Intelligent Design Detection

  1. Design is order imposed on parts of a system. The system is designed even if the order created is minimal (e.g. smearing paint on cave walls) and even if it contains random subsystems. ‘Design’ is inferred only for those parts of the system that reveal the order imposed by the designer. For cave art, we can analyze the paint, the shape of the paint smear, the shape of the wall, composition of the wall, etc. Each one of these separate analyses may result in separate ‘designed’ or ‘not designed’ conclusions. The ‘design’-detection algorithm shown in the attached diagram can be employed to analyze any system desired.
  2. How do we know something is not random? By rejecting the null hypothesis: “the order we see is just an artifact of randomness”. This method is well established and common in many fields of research (first decision block in diagram). If we search for extraterrestrial life, archeological artefacts, geologic events, organic traces, etc., we infer presence based on specific nonrandom patterns. Typical threshold (p-value) is 0.05 meaning “the outcome observed may be due to randomness with a 5% or less probability”. The actual threshold is not critical, as probabilities quickly get extreme. For instance, given a 10-bit outcome (10 coin toss set), the probability of that outcome being random yet matching a predetermined sequence is 0.1%, well below the 5% threshold. A quick glance at biological systems show extreme precision repeated over and over again and indicating essentially zero probability of system-level randomness. Kidneys and all other organs are not random, reproduction is not random, cell structure is not random, behavior is not random, etc.
  3. Is a nonrandom feature caused by design or by necessity? Once randomness has been excluded, the system analyzed must be either designed as in “created by an intelligent being”, or a product of necessity as in “dictated by the physical/scientific laws”. Currently (second decision block in diagram), a design inference is made when potential human/animal designers can be identified, and a ‘necessity’ inference is made in all other cases, even when there is no known necessity mechanism (no scientific laws responsible). This design detection method is circumstantial hence flawed, and may be improved only if a clearer distinction between design and necessity is possible. For instance, the DNA-to-Protein algorithm can be written into software that all would recognize as designed when presented under any other form than having been observed in a cell. But when revealed that this code has been discovered in a cell, dogmatic allegiances kick in and those so inclined start claiming that this code is not designed despite not being able to identify any alternative ‘necessity’ scenario.
  4. Design is just a set of ‘laws’, making the design-vs-necessity distinction impossible. Any design is defined by a set of rules (‘laws’) that the creator imposes on the creation. This is true for termite mounds, beaver dams, beehives, and human-anything from pencils to operating systems. Product specifications describe the rules the product must follow to be acceptable to customers, software is a set of behavior rules obeyed, and art is the sum of rules by which we can identify the artist, or at least the master’s style. When we reverse-engineer a product, we try to determine its rules – the same way we reverse-engineer nature to understand the scientific laws. And when new observations infirm the old product laws, we re-write them the same way we re-write the scientific laws when appropriate (e.g. Newton’s laws scope change). Design rules have the same exact properties as scientific laws with the arbitrary distinction that they are expected to be limited in space and time, whereas scientific laws are expected to be universal. For instance, to the laboratory animals, the human designed rules of the laboratory are no different than the scientific laws they experience. Being confined to their environment, they cannot verify the universality of the scientific laws, and neither can we since we are also confined in space and time for the foreseeable future.
  5. Necessity is Design to the best of our knowledge. We have seen how design creates necessity (a set of ‘laws’). We have never confirmed necessity without a designer. We have seen that the design-necessity distinction is currently arbitrarily based on the identification of a designer of a particular design and on the expectation of universality of the scientific laws (necessity). Finally, we can see that natural designs cannot be explained by the sum of the scientific laws these designs obey. This is true for cosmology (galaxies/stars/planets), to geology (sand dunes/mountains/continents), weather (clouds/climate/hydrology), biology (molecules/cells/tissues/organisms), and any other natural design out there.
  6. Scientific laws are unknowable. Only instances of these laws are known with any certainty. Mathematics is necessary but insufficient to determine the laws of physics and furthermore the laws of chemistry, biology, behavior, etc., meaning each of the narrower scientific laws has to be backwards compatible with the broader laws but does not derive from the more general laws. Aside from mathematics that do not depend on observations of nature, the ‘eternal’ and ‘universal’ attributes attached to the scientific laws are justified only as simplifying working assumptions, yet too often these are incorrectly taken as indisputable truths. Any confirming observation of a scientific law is nothing more than another instance that reinforces our mental model. But we will never know the actual laws, no matter how many observations we make. Conversely, a single contrary observation is enough to invalidate (or at least shake up) our model as happened historically with many of the scientific laws hypothesized.
  7. “One Designer” hypothesis is much more parsimonious compared to a sum of disparate and many unknown laws, particles, and “random” events. Since the only confirmed source of regularity (aka rules or laws) in nature is intelligence, it takes a much greater leap of faith to declare design a product of a zoo of laws, particles, and random events than of intelligence. Furthermore, since laws and particles are presumably ‘eternal’ and ‘universal’, randomness would be the only differentiator of designs. But “design by randomness” explanation is utterly inadequate especially in biology where randomness has not shown a capacity to generate design-like features in experiment after experiment. The non-random (how is it possible?) phantasm called “natural selection” fares no better as “natural selection” is not a necessity and in any case would not be a differentiator. Furthermore, complex machines such as the circulatory, digestive, etc. system in many organisms cannot be found in the nonliving with one exception: those designed by humans. So-called “convergent evolution”, the design similarity of supposedly unrelated organisms also confirms the ‘common design’ hypothesis.
  8. How does this proposed Intelligent Design Detection Method improve Dembski’s Explanatory Filter? The proposed filter is simpler, uncontroversial with the likely [important] exception of equating necessity with design, and is not dependent on vague concepts like “complexity”, “specification”, and “contingency”. Attempts to quantify “specified complexity” by estimating ”functional information” help clarify Dembski’s Explanatory Filter, but still fall short because design needs not implement a function (e.g. art) while ‘the function’ is arbitrary as are the ‘target space’, ‘search space’, and ‘threshold’. Furthermore, ID opponents can easily counter the functional information argument with the claim that the ‘functional islands’ are linked by yet unknown, uncreated, eternal and universal scientific laws so that “evolution” jumps from island to island effectively reducing the search space from a ‘vast ocean’ to a manageable size.

