Faculty Experiences - Nicholas Gessler
Human Complex Systems
What matters most to you in your teaching?
How are you using technology as a tool to achieve your teaching goals?
How have your students responded to your use of technology?
What new goals do you have for using technology in teaching?
Analyze complex systems
Test & critique theories
Class web site
Using Computer Simulation to Understand the World
The basic question is, "How do we come to know and understand the world around us?" As a social scientist, I focus my attention on the cultural world, the world of people, their ideas and technology. Fifty years ago we discovered computation, and ever since we have been learning how to explain the world in computational terms. Computation is an extremely important discovery, and computers are an extremely important innovation. But, why do I call this a discovery? Because it is the realization that computation is built into everything around us: in the physics of the world, in societies from ants to humans, and even in our minds. This is what I try to get across in my classes. I try to get my students to think about the complex world of human behavior in complex terms that are difficult, if not impossible, to express in natural language. I try to get them to describe those thoughts in the artificial languages that computers understand. I try to help my students acquire the skills they need to turn their complex ideas into computer simulations. We describe the world as elemental parts and processes, and then connect them together in complex ways to see how they interact to produce the behavior of the whole. We try to understand phenomena by describing them at a local level of detail and then running "what-if?" experiments to see what happens at a global level of analysis. Empowerment comes from our ability to describe a system and then study its entailments automatically. This is what's behind the powerful idea of emergence.
I do research in artificial culture. It has its roots in artificial intelligence, artificial life and artificial societies. The idea is to create a population of artificial humans, imbue them with artificial perceptions, beliefs and behaviors, then put them inside a computer along with an artificial social and physical environment, turn it on, and watch what happens! It's a way to test theories in social science for logical consistency, a way to embrace the empirical fact that cultures are composed of individuals, and it's a way to open one's eyes to seeing new complexities in how real human individuals behave. In brief, that is the project of artificial culture. [www.sscnet.ucla.edu/geog/gessler/cv-pubs/02comocultevo.htm]
All of my courses have been held in computer classrooms equipped with one computer for each student. We get underneath the hidden assumptions made by other people's software by writing our own from scratch. We write our simulations in the ubiquitous language of C++, emphasizing the importance of visualizing the behavior of the simulation with bold and compelling graphics. We begin with small examples that are counter intuitive and complex, like Conway's Game of Life, a simple system which spontaneously creates a complex ecosystem of strange creatures from a primordial soup of almost nothing. By writing our own simulations we begin to learn how complex systems work. We learn to understand what works and what does not. We learn the possibilities and limitations of our predictive models, how to build them and evaluate their potential for helping us understand the world. We learn what simulations and predictions can and cannot do.
All of my classes are linked from my web portal. Many of our text and resource materials are online. There's an "Index" icon linking to over 200 web pages I've created. There's a "Simulation" icon linking to over 100 simulations we have written. On these same pages are instructions on how to write simulations, the executable files themselves, source code, and project files for working with the Borland platform. We've received over 20,000 hits to our simulation pages and three awards.
There are no published textbooks for these subjects, so essentially I have had to write my own. It resides, as something of a manuscript, on our web site. It as an essential resource. A small class size of from 10 to 15 students is optimal for sharing ideas and working as a group. I have taught different mixes of this material for the Geography and Design/Media Arts Departments and the Honors Collegium. I will be teaching an improved version as a laboratory in our new Human Complex Systems Program. Students have been enthusiastic, many saying that it has been one of the most interesting, eye-opening classes they have ever taken at the university. They come away with a feeling of empowerment, knowing something of how computers work, envisioning a myriad of applications to a lot of different disciplines, and with a critical appreciation of simulations used for public policy decisions.
Students enrolled in my courses are from all corners of the campus -- about 50/50 from the "north" and "south." They are an even gender mix attracting an equal number of freshmen, sophomores, juniors, seniors and even some grads. Most participants have never had any previous computer programming experience at all, and yet they all complete the courses with the newfound confidence of making computers "dance to their own tunes." The variety of students in these classes is one of the delights of teaching. Their different experiences and interests adds to the richness of the examples we consider.
Thinking back to January 23, 1950, the cover of Time Magazine asked the question, "Can Man Create a Superhuman?" This was the first mainstream critique of computation. It quoted the "computists" of the time discussing computers as innovative, creative devices, thinking machines and speculating what part they may play in the future. We are now that future, and yet most of what we do with computers is 50 years behind their imagination. We routinely use computers as glorified filing cabinets, serving out pictures and text at our command. What I am trying to do is something different. I would like to enable students to catch up with and surpass the larger visions that these pioneers articulated half a century ago.
Having all classes online is an important step towards sharing knowledge worldwide. Wireless technologies will add to that. Each of these innovations introduces new possibilities and challenges. For the classes that I teach I need one computer for each student. As an anthropologist / archaeologist, with a broad and deep view of the evolution of culture and technology, I wonder where these smart artifacts will lead us. Although I am a technophile, I decline to use a cell phone and don't receive broadcast TV. At times I like the isolated wilderness of the mountains and deserts. My goal is to use technology to understand our relationships with one another and with the technologies we create. This is why I have focused on using computers to help us understand the complexities of culture. How did we get where we are? Where are we going? Simulation is a powerful way of understanding the world, in some ways more powerful than language. Understanding complexity is one thing that computers are very good at doing, and one thing that we as humans have great difficulty comprehending.
Four years ago, many of my colleagues told me it would be impossible to teach courses like these. Despite their warnings, all my students have succeeded. Give me two hours, and I will help you build a world, to begin with Conway's artificial world. Students understand the complexities of video and computer games. Not surprisingly, these games are built from many of the processes of real life. Students are accustomed to exploring artificial fictional worlds. They expect complexity, and they can readily understand the dynamics of exploring artificial factual worlds as well. What better way to explore the entailments of a cultural or social theory? We are moving away from the view of education as a tour or lecture, towards the view of education as an exploration: You have a question. You think you have an answer and you try it out. You have another question and a prospective answer. You may succeed or fail but you learn along the way. In essence, this is the scientific method. In part, this is what play and planning are about. I think exploration is a more effective, more natural and lasting approach to learning.