Debunking GTD: Distrust and productive use are not incompatible.

[Paul Keith]

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Among my friends and acquaintances, everybody distrusts Wikipedia and everybody uses it. Distrust and productive use are not incompatible. Wikipedia is the ultimate open source repository of information. Everyone is free to read it and everyone is free to write it. It contains articles in 262 languages written by several million authors. The information that it contains is totally unreliable and surprisingly accurate. It is often unreliable because many of the authors are ignorant or careless. It is often accurate because the articles are edited and corrected by readers who are better informed than the authors.

Jimmy Wales hoped when he started Wikipedia that the combination of enthusiastic volunteer writers with open source information technology would cause a revolution in human access to knowledge. The rate of growth of Wikipedia exceeded his wildest dreams. Within ten years it has become the biggest storehouse of information on the planet and the noisiest battleground of conflicting opinions. It illustrates Shannon’s law of reliable communication. Shannon’s law says that accurate transmission of information is possible in a communication system with a high level of noise. Even in the noisiest system, errors can be reliably corrected and accurate information transmitted, provided that the transmission is sufficiently redundant. That is, in a nutshell, how Wikipedia works.

The information flood has also brought enormous benefits to science. The public has a distorted view of science, because children are taught in school that science is a collection of firmly established truths. In fact, science is not a collection of truths. It is a continuing exploration of mysteries. Wherever we go exploring in the world around us, we find mysteries. Our planet is covered by continents and oceans whose origin we cannot explain. Our atmosphere is constantly stirred by poorly understood disturbances that we call weather and climate. The visible matter in the universe is outweighed by a much larger quantity of dark invisible matter that we do not understand at all. The origin of life is a total mystery, and so is the existence of human consciousness. We have no clear idea how the electrical discharges occurring in nerve cells in our brains are connected with our feelings and desires and actions.

Even physics, the most exact and most firmly established branch of science, is still full of mysteries. We do not know how much of Shannon’s theory of information will remain valid when quantum devices replace classical electric circuits as the carriers of information. Quantum devices may be made of single atoms or microscopic magnetic circuits. All that we know for sure is that they can theoretically do certain jobs that are beyond the reach of classical devices. Quantum computing is still an unexplored mystery on the frontier of information theory. Science is the sum total of a great multitude of mysteries. It is an unending argument between a great multitude of voices. It resembles Wikipedia much more than it resembles the Encyclopaedia Britannica.

The rapid growth of the flood of information in the last ten years made Wikipedia possible, and the same flood made twenty-first-century science possible. Twenty-first-century science is dominated by huge stores of information that we call databases. The information flood has made it easy and cheap to build databases. One example of a twenty-first-century database is the collection of genome sequences of living creatures belonging to various species from microbes to humans. Each genome contains the complete genetic information that shaped the creature to which it belongs. The genome data-base is rapidly growing and is available for scientists all over the world to explore. Its origin can be traced to the year 1939, when Shannon wrote his Ph.D. thesis with the title “An Algebra for Theoretical Genetics.”

Shannon was then a graduate student in the mathematics department at MIT. He was only dimly aware of the possible physical embodiment of genetic information. The true physical embodiment of the genome is the double helix structure of DNA molecules, discovered by Francis Crick and James Watson fourteen years later. In 1939 Shannon understood that the basis of genetics must be information, and that the information must be coded in some abstract algebra independent of its physical embodiment. Without any knowledge of the double helix, he could not hope to guess the detailed structure of the genetic code. He could only imagine that in some distant future the genetic information would be decoded and collected in a giant database that would define the total diversity of living creatures. It took only sixty years for his dream to come true.

Pasting it here because I feel it correlates with some flaws in productivity systems. Most notable though is the ultimate idea that clarity can and even must be achieved in noisier settings in order to be honed rather than secluded.

[Eóin]

It illustrates Shannon’s law of reliable communication. Shannon’s law says that accurate transmission of information is possible in a communication system with a high level of noise. Even in the noisiest system, errors can be reliably corrected and accurate information transmitted, provided that the transmission is sufficiently redundant. That is, in a nutshell, how Wikipedia works.

Shannons Law is about data transmission capacity, binary data being dumped into a noisy channel at one end and yet being able to ensure it can be accurately recovered at the other.

It is not relevant to Wikipedia.

I don't mean this as against you Paul, I know you're only quoting a source, but I really hate it when people subvert very specific science or maths theorem for something utterly unrelated.

[Paul Keith]

Shannons Law is about data transmission capacity, binary data being dumped into a noisy channel at one end and yet being able to ensure it can be accurately recovered at the other.

It is not relevant to Wikipedia.

I don't mean this as against you Paul, I know you're only quoting a source, but I really hate it when people subvert very specific science or maths theorem for something utterly unrelated.

Yeah, I'm not knowledgeable about Shannon's Law but the article reads like it's one big metaphor for information evolution or information transmission.

In that sense, it's relevant to Wikipedia in a stretch. Data as well as clarity of data transmission after all is not really limited to math theorem.

If memetics could be compared to diseases and genes could be given virtues of selfishness, then the theory of Math is in my opinion just as open to metaphors on other issues. This doesn't mean I'm defending the author because certainly I don't really understand what this is all specficially about but it doesn't read as irrelevant to me when it's really portrayed as a big picture thing. Wrong? Sure and I would hope you would explain it further to me but irrelevant...not so much except you're right maybe it is subversive...but can it really be subversive?

After all, who exactly is the audience of the author? He's not selling or making it clearer for bored ADD science interested readers. If anything it reads like a food for thought attempt at a metaphor and thus maybe the author over-stretched his metaphor but I doubt he aims to subvert when the end result is still a confusing mish mash of ideas and analogies and not really an article with a clear cut conclusion.