SETI needs Intelligent Design

As Dr. Gonzales' and Dr. Richards' show in the book "Privileged Planet" a SETI project with materialistic metaphysics does not have a hope in heaven to expect to find a habitable planet.  The improbabilities involved in the formation of habitable planet in the universe are extremely small, much smaller than the probabilistic resources available in our universe.

Fortunately, the fact we live on a habitable planet within our universe makes the possibility of a trans-universal designer extremely strong.  At least it makes such a possibility the much preferable explanation to a process that works through merely chance and necessity.  If an intelligent designer created our planet, despite the enormous probabilistic barriers to doing so, then this makes the possibility of other habitable planets a live possibility.

This possibility gives SETI a way out of the probabilistic hole they dug for themselves with materialism.  It is only if SETI allows for the possibility of intelligent design that they can justify further searches for other habited planets in the universe.

That is not all.  The very interesting result from "Privileged Planet" is more than the fact our planet is very finely tuned for highly complex living beings.  Additionally, our planet has been uniquely placed and constructed to make the discovery of the universe a tractable task.  Furthermore, the extremely amazing thing is that the finely tuned parameters for life are the same parameters for discovery.  This requires an even higher level of design than if these parameters were independent.

However, this third aspect is not explained by either the function of survival or discovery.  Also, it is both not necessitated by the situation while at the same time exhibiting a highly intelligent design decision.  Since design decisions are made for a reason, we need to identify a third reason for this third feature of our finely tuned abode.

So, what does the convergence between survival and discovery entail?  It entails that wherever there are  habitable planets in the world, they will share a common frame of conceptual reference.  What purpose would a common set of concepts serve?  On the Pioneer space mission, a disc was placed on the craft that attempted to communicate aspects of our world to extraterrestrial beings, and part of this communication made use of concepts that should be universal, such as mathematical concepts.  Or another example, in CS Lewis' "Out of the Silent Planet" the protagonist at one point attempts to communicate with an inhabitant of Mars by making use of common concepts the two share.

With these considerations in mind, one possible explanation for the convergence between survival and discovery is that it provides a means for disparate inhabitants of the universe to understand each other.  Why provide a means of understanding?  Perhaps because the inhabitants are meant to discover each other...

Method for Making New Technology from ID

http://appliedintelligentdesign.blogspot.com/2012/07/looking-for-human-engineering-concepts.html

In a number of arguments for ID, such as Dr. Meyer, Dr. Dembski and Dr. Behe, the writers argue that there appears to be intelligent design in nature because natural entities resemble human engineered products, and human engineered products are intelligently designed.

If we look at this relationship formally, then it looks like biological/natural entity -> human engineered object -> intelligent design.  However, what if we reverse the relationship so it looks like intelligent design -> human engineered artifact -> natural entity?  This means if intelligent design theory is true, then perhaps we can use human engineering to predict the kinds of functionality we will find in the natural world.

For instance, consider a city.  To make a functional city, a wide variety of important technologies are required: communication, transportation, plumbing, power plant, fuel, waste disposal, construction, health, etc.

Where might such a system reside within the biological world?  Perhaps the human body?  A human body is composed similarly to a city, and accomplishes a similar function, providing for its own wellbeing and maintenance.  We can look at the body and then look for the components we'd expect in a city.

"But, how does this give us new forms of technology?" you may ask.  Well, for one thing we can look at how the same functionality is implemented in the body and then attempt to reverse engineer it to improve our existing technology.  There is currently a technology company doing exactly this by reverse engineering the motor in the bacterial flagellum.  Our body contains much, much more than new kinds of motors, however.  It has instantaneous communication systems, extremely effective repair and construction systems, and is amazingly effectively at extracting and utilizing energy from food.

That is not all.  Furthermore, we can learn of new kinds of technology.  While our body shares similar systems with cities, it also has systems and capabilities we have not thought of before that equally apply to a city.  And this is where the real promise lies in the technique of learning from nature.

Here are a couple examples to get things started.
- While our cities today have a very limited utility system, the body not only distributes power and water, but the body also has a system of very decentralized manufacturing.  Today, we are rapidly nearing the point where people can manufacture objects within their homes.  The innovation within the body is there is also a resource utility system, such that the basic resources for manufacturing are distributed throughout the body.  The same could be done within cities.
- All the systems in the body are autonomously run and optimized by a central processing unit, to which our cities have no existing analog, but would be very useful.
- The body is maintained by what amount to robots.  While manning our cities with robots is not possible yet, the body presents a example on how it can be done.
- The body is able to turn its fuel waste into a form that can be recycled right back into fuel again.

