Biology Evolutionary biology Informatics Intelligent Design Irreducible Complexity

Applied Intelligent Design, Part 1

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This is the first of probably three posts on applied Intelligent Design. This is not an extensive list of applications of ID concepts, but I thought that giving people examples of how ID can be not only interesting and informative but actually useful in solving both biological and engineering problems.

Every science works as much from its limits as it does from its potentials. The laws of thermodynamics are actually limitations on what can be done with physics. It turns out that limitations are not science stoppers, but rather science starters, precisely because they allow fundamentally flawed ideas to be discarded at the beginning of the process, rather than after having spent lots of money researching them. No one today would think of creating a perpetual-motion machine, but we don’t look to the laws of thermodynamics as science-stoppers just because they say that such a thing is not possible. Instead, they encourage us to look to other sorts of possibilities and insights and solutions.

So, for this first post, I want to highlight a recent paper of mine which gives a proposed limit to the creation of information in evolutionary systems (for a short personal history of this paper which may aid understanding it a little better, see my personal blog entry on it). If you want to argue technical details, please see the paper itself first. However, a short, simplified summary of the argument goes like this:

  1. In order for evolution to be open-ended (i.e. work in environments which it did not have in mind beforehand) it must be on a Universal system (a system which can be programmed open-endedly)
  2. Universal systems are chaotic
  3. Chaotic systems are characterized by chaotic mappings between input configuration and results
  4. Natural selection assumes a fairly continuous mapping between input configuration and results
  5. Therefore, evolution cannot be open-ended, because navigating such a chaotic mapping would require design, and not having such a chaotic system would violate the notion of being open-ended in #1 & #2.

This indicates a fairly strict theoretical constraint on evolution. What’s more, is that it allows us to apply ID theory to biology.

One of Turing’s realizations was that, using a Universal system, you can actually implement any computational system, both Universal and non-Universal ones. Therefore, you could have something written in a Universal system, that, within a specific configuration space, acted as if it were a non-Universal system.

Therefore, if you see what looks to be open-ended evolution occurring, what you are more likely witnessing is a process driven by information – a portion of configuration-space within a Universal architecture which behaves in a non-open-ended, and thus non-Universal, fashion. Thus, knowing the limits of evolution give us something to look for. Just like if we see what appears to be a perpetual motion machine in physics, the laws of thermodynamics tells us to look for a hidden energy source. If we see, in biology, what appears to be an open-ended evolutor, we need to look for the source of information.

In my paper, I discuss why the FleQ/FleN system of the flagellum could not evolve Darwinistically. However, that does not mean that it could not evolve at all. Precisely because we know that it requires information to create such a structure, we should hope to see it evolve, precisely because that would point us to another source of information feeding the system. From a Darwinistic perspective, such an evolution can just happen through naturally-selected mutations, and thus, there isn’t much point in pinpointing a source. However, ID theory tells us that if we see something that appears to be open-ended evolution going on, that we know there must be an information source (whether within the genome or outside of it) that is playing a role.

So, that is application #1 – to be able to tell when additional information sources are feeding evolution. The next two applications of ID will not be biological at all, but rather related to software design and engineering. Many people think that ID is only about biology. I’ve pointed out the falsity of this before. As such, it can be used as a jumping-off point for a number of interesting engineering applications, which will be discussed in the next two installments.

4 Replies to “Applied Intelligent Design, Part 1

  1. 1
    Venus Mousetrap says:

    This is very interesting stuff, although I’m going to say I’m not sure if your argument with regard to natural selection follows.

    I think you’re right when we’re talking about, say, machine code. If I have a few thousand bits which make up a program, then changing a bit randomly will sometimes produce wildly unpredictable effects. But I’m not sure that just because universal systems CAN be chaotic doesn’t mean they always are. Isn’t life more robust than that?

    Take for example a virtual replicator like the von Neumann universal constructor (or perhaps the Hutton replicator, if you don’t want to be waiting all year for results 🙂 ). As you probably know they’re so fragile that a mutation in one cell will likely make them cease functioning completely. This is obviously not true of DNA (or we wouldn’t survive the mutations we’re born with), which implies that on some level, the system is not completely chaotic.

    Am I confusing myself here? 🙂

  2. 2
    johnnyb says:

    Venus –

    Very good thoughts. The issue is for _open-ended evolution_. It is true that the entire search space is not chaotic. However, in order to get open-ended evolution , it MUST traverse the parts that are chaotic. If it didn’t, it could be implemented with a non-universal computer, and therefore, it would not be open-ended. It might be powerful, but it would only be powerful along the lines for which the system was already built.

    So, for non-novel systems (i.e. parameterized evolution), yes, they don’t need to navigate chaotic search spaces. But, to get open-ended evolution, it requires such navigation.

    The cell can also have parts which limit the effects of catastrophic error. However, those same systems would also limit truly novel developments.

    As the paper pointed out, it’s not that such evolutions can’t happen at all, it’s just that if they do happen, it means that there was an information source guiding the change – either externally or through a parameterized space.

  3. 3
    Venus Mousetrap says:

    I think evolution does, perhaps, exhibit what could be considered non-universality. For example, since the appearance of the hox genes, a lot of evolution has been simply modifying those genes to arrive at new bodyplans – a vague kind of parameterised evolution. I envision that as acting rather like a stable track through otherwise chaotic regions of the sequence space.

    Of course, this is all rather speculative, since the structure of sequence space is unknown (plus the fact that it changes shape continuously and in response to things travelling through it makes it difficult to analyse).

    An interesting experiment might be to take a model organism like a cellular automaton and mutate one bit of it at a time, to generate a fitness space.

  4. 4
    johnnyb says:

    Yes, precisely! However, remember that Hox genes only control gross morphology. For other things to evolve, they would need their own parameterization.

    As to your experiment, similar things have been done. An experiment showed that as the length of a program grows, the space that holds functional programs tends towards 0. Stephen Wolfram has done several characterizations of automatons which were very interesting, and are referenced in my paper.

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