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Journal of Creation  Volume 28Issue 2 Cover

Journal of Creation 28(2):6–8
August 2014

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In the Beginning was Information


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Organized complexity—how atheistic assumptions hinder science

Photograph by Trevor Murray

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One of evolution’s outstanding problems is the origin of information. How can it be that biological systems which can express apparent purpose (in teleological terms) have arisen through completely natural processes? Heedless to the consequences to their own arguments, evolutionists have long argued that purpose is an illusion. The line of argument is simple:

  1. Order is mistaken for purpose.
  2. Order is a result of natural processes.
  3. Hence what appears to be purpose is actually a result of natural processes.

The latest turn at making this argument falls to complexity theory, on the basis of which Melanie Mitchell argues:

“Most biologists, heritors of the Darwinian tradition, suppose that the order of ontogeny is due to the grinding away of a molecular Rube Goldberg machine, slapped together piece by piece by evolution. I present a countering thesis: most of the beautiful order seen in ontogeny is spontaneous, a natural expression of the stunning self-organization that abounds in very complex regulatory networks. We appear to have been profoundly wrong. Order, vast and generative, arises naturally.”1

Again, however, this argument is taken forward heedless of the results of its actual outcome. What is the actual outcome of the argument from complexity theory? First, equating complexity with purpose defeats itself in demoting the thinking required to reach the conclusion offered from purposeful thought to simply ordered thought without meaning. Second, equating complexity with purpose closes off any hope of explaining and understanding ordered, or designed, complexity. It is this second result this article examines in some detail.

Ordered complexity

Statistics have come a long way in the area of unordered complexity.

Complexity is, as complexity theorists would like to say (in an ironic turn of phrase), an emergent field of study. From corporate financials, to the stock market, to social networking, complexity is on the cutting edge of current research—and with good reason. In each of these areas, researchers and engineers are discovering and rediscovering many of the same principles and ideas, finally bumping up against one another’s writing and finding parallel strains across fields as diverse as computer networking and biology.

Standing across the path in all these fields is a single obstacle: ordered complexity. As Weaver explained the problem in 1948:

“This new method of dealing with disorganized complexity, so powerful an advance over the earlier two-variable methods, leaves a great field untouched. One is tempted to oversimplify, and say that scientific methodology went from one extreme to the other—from two variables to an astronomical number—and left untouched a great middle region. The importance of this middle region, moreover, does not depend primarily on the fact that the number of variables involved is moderate—large compared to two, but small compared to the number of atoms in a pinch of salt. The problems in this middle region, in fact, will often involve a considerable number of variables. The really important characteristic of the problems of this middle region, which science has as yet little explored or conquered, lies in the fact that these problems, as contrasted with the disorganized situations with which statistics can cope, show the essential feature of organization. In fact, one can refer to this group of problems as those of organized complexity.”2

As an example of disordered complexity, Weaver offers a pool table with no side pockets (hence no place for the balls to exit the table), a perfectly frictionless surface, and perfectly rebounding bumpers (figure 1). Place on this table ten balls that can strike one another without losing energy—in short, suspend the laws of thermodynamics for this table and these balls. Now start the ten balls moving in random directions.

fig-1

Figure 1. Pair of pool tables as examples of disordered (above) and ordered (below) complexity. 

Fairly simple math can be used to predict the movement of each ball in some detail, including its impact with the bumpers and other balls. At any given moment, knowing the origin, energy, and direction of each ball at the moment all this movement starts, it’s possible to calculate the position and direction of travel of any given ball at any other moment in time. Take away all knowledge of the original location, direction, and amount of energy and simply observe the balls as they move about the table. More complex math, developed in the last few decades, can still predict the probability of any given ball being at any particular point on the table at any point in time. Statistics have come a long way in the area of unordered complexity.

But place the balls so they are all perfectly aligned and set them in motion so each ball will move around the table without touching another ball, and the math ceases to explain (figure 1). The path of each ball can be independently calculated but there is no way to describe the system as a whole. This is ordered complexity. It’s easy to extend the example with ordered interactions; a perfectly designed system can cause the balls to interact in a way that allows the observer to always know where any given ball will be and what the pattern of interaction will be into the indeterminate future. Even in this situation, the observer will not be able to determine how the system came to be in this state, only predict what the interactions will be among the various balls. Nor can the system be described as a system, rather as individual pieces. While a single formula or set of formulas can be used to describe a disordered system, an ordered system requires a set of formulas.

