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Understanding Complexity

Understanding Complexity

Professor Scott E. Page Ph.D.
University of Michigan

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Understanding Complexity

Understanding Complexity

Professor Scott E. Page Ph.D.
University of Michigan
Course No.  5181
Course No.  5181
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Course Overview

About This Course

12 lectures  |  30 minutes per lecture
Recent years have seen the introduction of concepts from the new and exciting field of complexity science that have captivated the attention of economists, sociologists, engineers, businesspeople, and many others.

These include

  • tipping points, the sociological term used to describe moments when unique or rare phenomena become more commonplace;
  • the wisdom of crowds, the argument that certain types of groups harness information and make decisions in more effective ways than individuals;
  • six degrees of separation, the idea that it takes no more than six steps to find some form of connection between two random individuals; and
  • emergence, the idea that new properties, processes, and structures can emerge unexpectedly from complex systems.
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Recent years have seen the introduction of concepts from the new and exciting field of complexity science that have captivated the attention of economists, sociologists, engineers, businesspeople, and many others.

These include

  • tipping points, the sociological term used to describe moments when unique or rare phenomena become more commonplace;
  • the wisdom of crowds, the argument that certain types of groups harness information and make decisions in more effective ways than individuals;
  • six degrees of separation, the idea that it takes no more than six steps to find some form of connection between two random individuals; and
  • emergence, the idea that new properties, processes, and structures can emerge unexpectedly from complex systems.

Interest in these intriguing concepts is widespread because of the utility of this field. Complexity science can shed light on why businesses or economies succeed and fail, how epidemics spread and can be stopped, and what causes ecological systems to rebalance themselves after a disaster.

In fact, complexity science is a discipline that may well hold the key to unlocking the secrets of some of the most important forces on Earth. But it's also a science that remains largely unknown, even among well-educated people.

Now you can discover and grasp the fundamentals and applications of this amazing field with Understanding Complexity. Professor Scott E. Page-one of the field's most highly regarded teachers, researchers, and real-world practitioners-introduces you to this vibrant and still evolving discipline. In 12 lucid lectures, you learn how complexity science helps us understand the nature and behavior of systems formed of financial markets, corporations, native cultures, governments, and more.

What Makes a System Complex?

What defines a system as complex, as opposed to being merely

View Less
12 Lectures
  • 1
    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. x
  • 2
    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. x
  • 3
    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. x
  • 4
    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. x
  • 5
    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. x
  • 6
    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. x
  • 7
    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. x
  • 8
    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. x
  • 9
    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." x
  • 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. x
  • 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. x
  • 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. x

Lecture Titles

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Scott E. Page
Scott E. Page, Ph.D.
University of Michigan

Dr. Scott E. Page is Leonid Hurwicz Collegiate Professor of Political Science, Complex Systems, and Economics at the University of Michigan, where he has taught since 2000. The holder of a master's degree in Mathematics from the University of Wisconsin and a Ph.D. in Managerial Economics and Decision Sciences from Northwestern University, Professor Page has also been Professor of Economics at the California Institute of Technology and at the University of Iowa. For the past 15 years, he has maintained an active involvement with the Santa Fe Institute-the interdisciplinary think tank recognized as the nerve center of research into complexity theory-where he is an external faculty member. His many honors as both scholar and educator include teaching awards earned at Cal Tech, Northwestern, and Michigan. The author of The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies and the coauthor of Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Professor Page has also lectured, consulted, and published across a diverse range of disciplines, including economics, political science, ecology, physics, management, public health, and computer science.

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Reviews

Rated 4.4 out of 5 by 93 reviewers.
Rated 4 out of 5 by Great content & examples, but not enough graphics A great course that covers a lot of the basics of complex systems, with clear and appropriate examples. The major drawback is a lack of graphics to illustrate all the points in particular the section on complex networks. It seems rather strange to teach complex networks, and their properties without showing any complex network image. It's like teaching someone how to paint with a canvas but no paint brushes...? Otherwise, good content and good speaker. May 25, 2015
Rated 3 out of 5 by nice overview, not enough graphics Complexity sounds like a subject that would have a lot of great visual aids to help understand, but this course was primarily a film of watching the professor talk. It could have been audio-only with little loss in comprehension, which id disappointing. I feel I learned something from this course, but would have learned the same amount if I had listened to it while commuting instead of spending 6 hours in front of the TV. April 23, 2015
Rated 5 out of 5 by Excellent introduction to topic Professor Page presents a well-paced overview of the subject of complexity that was greatly appreciated by me because I had had little understanding of the subject matter. His use of analogies and examples helps one grasp the essentials of the topic. The course is definitely worthwhile viewing. March 24, 2015
Rated 3 out of 5 by Tangled metaphors are difficult to follow I believe that complexity science is a fascinating and important field, but this class disappointed me. The biggest problem was the style of teaching, which relies heavily on a wide variety of metaphors. I found the metaphors difficult to follow, but there was no alternative -- the lecture studiously avoids mathematics and theoretical terminology. Eventually I discovered that the provided Guidebook uses a more direct approach. Overall, I felt the course lacks depth. Great claims were made for complexity science, but the presentation did not present success stories to back up those claims. January 11, 2015
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