Discover and grasp the fundamentals and applications of the amazing field of complexity science with Understanding Complexity. Professor Scott E. Page—one of the field's most highly regarded teachers and researchers—shows you how complexity science helps us understand the nature and behavior of financial markets, corporations, native cultures, governments, and other systems that play important roles in our increasingly complex world. By the conclusion of the course, you'll have attained a new lens through which to better view and make sense of your world.
Understanding Complexity
Discover and grasp the fundamentals and applications of the amazing field of complexity science with this course that helps you understand the nature and behavior of financial markets, corporations, native cultures, governments, and other systems.
Overview
About
Professor Scott E. Page received a B.A. in Mathematics from the University of Michigan and an M.A. in Mathematics from the University of Wisconsin–Madison. He then received his M.S. in Business and his Ph.D. in Managerial Economics and Decision Sciences from the Kellogg School of Management at Northwestern University. He completed his Ph.D. thesis under the guidance of Stan Reiter and Nobel laureate Roger Myerson. He has been a Professor of Economics at the California Institute of Technology and The University of Iowa and is currently Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics at the University of Michigan. At Michigan, he is also a Senior Research Scientist at the Institute for Social Research, a Senior Fellow in the Society of Fellows, and the Director of the Center for the Study of Complex Systems. In addition, Professor Page has been a long-time External Professor for the Santa Fe Institute, an interdisciplinary think tank devoted to the study of complexity. In 2011, he was elected to the American Academy of Arts and Sciences. Professor Page has won outstanding teaching assistant awards at the University of Wisconsin–Madison and Northwestern University, the Faculty Teaching Award at Caltech, and the Faculty Achievement Award for outstanding research, teaching, and service at the University of Michigan. Professor Page’s research interests span a wide range of disciplines. He has published more than 60 papers in a variety of fields, including economics, political science, computer science, physics, geography, public health, business, philosophy, and complexity. In addition, he has served on dissertation committees for students in more than 10 departments. In recent years, his core interest has been the various roles of diversity in complex adaptive systems, such as economies and ecosystems. He is the author of Diversity and Complexity; Complex Adaptive Systems: An Introduction to Computational Models of Social Life (with John H. Miller); and The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies . All three books were published by Princeton University Press. His most recent book, The Model Thinker: What You Need to Know to Make Data Work for You, provides a toolkit for people to be able to leverage data and information to their advantage. A popular speaker, Professor Page has appeared at the Aspen Ideas Festival and the World Economic Forum and before numerous corporate and nonprofit audiences around the world, including Google, Ford, Genentech, the International Monetary Fund, and the Association of American Medical Colleges. He has also recorded Understanding Complexity with The Great Courses. Professor Page lives with his wife and two sons in Ann Arbor, Michigan.
Trailer
01: Complexity—What Is It? Why Does It Matter?
Learn what the experts mean when they talk about "complex" systems. Discover why these networks of diverse, connected, and adaptive entities acting in interdependent ways are so powerful, and why understanding them is crucial to so many disciplines.
34 min
02: Simple, Rugged, and Dancing Landscapes
Using the concept of a mountainous landscape as both metaphor and mathematical object, you begin to grasp the ways in which concepts like "rugged" or "dancing" landscapes—where adaptation and learning are vital for survival—can be visualized even by nonmathematicians.
31 min
03: The Interesting In—Between
You develop your understanding of complexity's key components of interdependence, connectedness, diversity, and adaptation/learning. And you learn—by figuratively dialing the strength of each of these components up or down—why the proper balance between them is essential if a system is to be complex.
32 min
04: Why Different Is More
Variance and diversity have very different meanings in the world of complexity theory. Grasping that difference puts you on the way to understanding how complex systems achieve diversity and why diversity enables them to be both innovative and robust, maintaining functionality even when the system is disturbed.
32 min
05: Explore Exploit—The Fundamental Trade-Off
Actors in complex systems face a constant tradeoff. Do they exploit the knowledge already learned in past explorations to achieve a solution? Or do they continue to explore, seeking an even better solution? Learn the pros and cons of each, and how the best balance can be achieved.
33 min
06: Emergence I—Why More Is Different
One of the most fascinating ideas in complexity theory is that of "emergence", the spontaneous creation of order and functionality from the bottom up, with no "central planner" putting them into place. You gain an appreciation of the two kinds of emergence and why each is a source of wonder.
32 min
07: Emergence II—Network Structure and Function
Continuing the discussion of emergence, you see how emergence applies to networks and why network theory has become such an active discipline. And you understand how modern complexity theory adds to the study of networks the previously ignored element of "space."
33 min
08: Agent-Based Modeling—The New Tool
Agent-based modeling—in which computers model complex systems from interdependent agents—may be complexity theory's most promising tool. Its full potential hasn't yet been realized, but this lecture offers a taste of what it can already achieve in disciplines as disparate as fire prevention and disease transmission.
31 min
09: Feedbacks—Beehives, QWERTY, the Big Sort
Drill even deeper into the implications of interdependent agents as you focus on the idea of "feedbacks"—both the positive ones, in which "more creates more," and the negative ones, in which "more creates less."
32 min
10: The Sand Pile—Self-Organized Criticality
Complex systems often create large events. Using the example of how a single unscreened passenger in Atlanta delayed flights and passengers across the nation, you are introduced to one of the key concepts that explain how complex systems can be so powerful.
32 min
11: Complexity versus Uncertainty
There is a vast difference between thinking of events as "random" and recognizing them as the output of a complex system. Explore three conventional explanations of randomness before turning to a fourth—the interdependent rules-based analysis offered by complexity theory.
33 min
12: Harnessing Complexity
Although complex systems can't be controlled, we may well be able, with proper respect, to harness them. Learn why conventional decision theory doesn't work in complex environments and what a proper use of complexity theory might promise us instead.
33 min