Weaver placed great weight on the shoulders of the study of organized complexity, from the price of wheat to the stability of currency. Like Weaver, the modern social engineer is placing the same weight on the shoulders of organized complexity. Data scientists, biologists, and those who would build a utopia rely on solving the organized complexity puzzle.

Possible solutions to ordered complexity

So where are we now? What new progress has been made in understanding organized complexity? There are at least two specific recent attempts to explain ordered complexity and its existence in the world around us.3

Relational order theory is the current trend in thinking around complexity. In relational order theory, the position and characteristics of any particular object is only meaningful in relation to other objects. Thus an atom only exists in any meaningful way in relationship to other atoms and space does not exist except in relation to the objects within that space. Processes, in a sense, are embedded into the physical world.4

But this just begs the fundamental question that organized complexity presents: where did the organization come from?

To say that it is just a part of nature is to essentially say nothing at all. Assuming that order is an inherent part of the physical world, and that this inherent order somehow ‘emerges’ from within the physical world as a matter of course, doesn’t answer the question of how order became a part of the physical world. Making these assumptions doesn’t help to explain ordered complexity as a system. It simply posits an alternate source of order other than a designer.

Another effort worth noting is big data analytics. Pioneered by Google, the map/reduce paradigm illustrated in figure 2 is used to find patterns in large scale data sets. Big data is sometimes touted as the solution to understanding, and even managing, societal behaviour. According to Alex Pentland, a pioneer in big data:

“Understanding these human-machine systems is what’s going to make our future social systems stable and safe. We are getting beyond complexity, data science and web science, because we are including people as a key part of these systems. That’s the promise of Big Data, to really understand the systems that make our technological society. As you begin to understand them, then you can build systems that are better. The promise is for financial systems that don’t melt down, governments that don’t get mired in inaction, health systems that actually work, and so on, and so forth.”5
fig-2

Figure 2. The map/reduce processing technique illustrated. 

But big data faces a big problem: it doesn’t always work. Peering deep into the recesses of the big data and its assumptions can uncover two reasons for this problem. First, big data analysis assumes that all the right variables have been collected and pushed into the right algorithm to find the right trend at the right time. That’s an awful lot of ‘rights’ piled on top of one another. Second, big data assumes emergent order and goes about trying to find it by throwing computational power at the problem. Big data, at its foundation, doesn’t try to explain ordered complexity. It simply assumes ordered complexity is a natural property of all complex systems and then sets about trying to discover that order.

But what if order isn’t really emergent in the way big data postulates? In this case, we can expect some early success, followed by a long unwinding, or a lull in progress denoting the trend has reached its peak. As an article in the Financial Times on the unwinding of big data notes, we should (and can) never assume we have all the data.6 Google Flu’s failure in actually predicting the location and extent of 2014’s flu season is an illustrative example pointed out in the article. Anecdotal stories of false positives abound in the real world but never seem to be addressed in ‘the literature’. The New York Times notes nine problems with big data, including, “[big data] never tells us which correlations are meaningful”, the risk of finding apparent correlations that really aren’t, and the echo-chamber effect.7 Big data turns on the concept that all complexity is ordered complexity; treating all complexity as ordered will lead to discoveries of order in apparently unordered data sets that results in the ability to predict (and hence control) the world, even if it is one person at a time. That big data fails should be an alert on the ordered complexity front.

No, we still don’t understand ordered complexity. Begging the question and assuming emergence simply aren’t going to solve the underlying problem, either. What is the problem, then?

At the root lies a materialistic assumption: all there is, is matter.

