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At Mind Matters News: Can wholly random processes produce information?


Can information result, without intention, from a series of accidents? Some have tried it with computers…

Michael Egnor: Many evolutionary biologists claim that all of the information present in living things got there by natural selection of randomly assorted variation. Is that true? It’s very clear that living things contain a lot of information. Is it possible for the Darwinian process of random heritable mutation and natural selection to generate all that information in biology or even any of it?

Robert J. Marks: My background is not in biology but in computer science and computer engineering. And one of the things we do is artificial intelligence. And I think maybe your question — translated to artificial intelligence — is: Can anything happen in artificial intelligence from totally random, unguided mutations and processes? And the answer is absolutely not. We did a lot of work.

Winston Ewert and design theorist William Dembski did a lot of work analyzing programs that were purported to generate information.

With the advent of the computer, people said, evolution is such a slow process. It’s going to take us years and years in the laboratory to do anything. But if we have a computer, we can take these Darwin algorithms, simulate them on a computer, and show that indeed it works. And so people tried that. And there were people jumping up and down and saying, “Yes, we have proven Darwinian evolution.”

News, “Can wholly random processes produce information?” at Mind Matters News (November 16, 2021)

Robert J. Marks

Robert J. Marks: There was a problem, though, with their simulations. Number one is that all of the simulations were guided to be successful … You have the three steps of evolution: random mutation, killing off the weak, and the survival of the fittest.

The key step in those three steps is survival of the fittest. How do you determine what the survival of the fittest is? In order to do that, you have to have something called a fitness function or an objective function.

That needs to be imposed by the programmer. The programmer is telling you how the organism can better itself. That is necessary in order to perform evolution on the computer. In our book, Introduction to Evolutionary Informatics. We looked at a number of computer programs that purported to perform Darwinian evolution… based on publications in prestigious journals and conferences.

We showed that in all cases, that yes, [design] was required, and that there’s mathematics behind it. The mathematics is based on the No Free Lunch Theorem, which was popularized in the IEEE transactions on evolutionary computing in 1997. There, David Wolpert and W. G. Macready showed something which astonished the area of genetic programming and evolutionary programming.

Their conclusion — and their mathematical proof — was: If you have no idea about the direction that you’re going, you’re never going to get there. In accomplishing a goal, one search algorithm is as good on average as another one. And this astonished the computer science field, especially those in evolutionary computing. But it caught on. We took this up, and it’s covered in the Evolutionary Informatics book, for example.

We showed that, not only was this true, but we could measure the degree to which people infused information into the search process. We could measure in bits, the amount of information that a search process the programmer put into a computer program in order to get it to succeed…


Takehome: Dr. Marks: We could measure in bits the amount of information that the programmer put into a computer program to get a (random) search process to succeed.

Here are all the episodes in the series. Browse and enjoy:

  1. How information becomes everything, including life. Without the information that holds us together, we would just be dust floating around the room. As computer engineer Robert J. Marks explains, our DNA is fundamentally digital, not analog, in how it keeps us being what we are.
  2. Does creativity just mean Bigger Data? Or something else? Michael Egnor and Robert J. Marks look at claims that artificial intelligence can somehow be taught to be creative. The problem with getting AI to understand causation, as opposed to correlation, has led to many spurious correlations in data driven papers.
  3. Does Mt Rushmore contain no more information than Mt Fuji? That is, does intelligent intervention increase information? Is that intervention detectable by science methods? With 2 DVDs of the same storage capacity — one random noise and the other a film (BraveHeart, for example), how do we detect a difference?
  4. How do we know Lincoln contained more information than his bust? Life forms strive to be more of what they are. Grains of sand don’t. You need more information to strive than to just exist. Even bacteria, not intelligent in the sense we usually think of, strive. Grains of sand, the same size as bacteria, don’t. Life entails much more information.
  5. Why AI can’t really filter out “hate news.” As Robert J. Marks explains, the No Free Lunch theorem establishes that computer programs without bias are like ice cubes without cold. Marks and Egnor review worrying developments from large data harvesting algorithms — unexplainable, unknowable, and unaccountable — with underestimated risks.
  6. Can wholly random processes produce information? Can information result, without intention, from a series of accidents? Some have tried it with computers…
    Dr. Marks: We could measure in bits the amount of information that the programmer put into a computer program to get a (random) search process to succeed.
  7. How even random numbers show evidence of design Random number generators are actually pseudo-random number generators because they depend on designed algorithms. The only true randomness, Robert J. Marks explains, is quantum collapse. Claims for randomness in, say, evolution don’t withstand information theory scrutiny.

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