Algorithmic Specified Complexity Part I: Genesis

On this episode of ID The Future, Robert Marks and Winston Ewert, both of the Evolutionary Informatics Lab, discuss three of their recently published papers dealing with evolutionary informatics, algorithmic specified complexity and how information makes evolution work. This is the first of three segments.

Dr. Winston Ewert, a Senior Research Scientist at both Biologic Institute and the Evolutionary Informatics lab, discusses the mathematical foundation for why we know Mount Rushmore is designed and Mount Fuji isn’t. The mathematical theory of algorithmic specified complexity is introduced and illustrated. A single complex snowflake, for example, displays essentially zero algorithmic specified complexity whereas two identical snowflakes earns a high algorithmic specified complexity. The model discussed by Dr. Ewert can also measure algorithmic specified complexity in units of bits in the context of poker. Dr. Ewert explains how a Royal Flush has a high algorithmic specified complexity of about 16 bits whereas a poker hand with a single pair has essentially zero algorithmic specified complexity. The theory Dr. Ewert discusses is developed in the paper:

Winston Ewert, William A. Dembski, Robert J. Marks II, “Algorithmic Specified Complexity,” in Engineering and the Ultimate: An Interdisciplinary Investigation of Order and Design in Nature and Craft, edited by Jonathan Bartlett, Dominic Halsmer and Mark Hall (Blyth Institute Press, 2014), pp.131-149.

The paper is available online here: https://robertmarks.org/REPRINTS/2015_AlgorithmicSpecifiedComplexityInTheGameOfLife.pdf