At the root lies a materialistic assumption: all there is, is matter. If order exists, that order must come from the matter itself in some way. This is carried further in big data; if matter self-organizes, then people must also self-organize in much the same way. The actual existence of ordered complexity becomes proof that emergence must be real; self-organization is somehow ‘built into the DNA’ of the universe (although the universe actually has no DNA). As one atheist, Krauss, states:

“Every day beautiful and miraculous objects suddenly appear, from snowflakes on a cold winter morning to vibrant rainbows after a late-afternoon summer shower. Yet no one but the most ardent fundamentalists would suggest that each and every such object is lovingly and painstakingly and, most important, purposefully created by a divine intelligence. In fact, many laypeople as well as scientists revel in our ability to explain how snowflakes and rainbows can spontaneously appear, based on simple, elegant laws of physics.”8

Many mathematicians and scientists spend time trolling through complexity theories trying to explain design away simply because they can’t accept the existence of a designer. Perhaps, as Krauss believes, there is an answer in simply positing every possible universe that could ever exist has actually existed. On the other hand, a theory that explains every possible outcome has no final explanatory power.

Conclusion

We can’t solve the problems of ordered complexity using the tools of randomness; nor can we explain the order we find in nature by sweeping it under the ‘rug of emergence’. Instead, to make progress on the ordered complexity front, science must face design squarely. Atheism is blind to teleology; materialistic worldviews must reject any concept of purpose at the risk of letting the nose of God into the tent—but ordered complexity, at a systemic level, will ultimately only make sense in the context of teleology, or final intent.

By ignoring design—by assuming emergence—atheistic science is blind to design, and therefore cannot even begin to approach the problem of ordered complexity. This truly harms the progress of science by directing a lot of research time and money down blind alleyways, and by stopping science from asking that one all-important question: why?

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Further Reading

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References and notes

  1. Mitchell, M., Complexity: A Guided Tour, Oxford University Press, New York, p. 286, 2009. Return to text
  2. Weaver, W., Science and complexity, American Scientist 36(4):539, 1948 | jstor.org/stable/27826254. Return to text
  3. A realm of inquiry not covered here is the various attempts at finding a Grand Unified Theory (GUT) that will explain the interaction of all the various systems present in the universe by finding the relationship between the four forces. No widely accepted model of a GUT has emerged, however, and any model that does emerge will still face the problem of where the order on which the model rests comes from. Herrmann, for instance, has been working on a grand unification model that does, in fact, posit an underlying intelligence; see The GGU-model and the GID-model Processes and Their Secular and Theological Interpretations, vixra.org, accessed 18 April 2014. Return to text
  4. Relational Order Theories, en.wikipedia.org, accessed 12 April 2014. Return to text
  5. Pentland, A., Reinventing Society in the Wake of Big Data, edge.org, accessed April 2014. Return to text
  6. Harford, T., Big Data: Are We Making a Big Mistake?, Financial Times, 28 March 2014, ft.com, accessed April 2014. Return to text
  7. Marcus, G. and Davis, E., Eight (No, Nine!) Problems With Big Data, The New York Times, 6 April 2014, nytimes.com, accessed April 2014. Return to text
  8. Krauss, L.M., A Universe from Nothing: Why There is Something Rather than Nothing, Free Press, New York, p. xi, 2012. Return to text

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Readers’ comments
Steven H., United States, 11 February 2016

During college (1963-67) I encountered many of the problems that others have commented upon. Over the years I find that scientists are unprepared for their discipline by inadequate training in classic metaphysics and logic. Melanie Mitchell's argument is riddled with logical fallacies and philosophical errors beyond the scope of a brief comment. It makes discourse difficult when the opposing party is not able to analyze obvious thinking errors ahead of time and reword their language in logical and valid form. This proves that your educational task is enormous. Thank you for your wonderful Christian spirit in giving a 'reason for the Hope'. It is absolutely necessary to continue the good fight.

John L., United States, 7 February 2016

Thank you for this informative article. Back in 1988 I wrote a paper for the Creation Journal titled "The Hindrance of Evolutionary Terminology to the Teaching of Science." I was in medical school at the time and taking a course in Anatomy and Neuroanatomy. Many of the terms for parts of organs were designated by assumed evolutionary development through time and reflected nothing of the structure of the tissue or organ function. Thus, I had to learn far more the number of anatomical terms than needed. The evolutionary terms detracted from my learning. An example would be "Archeocerebellum". What does that mean? The Latin derivative for the proper term is Vestibulocerebellum which reflects a connection (space) between the Cerebellum and the Vestibular Apparatus that is involved in balance. Thus it describes a connection between these structures. The evolutionary term describes nothing functionally and is therefore of no value in the understanding and practice of medicine. There are many other such examples. Evolutionary terms (along with the assumed principles) hinder the teaching of science and medicine.

murk P., Canada, 7 February 2016

thoughtful article - thank you

"At the root lies a materialistic assumption: all there is, is matter. If order exists, that order must come from the matter itself in some way."