 Summary

  • Design is order imposed on parts of a system
  • A system is nonrandom if we reject the null hypothesis: “the order we see is just an artifact of randomness”
  • Current design detection method based on identifying the designer is circumstantial hence flawed
  • Design is just a set of ‘laws’, making the design-vs-necessity distinction impossible
  • Necessity is Design to the best of our knowledge
  • Scientific laws are unknowable. Only instances of these laws are known with any certainty
  • “One Designer” hypothesis is much more parsimonious compared to a sum of disparate and many unknown laws, particles, and “random” events
  • This Intelligent Design Detection Method improves on Dembski’s Explanatory Filter

Pro-Con Notes

Con: Everything is explained by the Big Bang singularity, therefore we don’t need Intelligent Design.

Pro: How can a point of disruption where all our knowledge completely breaks down explain anything? To the best of our knowledge, Intelligent Design is responsible for that singularity and more.

0

514 thoughts on “Intelligent Design Detection

  1. Nonlin.org: This is wrong:
    “You were invoking statistical testing to distinguish intentional patterns from randomly generated stuff, right? ”

    Wow, that is some powerful necromancing. I had to follow our conversation back to see what we were discussing a month ago. It appears to be paragraph 2 of your OP.

    I am sorry, but my quote seems a pretty accurate description. If this is incorrect, than you need to explain to me what your were trying to say in that paragraph.

    0
  2. Rumraket: Nonlin.org: We generally do not design and build by “assembling the atoms”.

    How do soap bubbles form? Is an invisible magic conjurerer somehow pushing the soap molecules around?

    The “questions” are dumb and don’t follow the statement.

    0
  3. Rumraket: Well if you can just sit there and claim that, I can claim it’s negation. These physical-chemical reasons are NOT the product of design to the best of our knowledge.

    What now, where do we go from here?

    …childishly cutting out the explanation:
    “This is what’s shown in this OP if one reads for comprehension.”

    And yours?

    0
  4. Corneel: Nonlin.org: This is wrong:
    “You were invoking statistical testing to distinguish intentional patterns from randomly generated stuff, right? ”

    Wow, that is some powerful necromancing. I had to follow our conversation back to see what we were discussing a month ago. It appears to be paragraph 2 of your OP.

    I am sorry, but my quote seems a pretty accurate description. If this is incorrect, than you need to explain to me what your were trying to say in that paragraph.

    Read again paragraph 2, this time for comprehension. Pay attention; it’s real simple. Hint: it starts with “How do we know something is not random? “

    0
  5. Nonlin.org: Read again paragraph 2, this time for comprehension. Pay attention; it’s real simple. Hint: it starts with “How do we know something is not random? ”

    I am sorry, but my quote seems a pretty accurate description. If this is incorrect, than you need to explain to me what your were trying to say in that paragraph.

