Blessings to all. Humans cannot successfully “direct our own evolution” because we’re nowhere near as smart as the intelligence that created life in the first place and we do not have the ability to gather as much data as the Mutation Algorithm can gather.
Humans will not “take over” our own evolution in some triumphal Eugenics experiment of the future.
The very notion of engineering our own evolution is preposterous. It will continue to be preposterous until the genome is fully understood, an achievement that is at least several hundred years away.
5. This new view of evolution as an engineered process (i.e. the genome uses concepts comparable to Six Sigma, Kaizen and Quality Control to adapt to its environment) will lead to specific discoveries and systems in DNA that can be directly applied to man-made systems.
This is in stark contrast to Darwinism, which is virtually useless for teaching anyone how to design anything.
(After you learned about Darwinian evolution, what did you suddenly know how to do or build as a result? Nothing!)
Our cave-man ancestors knew that the fittest survive. There’s nothing profound about that; and Random mutation as an alleged path to improved designs is useless.
If Taguchi or other Continuous Improvement methods are the fastest way to improve a design, a random walk is actually the fastest way to destroy a design.
(Also notice that even in the best of circumstances, like Dawkins ‘methinks it is like a weasel’ program, Random Mutation still does not work without a pre-programmed selective goal.)
Genetic Algorithms that mindlessly grind through millions of permutations are notoriously inefficient, which is why their use in the software industry is so limited.
Thus the most potentially productive hypothesis for evolution is that it follows an algorithm that’s pre-engineered for maximum improvement within the smallest possible number of steps. A program that starts with single cells and ends up with human beings in only 3 billion years is an engineering achievement of the highest order.
Reverse-engineering the Mutation Algorithm will be one of the most powerful future applications of applied science. To understand this 21st century view of evolution will be to know something that has immensely practical, real-world applications.
Eventually, unlocking the secrets of the Mutation Algorithm will be the “Holy Grail” of biology. It’s the secret to everything. The 20th century theory of random mutation will be seen as being just as foolish and detrimental to the practice of real science as the church’s opposition to Galileo.
6. The adaptive capabilities of DNA (the Mutation Algorithm) are best understood as a function of intelligence. This adaptive algorithm that makes evolution possible does not blindly plod forward the way man-made programs do, but makes remarkably fit choices in environments that it has not faced before.
7. DNA’s information storage is an optimal combination of physical data density, error-minimizing redundancy, and data compression.
Common sense observation: The entire human genome builds a 3-dimensional biological machine with a lifespan of 70-80 years and all the data necessary to do this can fit on a 750 Megabyte CD-ROM. A DNA molecule is thousands of times denser than a CD-ROM. Windows Vista can’t begin to fit on a CD-ROM, it has thousands of bugs and requires a never-ending series of software patches.
A man-made data storage program (i.e. CAD program) would require hundreds, perhaps thousands of times more storage space than DNA, to accurately represent the human body.
Hypothesis: DNA currently stores data at a higher density than any man-made digital information storage system, and as we approach or attempt to surpass the DNA benchmark we will encounter physical limitations that result in severe tradeoffs (i.e. greatly increased possibilities of long-term data loss).The resources DNA devotes to error correction are extensive and absolutely necessary. In DNA a single sequence of data is used in more ways and does more jobs than researchers presently imagine.
In DNA, nothing goes to waste.