It has been noted by a number of scientists that biological organisms appear to be phenomenally optimized for their particular function.  The technology in nature far exceeds any technology we have ever been able to create.  If we can perfect our ability to reverse engineer natural systems, our modern technology will grow by incredible leaps and bounds, since we can see from nature that we are only beginning to touch what is technologically possible.  There is an enormous wealth of technological innovation that is ours for the taking, to which we have been blinded ever since the industrial revolution by Darwinism and methodological naturalism.

However, with the introduction of Intelligent Design, our blinders have been removed.  Forget mining for gold and diamonds.  Forget pumping oil.  We have vast untapped quantities of the most valuable resource in our universe: CSI.

Still feeling skeptical?  Well, ask yourself what the greatest technological innovation has been of the past century that has revolutionized our entire world.  It is information technology.  But where has information technology existed since the beginning of life?  Why, within the very DNA and protein production that make up all organism.  Think how much sooner we could have invented computers if we'd only known where to look.

What untold other technologies are lying out in the natural world just waiting for us to discover them?  It is time to look for Intelligent Design!

ID Implies the Supernatural

Here is a first order predicate logic proof which shows ID implies a supernatural causal agent.  The agent is properly called "supernatural" because it possess an ability that is above nature.

Legend

------

V x p : universal quantification - for all x proposition p holds

~p : not p

p1 ^ p2 : conjunction

p1 v p2 : disjunction

p1 -> p2 : implication



The following is how new universal propositions are introduced using temporary variables.

The | indicates that the corresponding line is part of a subproof.

The numbers on the right indicate which prior lines, and laws/identities, are used to generate the current line. 

1. | x0 ^ y0                                        x0, y0

   --

2. | x0                                             1

3. V x, y ( x ^ y -> x )                            1-2



Proof

-----

P(x): x is an entity that is entirely controlled by physical laws

C&N(x):  x is an entity that operates by events entirely describable by chance and necessity

C&NO(x): x is an entity whose origin can be explained by proximate chance and necessity causes

CSI(x): x contains CSI

C(x, y): x is the proximate cause of y



Goal: V x, y ( C(x, y) ^ CSI(y) -> ~P(x) )



1.  V x ( P(x) -> C&N(x) )

2.  V x ( CSI(x) -> ~C&NO(x) )

3.  V x, y ( C&N(x) ^ C(x, y) -> C&NO(y) )



4.  | C&N(x0) ^ C(x0, y0) ^ CSI(y0)                 x0, y0

    --

5.  | CSI(y0)                                       4

6.  | ~C&NO(y0)                                     2, 5

7.  | C&NO(y0)                                      3, 4

8.  | _|_                                           6, 7



9. V x, y ( ~(C&N(x) ^ C(x, y) ^ CSI(y)) )          4-8

10. V x, y ( ~C&N(x) v ~C(x, y) v ~CSI(y) )         9 & De Morgan's Law



11. | C(x0, y0) ^ CSI(y0)                           x0, y0

    --

12. | ~C&N(x0)                                      10, 11

13. | ~P(x0)                                        1 & Modus Tollens, 12



14. V x, y ( C(x, y) ^ CSI(y) -> ~P(x) )     11-13

UPDATE:

Elsewhere, an author claims this argument shows ID is committed to substance dualism.  

http://www.jackscanlan.com/2011/08/homologous-legs-now-has-a-facebook-page-its-2011-right/

While I agree substance dualism is the easiest way to make sense of this argument, it is still not a necessary conclusion.  For example, Mormon theology maintains there is a way for matter to be intelligent and possess free will.  Such a claim is not logically incoherent (as far as I know), so here we have a materialistic theory of intelligence that is compatible with my argument above.

However, a materialistic theory of intelligence would still be supernatural, since intelligent matter is beyond the physical laws of chance and necessity.

Subjective specification makes CSI non-functional

It has been claimed a number of times that the specification in complex specified information (CSI) is subjective, at least to some degree.  The claim is that even though it is possible to quantify specification, to some degree, it is still at some level dependent upon a human domain of discourse for its description.

However, if it is true that specification is always subjective this presents a problem.  To understand why, we must examine the problem CSI is attempting to solve.

In bygone days, creationists used to argue that the universe must have been designed because many parameters are so finely tuned, and the combination of so many independent finely tuned parameters is vastly improbable.  While intuitively this seems like a knock down drag out argument, there is a logical fallacy at work.

