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We usually view her in simulated form, but, when seen at the Louvre, up close and in person, she takes on a completely new significance. It seems as if every brushstroke is infused with essence and meaning.

The centuries old masterpiece and the digitized (and often satirized) versions stand side by side in our minds eye. The digital Mona Lisa, of course, is not made up of brushstrokes, but code and, as we shall see, that makes all the difference.

The value of complexity

Complexity is something we usually admire (except, of course, in our significant others). What’s striking about the original Mona Lisa is the intricate detail that makes it a unique work of art. It is that complexity of detail that never makes it into the more widely dispersed verions.

Mathematicians value complexity so much that they have gone to great lengths to define it with a concept called Kolmogorov-Chaitin complexity. Most numbers, even big ones like 1,000,000 easy to simplify it (i.e. 106). Others, like 987,654,321 lend themselves to easy memorization

Some numbers are more difficult. For instance 6,461,333,267 is not only a large number but it is also a prime. There is no way to explain it except by repeating all ten digits in sequence. It is unique and difficult to describe accurately, much like the Mona Lisa.

That’s the essence of complexity. There’s no way to easily simplify it without losing information.

If you want to contain information, complexity is a valuable thing. Your credit card company uses the complexity of prime numbers to protect you by encrypting information. Governments use complex codes to keep secrets. Complexity both preserves meaning and keeps information from wandering off.

The paradoxical charms of simplicity

Simplicity is, of course, the opposite of complexity. Simple information is easy to transmit and share, which makes simple things more popular than complex things.

We often add information to simple messages to ensure that they get through. Our everyday language is filled with redundancy to help insure that messages are passed on accurately, but in truth, we don’t need all the letters that we use.

For instance: vwls rn’t rlly ncssry.

Simplifying by omitting superfluous information has become an intrinsic part of modern life. Transmissions of sound and video are sampled in order to compress them, making them easier to disseminate widely. The computer on the other end will be able to get the gist of the message and then use established algorithms to fill in the blanks.

Information is inevitably lost in compression and transmission which is why the original Mona Lisa is so different from the ones we often see. Those that broadcast media struggle to transmit complex signals in the simplest way possible in order to save bandwidth, getting their messages more widely disseminated, but sacrificing signal quality.

Popularity has a price.

Encoding logic and meaning

Codes are important because our lives are, to a great extent, quests for logic and meaning. We try to make sense of a complicated universe through simplified models that rely on context to aid interpretation. This can be problematic though. Common discourse is fraught with paradoxes that throw codes into disarray.

A famous example is called Russell’s paradox, which can be represented by the simple statement: : “The barber of Siberia shaves everybody who does not shave themselves.” These kinds of contradictions (in this case, sets that are members of themselves) lead to logical circles that cause codes to fail and computer systems to crash.

Bertrand Russell and Alfred North Whitehead tried to solve the problem of paradoxes in their classic work Principia Mathematica. In it they set out rules for restating language into a logical code, which would do away with such inconsistencies. Unfortunately, it was not to be.

In 1931, Kurt Gödel came up with a new code, called Gödel numbering and used it to simplify the statements of Principia Mathematica down to prime numbers. He was then able to show, through proving his incompleteness theorems, that every logical system will contradict itself in the long run.

In other words, while meaning can endure, every logical process will eventually crash, it’s only a matter of time. There is no perfect code.

Selfish codes

The most consequential information to us is, of course, that which is encoded in our genes. Evolution has ingeniously compressed an enormous amount of data into the very simple molecule of DNA, which, by the way, is also highly dependent on context and will fail if given the wrong environment.

While we normally see our DNA as a function of our biology, Richard Dawkins quite famously proposed the opposite view – that our DNA selfishly creates us in order to propagate itself. We are then, simply vehicles for a battle between competing codes.

He then went further. Dawkins also proposed that the meaning of concepts themselves are encoded in memes, which then compete very much like genes do. As Daniel Dennett said, “A scholar is just a library’s way of making another library”

In other words, it’s not always clear who’s coding whom. A particularly interesting case is software developers, who call their work “coding.” Actually, that’s a misnomer, because they write code only as a last resort. Whenever possible, the find and re-purpose code that has worked well in the past.

Memes in code

Just as memes are selfish and information wants to be free (essentially two ways of saying the same thing), media wants to be usable. Simplicity is favored over complexity. Media, in order to become popular, strive to display the least originality possible without loss of essence.

Of course, the artistic impulse is exactly the opposite. As Paul Dirac once said, “In science one tries to tell people, in such a way as to be understood by everyone, something that no one ever knew before. But in poetry, it’s the exact opposite”

Therein lies the primary challenge of communication: to encode creativity while preserving meaning. For when you stand in front of the Mona Lisa and take in the dazzling richness of brushstrokes on canvas, it is undoubtedly her encoded memes that led you to her.

Maybe that’s why she’s smiling…

Greg Satell is a blogger and a consultant at the Americal online media Digital Tonto. You can read his blog entries at

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