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Team:ETH Zurich/human/overview
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Revision as of 08:51, 8 October 2014
Overview
Complexity
Complexity does not have a unique and absolute definition. It is highly relative and variable. However, we encounter it everyday. It has been strikingly apparent throughout our iGEM experience. Neil Johnson suggested that "Even among scientists, there is no unique definition of Complexity. Instead, the scientific notion of Complexity – and hence of a Complex System – has traditionally been conveyed using particular examples of real-world systems which scientists believe to be
complex." Here are some illustrations of complexity we came across during the course of our project.
- We aim to generate a pattern using bacteria on a grid based on a simple rule. In our particular case, we want to see triangles pop up. This property is called emergence. It is typical for complex objects. The most fundamental part of our project is intimately linked with complexity.
- We work with living cells, namely bacteria. Biology often gives unpredictable results, coming from the very core essence of life. Uncertainty is also one of the main property of complexity.
- Moreover, while designing our system, we tried to cut down to the most simple functions. We simplified. The simplification process negates the intrinsic complex properties of the whole. It sets boundaries to possible interactions.
The main characteristics of complexity can be retrieved in Neil Johnson's work. He defines complexity as the "study of the phenomena which emerge from a collection of interacting objects." In simpler words, complexity is something with many parts. Emergence and uncertainty can not be dissociated from it. Relationships between subparts are keys to understand better why a complex whole does not correspond to the sum of its parts.
Scientists, in particular biologists, are confronted to complexity in research. How does one deal with complexity?
Should scientists consider that subparts of a complex entity are mixed in a both ordered and unorganized way, accept uncertainty, and try to take it into account? Or should they consider that parts are strictly ordered, and that complexity arises from simple parts by following rules?
The first approach is needed to take into account uncertainty of intrinsic complexity of the parts we consider and of the environment. The second approach is necessary to understand the parts better in order to be able to predict results.
Our Approach
The main focus of our project lies in complexity. How does it emerge? How can we handle it? Additionally, what can we learn from it and how can we use it?
Our human practice project attempts to answer these questions by focusing on four different components: listening, discussing, thinking and sharing.
.
The first component consists of a survey regarding complexity. By listening to the public we learn about the existing ideas of complexity and how people relate to it.
Our second component involves interviews with experts from different backgrounds. These discussions focus on the complexity existing in their field and how they deal with it which enables us to improve our understanding of complexity as a whole and how we could profit from this profound, interdisciplinary knowledge. The various methods of resolution are summarized and compared in an essay.
In our third component, we bring elements from the survey, from interviews, from further reading together. Thinking on how our project and science, in general, relates to these topics.
Finally, we impart or share knowledge via different platforms like high school lectures and science slams. Here, we aim to explain the fundamentals of synthetic biology and how it can be a way to approach complexity.
Conclusions