Take a jar of multicolor marbles.  It happens to be configured in such a way that the marbles spell out the word "Supercalifragilisticexpialidocious" around the edge of the jar.  However, mathematically speaking, this particular configuration, while very improbable, is just as probable as any other configuration of marbles in the jar.  Yet, it is a necessity that one of these improbable configurations is instantiated in the jar, regardless of whether through material or intelligent causation.  As such, the mere fact that the configuration is improbable says nothing about the causal agency that brought it about.

CSI gets around this problem by placing a non-uniform probability distribution on sets of marble configurations.  So, while the particular configurations are equally probable in themselves, the probability of a configuration coming from a particular set varies.  Thus, with a the right choice of  specification, it is now possible to exclude either a material or intelligent causal agent as being responsible for the marble configuration.

But, how do we choose the correct specification?  The problem is that there are many possible specifications for the marble configurations.  In fact, there is a specification for each possible probability distribution.  The information conferred by picking one of these specifications must be averaged out over all possible choices of specifications.  Unfortunately, this brings us right back to square one, and each marble configuration again regains an equal, though very low, probability, when averaged over all choices of specifications.

This is where the problem with a subjective specification comes into play.

We might say that the selection of specification is up to the group of scientists detecting intelligent design, so even though syntactically speaking one specification is as preferable as any other, there is an external mapping of value to each specification (i.e. semantics) held by the scientists that makes one specification more valuable than another.  Furthermore, this mapping is held by the vast majority of people, and they all agree the mapping is objective.

Unfortunately, while this may well be true, such a mapping begs the question if it meant to support a scientific claim, since the mapping is no longer a strictly scientific claim.  Science, at least of the hard science variety, decides matters of qualification using quantification.  It proposes a variety of models to fit observed data, and uses model fitting (i.e. linear regression) to determine which model is best.  In this way, it is possible to make objectively true statements about the physical world, which is at the level of mathematical veracity, given the premises are true.

However, in the case of CSI, the choice of specification is what determines the answer to whether a particular object is designed.  Two choices of specification can give two completely different answers. Thus, if the choice of specification is determined by some factor completely external to the marble configurations under consideration, then this may be equivalent to fitting the data to the model, since the specification chosen is part of the data being measured.  Fitting the data to the model does not count as science.

As a result, even though it is not necessarily the case that an externally determined specification is fitting the data to the model, it remains a live possibility.  As long as there is no objective way to eliminate this possibility, then by the principle of maximum entropy both the possibility of fitting the data to the model and fitting the model to the data must be given equal weighting.  If both possibilities are given equal weighting then ultimately the CSI metric cannot give a positive reading, inherently cannot discriminate between design and non-design, and therefore does not count as a scientific claim.

The only way the CSI metric can count as science is if there is an objective way to choose a specification.

Capitalism Needs Intelligent Design

Let us say that economic models fall along a spectrum from a totally centralized to a totally decentralized economies.  The question is, where on this spectrum do we see the greatest source of wealth for human prosperity?  Well, this question is answered in turn by a prior question of whether wealth is of a bounded quantity, or unbounded quantity.

If wealth is bounded, and there is only a finite amount of wealth to go around in this world, then the haves are always taking from the have nots.  This is a great injustice, and the only just economy that provides prosperity for the most people, even though it is quite limited, is a centrally planned economy that shares out the wealth equally amongst all.

However, suppose wealth is unbounded.  Suppose new wealth can be created at any given time to improve the lot of man.  Then, a more decentralized economic model is more just than a centralized model because the decentralized model produces more wealth and benefits a greater number of people. In fact, a centralized model in this case becomes inherently unjust because it is artificially and needlessly restricting how much wealth can benefit mankind, and thus leading to greater poverty and misery.

What is the nature of wealth, bounded or unbounded?  Within the modern paradigm of materialism, the answer must be bounded.  Matter abides by strict conservation laws, and while resources may get shuffled around, there is no such concept of "creation."  As such, within a materialistic worldview, the most just economy is a centralized economy.  Therefore, capitalism is unjustified within a materialistic worldview.

On the other hand, if we adopt a worldview that includes intelligent design, then creation becomes a live option.  We gain the metaphysical possibility of wealth generation.  How so?  According to ID, intelligent agents are defined by their ability to originate information, not merely pass it from one location to another.  Consequently, it is only within an ID friendly worldview that capitalism gains the necessary metaphysical properties to make sense of an decentralized economic model based on wealth creation.

Must the designer be more complex than the design?

One of Dr. Richard Dawkins' favorite arguments against Intelligent Design's coherence is that ID does not explain complexity because the designer must be even more complex than the design.

