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Applying the Theory of Intelligent Design

What are ID's implications for economics, metaphysics, and computer science?

As my PhD advisor Dr. Robert Marks likes to say: “You have to make the queen of the sciences get down and scrub the floors.” Intelligent design (ID) is a science, and so ID has to get down and scrub the floors.

To further this goal, I’ve come up with a schema for the ways in which ID can be applied, and what it in fact means for ID to be applied. The upshot of this schema is not only to guide brainstorming, but it also demonstrates that ID is already applied in many areas, unbeknownst to all. As they say, the best way to get something done is to take credit for someone else’s work.

First, let’s identify what ID is. ID is the theory that intelligent activity can be empirically distinguished from the results of chance and necessity. While commonly applied to the biological history, ID is fundamentally a much more general theory.  The mathematical basis of ID is eruditely defined in William Dembski’s The Design Inference and The No Free Lunch Theorem.

There are two main facets to Dembski’s work.  The first is a quantitative method of measuring intelligent design, known as complex specified information (CSI), which is related to Shannon entropy and Kolmogorov complexity.  The second is a mathematical theorem known as the “no free lunch theorem.”  Together, these theorems seek to demonstrate that intelligent design is both detectable and cannot be attributed to any combination of random or deterministic process (i.e. physics, chemistry, biology, etc.), even over an extremely long period of time.

Theoretical, But Practical

It all sounds very theoretical, yet at the same time it turns out to be very practical. So, let’s get down to brass tacks and identify abstractly the ways such theories can be applied in a practical arena.

For every instance of intelligent design, there is a designer and the designed artifact. The most obvious way to apply the design inference is to identify arenas where it is useful to distinguish intelligent design from normal processes in a quantitative manner. Many such areas abound in the computer industry:

  • detecting secret communication, i.e. stenography
  • catching computer hackers
  • identifying computer viruses
  • distinguishing genetically engineered organisms from natural organisms
  • isolating security credentials in vast troves of computer code
  • improving computer network speed and bandwidth
  • financial and political fraud

We can also flip the design inference on its head. While the design inference only guarantees true positives, so we can’t use it to identify instances of non-design, what we can still do is identify when design is invalidly inferred, i.e. missed a step or two in the design inference. A number of uses for this inverted design inferences:

  • filtering out invalid stock market prediction strategies
  • reducing medical overdiagnosis
  • identifying stolen identities

The mathematics that makes the design inference work is often subjected to ridicule and controversy.  Something practical to do about this is to abstract out the mathematics from the design inference and show that the mathematics can be applied in many areas, not just intelligent design, so there is nothing wrong with the mathematics.

  • making machine learning algorithms generalize
  • lossless digital communication channels
  • proving self-fed artificial intelligence becomes gibberish
  • cryptographic authentication

The above lists contain many well-established technologies, including technologies that allow you to read this article. This indicates the theory behind intelligent design is solid. What is the good of that, you may ask, if these things are already done? Consider Newton’s discovery of the law of gravity. People still fell off cliffs before Newton made his discovery, but they only launched rovers to Mars after Newton’s discovery. Similarly, by identifying the law behind the technologies revolutionizing our world we can progress even further.

We can go in another direction and take a step back to think about the implications of intelligent design being true in everyday life. There are a number of scientific and technical areas that are not neutral when it comes to intelligent design. So first, the big picture of intelligent design being true, which is a metaphysics of intelligent design:

  • many areas of life contain vast troves of information
  • the mind has the ability to create information
  • information is not reducible to the physical, i.e. chance and necessity

Speaking to our present moment, these principles imply general strategies for picking companies to invest in, and companies to short. Companies that base their business case on the human mind being completely replaced by computers will fail as long as they stay true to their principles. On the other hand, companies that use humans to create the AI datasets will prosper, as well as AI companies that optimize the tradeoff between humans and computers. Companies that assume there is a lot of information to be gleaned from the genetic code, such as biotech companies, will prosper.

Economic Implications

Even more broadly, the theory of intelligent design has economic implications. Economies can only grow if something is created. Both energy and matter are conserved. That leaves information as the thing that can be created. Only the human mind can create information, and the ability to create information is maximized when the mind is not constrained by chance and necessity. So, this means that an economy that maximizes free, creative minds will be the most successful.

The stock market is an expression of the value of information. It is the one place where information directly creates monetary value. No physical medium is necessary. While there is a lot of algorithmic trading that happens, the algorithms are derivative of human-generated information about the market.

Cryptocurrencies are another interesting take on intelligent design metaphysics. Prior to cryptocurrencies, all forms of currency were based in some physical medium of exchange. Cryptocurrencies, like bitcoin, are the first purely informational currency.

Finally, taking a break from the purely practical, and venturing into the more speculative, intelligent design provides insight into the humanities. Gödel proved that ideas transcend symbolic representation, which is equivalent to physical processes being unable to create information. Philosophy supports intelligent design through Platonism, Aristotle’s four causes, and mind realism. The traditional division between fantasy and sci-fi can be seen as two sides of the intelligent design coin: fantasy deals with the designers and sci-fi deals with the designed artifacts.

To broadly summarize the schema I used for this analysis of applied intelligent design, I broke the concept into three areas:

  • math: complex specified information, active information, and the no free lunch theorem
  • theory: design inference, irreducible complexity, and genetic entropy
  • reality: designers, designed artifacts, and information

In conclusion, this short article just scratches the surface of how widely intelligent design theory can be applied. I hope it gives you some stimulating food for thought!

Eric Holloway

Senior Fellow, Walter Bradley Center for Natural & Artificial Intelligence
Eric Holloway is a Senior Fellow with the Walter Bradley Center for Natural & Artificial Intelligence, and holds a PhD in Electrical & Computer Engineering from Baylor University. A Captain in the United States Air Force, he served in the US and Afghanistan. He is the co-editor of Naturalism and Its Alternatives in Scientific Methodologies.

Applying the Theory of Intelligent Design