Unfortunately this statement relies on immaterial laws. Therefore it refutes itself. This statement depends on the validity of the law of non-contradiction, induction, uniformity and identity which are not dependent on matter.

Furthermore the proclamation of negating purpose itself has purpose.

As always, when dealing with reality, it is required to invoke the very thing asserted to be denied.

eg. the position that the Sovereign one is not behind everything only leaves one possibility - anything can happen

Thus when looking at His creation they see order/purpose/meaning which has been discounted at the start

So then, like you articulated, we get statements like "an atom only exists in meaningful ways to other atoms"

But here the notion of meaningful is invoked - but cannot be accounted for in a matter only universe.

Thank you for the good work

i think of His revelation which clearly teaches that the immaterial precedes the material:

"When there were no watery depths i was given birth,"

"The Lord brought me forth as the first of his works, before his deeds of old;"

Let alone "In the beginning God created..."

requires purpose/meaning/order existing prior to matter existing.

We all know this - the whole enterprise of science rests on immaterial realities and furthermore these foundations are beyond the reach of science

Why are people so determined to sacrifice their given rationality in an attempt to deny the very one who gave and allows this rationality to endure?

David M., Australia, 7 February 2016

Thanks for this article. Seeing computers are so much a part of our modern world (and so interesting to many) it is good to get a christian viewpoint on some of these aspects. Would look forward to more articles from the writer.

Bill I., Canada, 5 February 2016

How much time is wasted on analyzing all of these supposed reasons for matter and order? So many variables to consider takes time away from real work. That's how it seems to me at least. I'm a suspicious guy mind you, and I can't help but wonder if all these atheistic mental gymnastics on these topics is just another way to distract from what is true, real, worthwhile.

I'm grateful for your ministry that has blessed me greatly. Don't get me wrong, it has to be addressed, I guess, but how many hoops are there to jump through? They, the atheists know it, and come up with so much fodder. I'm thinking they just want to waste your time. Keep up the good work.

Joseph M., United Kingdom, 5 February 2016

Evolutionists seem to conveniently leave out the fact that ordered complexity not only can arise from naturalistic processes but it can also arise from CHOICE. Naturalistic processes or chance tends towards patterns. Choice tends towards programming (instructions) or language constructions (codes).

In the cell, translation exhibit specified choice; Codon codes have meaning; Proteins act-out purpose. Instructions and codes are self-evident in the cell. So it’s somewhat foolish for evolutionists to pretend otherwise.

Choice acting into the physical and natural world don’t violate physical or natural laws but can temporarily avoid or make use of physical laws to achieve formal function. Ordered complexity by itself does not give functionality.

Choice gives meaning to ORDERED COMPLEXITY turning it into languages, codes, specified integrated complexity and thus acts on POTENTIAL functionality. Ultimately these choices are instantiated as configurable switches to be reused by reusable processes. So choice alone produces functionality at the beginning.

Naturalistic processes work only on ALREADY existing functionality. Physical or chemical laws are deterministic, thus has no choice.

The only logical and reasonable option we have is design by a supernatural intelligence whose character gives us and the world choice. Genesis 1:3 “And God said, …”

Jonathan Y., United States, 5 February 2016

Excellent article. I recently had an encounter during a leadership training conference with exactly these problems. Trying to define purpose and order and integrity without the foundation of true purpose. A naturalistic worldview that espouses purpose is only espousing the illusion of purpose as their idea of purpose is introspective.

Dan M., United States, 5 February 2016

The atheist Krauss makes another mistaken assumption as is the norm for evolutionists. Quote, "Yet no one but the most ardent fundamentalists would suggest that each and every such object is lovingly and painstakingly and, most important, purposefully created by a divine intelligence."

