Module overview
Connect incentives, second-order effects, and cross-domain synthesis into a bigger worldview.
Lessons
Parts, Patterns, And Systems
In 1972, a young American scientist named Donella Meadows helped write a book called The Limits to Growth that made some of the first computer models of how the whole planet actually works as a system. Her whole career after that was about teaching people to stop looking at isolated events and start looking at the systems those events live inside. In this lesson you will learn what a system is, practise spotting feedback loops, map a real system from your own life, and capture one insight that changes how you see an issue.
Incentives Drive Behavior
In the late 1990s, a group of economists ran an experiment in a set of daycare centres in Israel. They added a small fine for parents who picked their children up late. Something very strange happened: the number of late pickups went up, not down. The economist who told this story in the book Freakonomics was Steven Levitt, and his explanation changed how a lot of people think about why people act the way they do. In this lesson you will learn to see incentives and constraints behind behaviour, analyse a real-world case, and redesign one small incentive system to produce a better outcome.
Second-Order Effects
In the early 2000s, an MIT economist named Esther Duflo wanted to know something that sounds simple but is surprisingly hard to answer: if you want more families in rural Kenya to sleep under mosquito nets (which prevent malaria), should you give the nets away for free or sell them at a small price? The obvious answers were both wrong, and the real answer only showed up when she looked at the second-order effects. In this lesson you will learn to see past the first-order consequences, map ripples, forecast wider effects, and build a personal checklist for longer-view thinking.
Connect The Dots Across Domains
In his sixties, a particle physicist named Geoffrey West walked into the Santa Fe Institute and asked a strange question: do cities, companies, and animals all grow by the same mathematical rules? The answer was yes, and it changed how scientists think about connections across completely different fields. In this lesson you will learn to see the same issue through multiple lenses, combine insights from different domains into one clearer view, solve a challenge that requires connected thinking, and write a note about what became clearer when the domains connected.