Why does Dawkins say this?  For instance, he believes great complexity comes from very simple origins through the process of Darwinistic evolution.  But, for some reason introducing a designer implies greater preceding complexity.

While I am not sure why Dawkins makes this claim, I can address a reason why he may, and the problem with this reason.

First, he may be thinking of the designer as some complex physical entity, such as a factory.  In this case it is quite obvious that to generate even a seemingly simple object such as a pencil we need an enormously complicated number of processes and mechanisms.  So, it is quite easy for me to accept that if the designer were like a factory, then it in turn would require even more explanation than the pencil.  In which case, intelligent design theory would not be very helpful.

However, intelligent design theory does not say the designer is like a factory.  In fact, it precludes the designer from being like a factory.  To see this, we must examine the core concept of ID, which is complex, specified information.

Complex, specified information (CSI) is a mathematical quantification of an entity.  The two criteria for an entity to possess CSI is that it must be highly unlikely (complex) given the environment in which it came to exist, while also precisely and concisely described by a specification that is independent from its environment.

For a causal agent to be the intelligent designer responsible for the CSI in the entity, the entity must abide by the two criteria in the context of being generated by a particular agent.  Take the pencil factory as an example, since pencils are quite evidently designed, are relatively complex and can be described quite simply as an erasing and writing instrument.  Can we say the pencil factory is the designer of the pencil?

Well, let's look at the criteria for CSI.  Would we consider it highly unlikely for a pencil factory to generate pencils?  Probably not, unless it is a particularly bad pencil factory.  Next, do we consider the pencil's description to be independent from the factory?  In other words, does the pencil factory produce something that is better described as totally unlike a pencil?  Again, probably not, unless it is a particularly bad pencil factory.  As such, the pencil factory cannot be said to be the designer of the pencil.

In this way we see that if the supposed intelligent designer is to a designed entity like a pencil factory is to a pencil, then ID states the supposed intelligent designer is not the real designer.  Rather than disagreeing with Dawkins, ID actually agrees and says the designer cannot be like a pencil factory in relation to its design, ever growing in complexity.

Instead, the designer must be quite independent from its design.  This means that a design implies nothing about the complexity of the designer.  While it may well be the case that the designer is more complex, this is not necessitated by ID and the designer may be much, much simpler than the design.

In fact, the foregoing argument logically entails that there is more to intelligent design than just complex specified information:
http://appliedintelligentdesign.blogspot.com/2012/07/intelligent-design-goes-beyond.html

Background, experiment and results of CSI Collecting (CSIC)

The essential idea of CSI Collecting is to incorporate human pattern detection to improve the capabilities of search and optimization algorithm.

The question is, do humans have the ability to detect patterns any better than computers?  If not, then any advantage human interaction brings is equivalent to some computer algorithm.  Hence, there is nothing especially unique about human involvement, and there is no guarantee it will bring an advantage to a particular problem.

On the other hand, if humans do have a pattern recognition capability that is non-computational then we can expect human involvement to bring an advantage to all problems where an advantage is possible.  There are problems where there is no other way to solve the problem than by trying all combinations, and in such problems human interaction will bring no advantage whether such interaction is non-computational or not.

Why would we think a non-computational ability exists in humans?  This question is a bit more involved to answer.  The answer is a hypothesis, and is based on a couple assumptions which are potentially testable.

The starting point is Dr. Dembski's paper "A search for a search".  This paper states two important points: 1) a search process cannot produce more information than is originally placed in the search algorithm, and 2) a search for search also cannot produce more information than is place in the initial search algorithm.  The term information in these papers refers to a metric of how much more likely a search algorithm will find a search target than a purely random sample based search.

According to these two points, as long as the only means we have of inserting information into a search process is another search process, then we can never insert information into a search process.  This means that for all problem domains any search will perform no better than a random sample search.  The only way to get information into a search process is by a non-search.  However, all algorithms that are capable of inserting information can be characterized as searches.  Thus, the source of information must ultimately be non-algorithmic.  Since all computers are algorithmic, this means that the source of information must also be non-computational.

The one known source of non-algorithmic information is intelligence.  According to intelligent design, intelligence can create information, in particular, complex specified information.  However, is complex specified information the same kind of information that a search process requires?

The mathematical definition of complex specified information is approximately the amount of specificational resources multiplied by the number of specifications we are interested in divided by the number of possible specifications.  This characterization can be fit to the search process.  The range of potential solutions that a search will examine is equivalent to the number of possible specifications.  The target set of solutions is equivalent to the specifications we are interested in.  The specificational resources are the number of solutions sampled by the search process.  If the search process selects the target specifications more often than we would expect given their proportion to the number of potential specifications, then when we calculate the CSI formula on the search process, it will contain information.

