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This is quite a common teleological argument known as the Watchmake Analogy - https://en.wikipedia.org/wiki/Watchmaker_analogy

Instead of going over the common ground, I wish to present to you some examples of Computer Science (and other areas) finding the exact opposite (that is complex systems often have no defined controller or designer) is true.

Time after time, Computer Scientists, Physicists, Mathematicians and Biologists modeling behaviors of fractals, bacteria, flocking birds, ants, fluid, fish and even people have learned that systems with very simplistic rules can produce insanely complex behavior.

NASA famously developed a program that would design antennas with great success: http://www.nasa.gov/centers/ames/news/releases/2004/04_55AR.... , these antennas worked extremely well, but were created by a computer following a few "simple" rules, but the results were outstanding. There is an entire branch of Computer Science dedicated to researching Evolutionary Algorithms(https://en.wikipedia.org/wiki/Evolutionary_algorithm ), these algorithms produce solutions.

Now if I was to say to you that I was going to start a company with a few workers, each worker could do what they wanted at any time and in 5 years I expected to have to giant skyscraper (which would be constantly cleaned - remember I am not telling anyone to clean!), thousands or millions of workers and a constant supply chain. You would probably call me crazy (mostly for not having any plan at all!), yet almost this exact situation happens all across the world, every single day and has been doing so for millions of years.

Ants. Ants as you may know live in colonies, and generally produce huge underground nests. They are often able to find the shortest path to food and building supplies, the nests are kept free of obstacles and defended to the death. Yet, there is no central controller (the "queen" is a misnomer, all she does is give birth) that indicates where the tunnels go, noone is telling an ant what to do at any other time. The system evolves naturally out of very simple genetic rules and is based on communication between peer ants. Deborah Gordon gave a brilliant TED talk on the subject of how clever ants (or at least collections of ants) can be : http://www.ted.com/talks/deborah_gordon_digs_ants.html

(Note: I am not advocating trying to form a company as described above!)

A few books for those who want to research further into this fascinating area:

http://www.amazon.com/Computational-Beauty-Nature-Exploratio... - The Computational Beauty of Nature - Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation

http://www.amazon.com/Turtles-Termites-Traffic-Jams-Explorat... - Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds - The book that started me in this field

And some Google (other search engines are available) search terms:

- Fractals - Ants / Termites/ Turtles Behaviour - Flocking Algorithms - Cellular Automata




I see where your going with this and you are right. In any of these scenarios there are no central controllers identified. At the same time these do not deal with identifiable traits the display a signature of an "originator". For instance with the antennas, there was still an initial program/programmer that designed the program that would carry out instruction to design antennas. With the ants we are still not dealing with the how did ants get here? Why do ants have such a variety of complex and unique genetic structure design?

  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1208186/
What I'm getting at is at the root level there always seems to be a implication or inference of design. Yes, these design patterns seem to formulate behavior and gradual change within their domain. At the same time the domain of change is limited to measurable spectrum of analysis. Who defines these domains? Who set the spectrum in which they are distributed? At the lowest level of biological organization who initially places the constraints in which these systems and species can move and evolve.




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