Krauss shows he doesn't understand the creationist theological point of view, (he is knocking down straw men). We fundamental creationists don't believe God is controlling every little detail of his creation but he is the law giver and sustains his creation through his law. In other words, God set, (created) the laws of physics to organize and maintain his creation after creation week.

I again quote, "In fact, many laypeople as well as scientists revel in our ability to explain how snowflakes and rainbows can spontaneously appear, based on simple, elegant laws of physics." Just because Krauss, (from physics) can explain snowflake formation doesn't mean he understands where the law, (order) came from. He thinks physical laws just happened, which is an illogical assumption. This is why they are without excuse, (Rom 1:20) because the atheist refuses to recognize God as law giver and creator in the face of so much evidence.

Great article!

Arthur G., United Kingdom, 5 February 2016

The article concludes that an atheistic approach to science is blind to design, thereby by "stopping science from asking that one all-important question: why?"

If I may say, science cannot answer the 'why?' question. Science is only concerned with the 'how', based on observation and reason, or simply 'what is'. This no doubt explains why the philosophy of modern science is predominantly materialistic. however, science cannot find purpose in its observations of nature. David Hume was a strict empiricist. In his 'Treatise on Human Nature' he was looking to explain where we can find morality (that is, purpose) in nature. He points out that it is impossible to get from an 'is' to an 'ought' when confined to the natural world. (Fontana-Collins, 1982; Book 3, Section 1.1, p. 203).

Attempting to find purpose in complex systems (biological or otherwise) without admitting design, is quite simply trying to get an 'ought' from an 'is'. It can't be done. The 'why?' of things is outside the remit of operational science. For that we need theology and philosophy.

Peter W., Japan, 5 February 2016

Thank you sincerely for this article. I tried to hang on as best I could through the technical language, having confidence that I would be reassured by the only possible conclusion: Design comes from a Designer. The 'boy who drives the plough' can better the atheist scientist, after all.

It's simple enough to explain in a foreign language: 1) there is obvious design in all things, 2) the presence of design means that must be a Designer, 3) design also requires desire: what did/does the Designer want to do? 4) the Designer's desire is destiny: All things have a purpose, our life is not by chance. God is a Living, Loving, Good and Giving, Great and Glorious God. Bless the Lord for His wisdom.

The article reminds me of a lecture online given by Chuck Missler, speaking about information and design. Missler spoke of a limit to how small something can be, after a certain point an entity 'would lose locality'. Missler mentioned that an advanced mathematician or physicist who studied this came to a shocking conclusion: Every atom is somehow aware of the location of every other atom, and the obvious implication of this drove him (the physicist, not Missler) to suicide.

For a believer, secure in knowledge and devotion to the Creator who is by definition apart from His creation, such a revelation is not shocking at all, but rather inspiring. Those who refuse to see deprive themselves of life; may our prayers and outreach be kind and merciful.

Would you be able to identify the scientist that Missler was speaking of, or enhance my understanding of what Missler was speaking of?

In Christ, Peter Warner.

Japan.

Tas Walker responds

Sorry, but I don't know the scientist he was talking about.

Phil M., Australia, 4 February 2016

‘Process’ is a common term when talking science. ‘Event’ is a common term when talking history. Now there is a clear difference between a ‘natural/scientific process’ and an ‘historical event’, and more particularly a ‘chance historical event’, and even more particularly an ‘unobserved chance historical event’.

‘Natural processes’ are deterministic – the steps in a process that convert initial reactants into an intermediate(s) into another into another into the final outcome(s) are all pre-determined – both the sequence of the steps, their intermediates and the final result. They are always consistent. This is why we can always predict the outcome of an uninterrupted chemical or biological process, and we give them names e.g. metamorphosis, photosynthesis, etc.

Now there is no scientific process anywhere in nature that can convert chemical molecules into a biological cell – non-living chemicals into a living cell. Therefore for darwinists to attempt to speak of the origin of the biological cell in terms of ‘natural processes’ is ludicrous, and they should not be allowed to get away with it.

And any to attempt to delve into historical novelty and construct an historical scenario of chance events, and call the events ‘natural’ and the scenario ‘scientific’, is not the stuff of either history or science.

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