Now if we invert the argument that CSI implies intelligence, then we can say intelligence can potentially, but not necessarily, impart information into a search process.  As we saw when comparing the definition of CSI to information in a search process, if information is imparted into a search process, it will find its target more often than without the information.  So, if an intelligent being, such as a person, is involved in a search process, then the intelligent being can cause any given search algorithm to perform better than mathematically possible.

This is the theoretical basis behind the CSI Collecting (CSIC) method.  Since humans have some sort of ability to insert information into any search algorithm, then there must be a general methodology for allowing humans to interact with search algorithms.  Does such a methodology exist in modern computer science?  Currently, there are a number of researchers are attempting to incorporate human interaction into search processes, the most well known being the Google search engine, which uses our search patterns and web page linking to improve our searches results.  However, none of these methods attempt to establish a generalized approach.  The general field is known as human computation, and there is currently no theoretical foundation for the field that is compatible with intelligent design's dual claims that algorithms cannot create information and that intelligent agents can.

Now, you may be asking, given that CSIC seems to be a unique approach to human computation, how do I plan to test my hypothesis, and what are my results?  First, I must admit there are practical problems to testing the efficacy of human computation.  The most glaring problem is distinguishing between A) a general non-algorithmic ability to improve a search algorithm and B) happenstance that an algorithmic ability improves a search algorithm.  In theory the two cases are quite distinct: there will always be instances of search algorithms where A improves the search and B does not, for any type of algorithmic ability in B.  In practice it is not possible to test an ability over all possible problems, we can only test a very small subset of all problems.  However, the good thing is that there are many finite problem subsets that have approximately the same characteristic as the set of all problems.  So, if I pick such a subset, while I cannot categorically state that the tested ability falls in A instead of B, I can make such a claim with a strong degree of confidence.

Which subset of problems have the necessary characteristic?  It is the subset of problems that the No Free Lunch Theorem (NFLT) applies, or almost applies (ANFLT).  Unfortunately, the set of NFLT problems is not very large.  Fortunately, the nest of ANFLT problems is very large.  In fact, most problems of interest quite likely fall into this set because they are NP complete or harder.  So, as long as I pick a problem that is ANFLT, I can at least give a confidence rating to my hypothesis, as well as potentially generate useful results.

The second practical issue is determining whether humans categorically contributed to the search process, or I just picked a bad search algorithm.  This case too I cannot say definitively whether my algorithm is to blame or not.  The best I can do is give a degree of confidence.  And in my case, I cannot even mathematically quantify this confidence since my current work is merely a first pass to see if the idea shows promise.

The general technique I use is as follows.  I use a standard multi-objective genetic algorithm.  A genetic algorithm takes a set of solutions, measures how good each solution is according to some fitness valuation function, varies the solutions to generate a new set using variation operators such as mutation and crossover, and then from both sets of solutions selects a final set according to some critera.  The algorithm then reiterates this process on each subsequent final set until a stopping criteria is reached.  The solutions themselves are represented to the algorithm as fixed length bit strings.  The one innovation I add to create CSIC is to allow a person to provide input for the selection phase.  The person can only see the bit string solution and its fitness valuation.

The metric of comparison between the human and the genetic algorithm is the number of unique solution valuations needed to improve on the best found solution to date.  The search (algorithmic or human manual) process requiring fewer unique solution valuations to find a better solution is considered the superior search process.

My first problem domain consisted of scheduling member roles for multiple club meetings.  This is a form of the well known scheduling problem, and as such is harder than NPC.  My method was to run the genetic algorithm until it stopped finding better solutions for a large number of iterations.  Then I manually attempted to find better solutions.  In about 0.05% of the fitness valuations the algorithmic search used and was still unable to find better solutions, I was able to find three superior solutions.

My second problem domain of choice is that of coming up with the primes that generate an RSA public private key pair.  This domain is much harder than NPC, and as such is quite likely an ANFLT domain.  I ran the algorithmic search algorithm in tandem with 500 attempts by humans using the Amazon Mechanical Turk service.  The humans contributed 2.4% of the overall set of superior solutions.

These results are still preliminary, and there is much hard mathematical work to be done to quantify specifically the degree to which humans contributed, and whether this contribution is statistically significant enough to validate the ID hypothesis.  However, at the very least, it is clear that humans can contribute to algorithmic optimization when given only the exact same data available to the algorithm.  So, the initial results show promise, however so slight.