    Isn’t this fun?

    0
  6. We covered this in the first two pages of comments on this thread.
    We explained the Schoolboy Howler contained in your para 2.
    You failed to understand then.
    Have you learnt the difference between P(theory|data) and P(data|theory) in the interim?

    0
  7. Corneel: I am sorry, but my quote seems a pretty accurate description. If this is incorrect, than you need to explain to me what your were trying to say in that paragraph.

    If I tell you you’re wrong, then you’re wrong. I should know what I wrote. Sorry, if you cannot process something as simple as that, I can’t help you. But I suspect you’re not willing rather than not capable.

    0
  8. DNA_Jock: We covered this in the first two pages of comments on this thread.

    Last I checked, your objections have been proven wrong – read the thread. If you insist on not understanding something as simple as this, sorry but you’re beyond help.

    If you think this OP is wrong, state(restate) your objection and let’s move on.

    0
  9. Thank you, Nonlin.org, for such an inventive use of the phrase “proven wrong”.

    Corneel and I laid out our objections a couple of times each and, judging by your responses, you failed to understand simple math. My best explanation is that you were unwilling to admit that the notation P(A|B) was beyond you.

    My objection

    Your first sentence is strangely worded, but accurate. The metric here is P(result|null), that is, the probability of getting a result this weird (or weirder), if there is no real difference, just random sampling. Your second sentence is a highly context-dependent assertion. Your third sentence is completely and utterly wrong, because you have switched to talking about P(null|result), that is the probability that the outcome is the result of “randomness’ given the observed result. This is a completely different thing.
    And the difference is what Bayes Law is all about.
    Hint: your third sentence should read “Given a fair coin fairly tossed, the probability of the outcome is ~0.1%”, not “the probability of that outcome being random”. You are assigning a probability to the (random) cause; you don’t have enough information to do that.
    Learn. High. School. Math.
    I have developed a diagnostic test that is 99% accurate, specifically:
    If you have the disease, then P(+) = 0.99, P(-) = 0.01.
    If you don’t have the disease, then P(+) = 0.01, P(-) = 0.99
    Your doctor administers this test to you. You get a positive result. What is the probability that you have the disease?
    Answer: you don’t know.
    You know P(+|D), but you want to know P(D|+).
    You need more information…
    P.S. Your entire OP is gibberish, but this mistake is the first one we need to fix…

    Your response

    This should work:
    “Typical threshold (p-value) is 0.05 meaning “if the outcome were due to randomness (null), it would only be observed in 5% or less of trials”. To reject the “randomness” hypothesis, the actual threshold is not critical, as probabilities get extreme quickly. For instance, given a 10 coin toss set, the probability of that set matching a predetermined sequence given a fair coin is 0.1%, well below the 5% threshold.

    If you think that this re-wording fixes your problem with detecting that something is not random, then you have failed to understand the objection.
    Do you understand the example with the diagnostic test?
    What additional information do you need before you can answer the patient’s question?

    0
  10. Nonlin.org: If I tell you you’re wrong, then you’re wrong. I should know what I wrote. Sorry, if you cannot process something as simple as that, I can’t help you.

    As you wish. Then I don’t understand what you are trying to say.

    Nonlin.org: But I suspect you’re not willing rather than not capable.

    You don’t suppose your persistent refusal to clarify has anything to do with it?

    0
  11. DNA_Jock: If you think that this re-wording fixes your problem with detecting that something is not random, then you have failed to understand the objection.

    I give you a number of examples, including the one you cite, and instead of commenting on those, you chose to bring your own irrelevant one. But we are not discussing the WELL KNOWN but IRRELEVANT disease example. We are rejecting the null “random”.

    I am not inventing the wheel here (paragraph 2), just using an existing “wheel” that everyone knows and accepts. If you disagree, show how you would reject the null “random” and how your method is different than mine.

    0
  12. Corneel: As you wish. Then I don’t understand what you are trying to say.

    Maybe you are honest. Let’s try again. This is wrong regarding paragraph 2:

    “You were invoking statistical testing to distinguish intentional patterns from randomly generated stuff, right? ”

    Paragraph 2 distinguishes “randomly generated stuff” from EVERYTHING ELSE, not just “intentional patterns”. Big difference.

    IOW, you look at something and ask yourself: “could this be the way it is due to randomness?” You will then have to reject the null if you conclude: “the probability of this feature being the way it is due to randomness is exceedingly small (i.e. less than threshold)”

    0

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.