A common belief is that Evolution and Intelligent Design are an either/or proposition.
Today I’m going to tie the two together in an elegant way and show that they compliment each other beautifully.
A common criticism of Intelligent Design is that it offers no testable hypothesis.
Today I’m going to lay that accusation firmly to rest with a whole series of predictions about what evolution research will show us in the next 3 to 20 years.
You may or may not have noticed, but Information is always written top-down, not bottom-up. You may or may not have noticed that information also has to be modified or re-written top-down.
Random mutation assumes information is bottom-up. That is the most fundamental reason why that theory is failing. Evolution is a top-down process.
The highest layer of information is intent. All coded information is driven by intent. Intent results in meaning which results in sentences which dictate words which dictate letters.
(Not the other way around.)
Everything I predict in this series, then, comes from a proposition that evolution is an engineered process and is programmed to happen; and that the program itself is intelligent and operates in a top-down fashion.
Onward with my testable hypothesis:
1) Evolutionary adaptation is the work of a “Mutation Algorithm.”
Cells employ a built-in algorithm, which engineers re-arrangement of Mobile Genetic Elements (as observed by McClintock and Shapiro). Genes and Chromosomes are re-arranged in a fantastically beautiful process which produces useful adaptations and new species.
I call this the Mutation Algorithm. It is a program which attempts to evolve when necessary and computes the optimal path to a desired result. This algorithm is described as exhibiting some form of intelligence.
This Mutation Algorithm, in combination with natural selection, explains what random mutation and natural selection cannot.
2) The Mutation Algorithm tests design options like blades on a Swiss army knife. DNA has a huge “bag of tricks” and is able to mix and match combinations of eyes, feet and claws, joints, digits, hair, skin and fur colors and patterns, switching out different “blades” as environments change.
It builds animals on a common chassis of head, spine, heart, lungs, stomach and limbs.
It ferociously defends this core chassis from being corrupted by random mutations, while switching out different variables in the head, spine, heart etc.
3) The Swiss army knife “blades” include variables that adjust the structure of incredibly complex systems with simple changes.
For example the length of a giraffe neck could be “dialed in” by a single gene which controls the length of nerve fibers, muscles, esophagus and number of vertebra, all at the same time
This explains both small and large variations in species. DNA fills the ecosystem with every imaginable variety of life because it’s designed to.
It adjusts these variables until the creature is maximally adapted to its environment.
4) The Mutation Algorithm is normally at rest. It goes to work whenever the population is under extreme stress. This is why we see the pattern of “punctuated equilibrium” in the fossil record.
There are long periods of stability where there is no change, because the Mutation Algorithm is dormant. When there is a crisis, it activates and begins to test novel features.
5) The Mutation Algorithm operates within populations, not just individuals.
The Mutation Algorithm catalogs past mutation attempts so that it does not get “stuck” repeating past failures. Organisms somehow share information so that they can collectively test a wider variety of mutations than any one organism could attempt.
Efforts to find a mechanism by which organisms share this information will eventually be rewarded. And the mechanism that is discovered will be as surprising and revolutionary to biology as Einstein’s theory of relativity was to physics.
6) Evolutionary pathways are not random and purposeless, they are mathematically optimized in advance to reach desired destinations in the smallest possible number of steps.
An analogous process is the Taguchi method used in Quality Control, which creates a very small set of manufacturing experiments, which represent a very large number of possible manufacturing combinations.
It systematically tests them via a “design of experiments” process, then generates a new design which is a nearly optimal combination.
>Thousands of possible design combinations are evaluated with only a few dozen tests.
Then more inputs are gathered, new designs are generated and the test is run again.
I invite you to consider that DNA does something very similar with arrangements of modular biological components, literally calculating and anticipating possible evolutionary steps. It senses inputs from its environment and optimizes the experimental process.
Imagine for a moment, if you will – that same process that DNA uses can be quantified and adapted for use in manufacturing and process control.
Comparisons to Quality Control and manufacturing are very useful when considering evolutionary theories. The theory of Neo-Darwinism, which is now fighting for its very life, always insisted that evolution proceeded as a function of random mutations combined with natural selection.
A direct analogy in manufacturing would be if we made a production line where incoming parts were randomly and carelessly modified; then a QC check simply discarded all unsuitable assemblies at the end of the line.
Can you even think of a more wasteful and inefficient quality control system? Soon it would also result in the most wasteful and inefficient factory imaginable. The employees would be laid off and the plant would close.
You may or may not have noticed…. there is no manufacturing facility in the world that makes products that way. Quality Control is always an extremely deliberate set of inputs combined with rigorous analysis of the outputs.
My hypothesis is that DNA operates much the same way as a Kaizen / Six Sigma manufacturing operation. DNA not only actively participates in the mutation process, it also monitors the natural selection process.
I hypothesize that the genome got from single cells to humans in an incredibly short period of time – that 3 billion years from cells to mankind is an engineering feat of the highest order. That such a feat required the most advanced forms of optimization and as little waste as possible.
We’ve only begun. Stay tuned for future installments, where I’ll discuss “Junk DNA”, show you the layers of information in DNA and new discoveries that await us in computer science.
In later parts I’ll also talk about human genetic engineering, the Human Genome Project, and a new Anthropic Principle that specifically applies to DNA.
Further reading: Swine Flu Virus Mutations and the Evolution of Google Ads
A 21st Century View of Evolution by James A. Shapiro
Evolution as Computation by Laura F. Landweber and Erik WinfreeDownload The First 3 Chapters of Evolution 2.0 For Free, Here – https://evo2.org/evolution/
Where Did Life And The Genetic Code Come From? Can The Answer Build Superior AI? The #1 Mystery In Science Now Has A $10 Million Prize. Learn More About It, Here – https://www.herox.com/evolution2.0