consequences of this seemingly attractive and logical tax reduction were unintended and, in hindsight, seem completely predictable. Or imagine a state, California in this case, creating an electric car incentive for low income people that ends up being taken advantage of mostly by people who are low income yet high wealth (eg retirees) instead of the target group. This unintended consequence of using the wrong metric for participation also seems predictable. 

Unintended consequences of well-meaning, or misinformed decisions, are widespread. What causes them? How can they be avoided? What are possible large and impactful unintended consequences of decisions being made today or soon? Those are the kind of questions discussed and investigated in this course.

We will look at past decisions across industry, government, academia and societies at large. Guest experts from around the US and some from overseas will help us understand and analyze the decision processes. We will also look at important developments today and analyze the potential unintended consequences they may bring about. Topics are chosen from a large pool including the two examples given, wildland fires, the Deep Water Horizon disaster, the Tortilla crisis, social media, and emergency healthcare, amongst others. 

This class is highly interactive and collaborative. Students will conduct individual and group projects and analyses and report on findings through written and oral reports and presentations. 

This course will help you develop critical thinking skills, will broaden context and deepen understanding of complex systems and we hope it will allow you to become a stronger and better prepared participant in decision making processes in your career and personal life. 

Note: this class will be taught primarily on Zoom in a synchronous remote format, with in-person class meetings on the Tuesdays of Weeks 2, 4, 6, 8, and 10.

Dr. Margot Gerritsen is Emeritus Faculty in Energy Science and Engineering and Computational Mathematics at Stanford University. The founder of Women in Data Science Worldwide, she uses data, computer simulation, and mathematical modelling to analyze diverse engineering and natural processes including coastal ocean dynamics, reservoir flows and vehicle transport and emissions.