Specified complexity

Specified Complexity is a concept that was developed by intelligent design advocate William Dembski . It is intended to formalize a property that is intended to distinguish certain patterns as specified and complex. Dembski claims that specified complexity is a reliable indicator of design by an intelligent actor, a central tenet of intelligent design. With this Dembski tries to argue against the theory of evolution .

In Dembski's terminology, a specified pattern can be described succinctly, while a complex pattern is unlikely to arise by chance. Dembski argues that specified complexity cannot possibly exist in patterns created by unmanaged processes. Hence, according to Dembski, the presence of specified complex patterns in living things indicates that they were necessarily originally designed for some form of expediency, which he argues suggests intelligence. Dembski further asserts that one can rigorously prove with the no-free-lunch theorems that evolutionary algorithms cannot possibly select for configurations of high specified complexity and therefore cannot generate them. Dembski also refers to specified complexity as complex-specified information (CSI).

In the literature on intelligent design, an intelligent actor chooses between various available possibilities and in this way designs the forms of life using means and methods that are not expressly mentioned. According to Dembski, specified complexity should be an 'explanatory filter', which enables the recognition of 'design' by hitting complex-specified information. The filter is based on the assumption that the categories regularity, randomness and design, according to Dembski, are disjoint and complete. Complex-specified information is supposed to be an indicator of design because it is supposed to be an indication of intelligent authorship; it is intended to be an indicator of the implementation of a certain of many competing possibilities.

The concept of specified complexity and the related considerations are widely viewed as inconsistent. She describes an examination of Dembski's work as riddled with contradictions, ambiguities, incorrect use of mathematics, poor scientific craftsmanship and misinterpretation of other people's results. Another objection concerns Dembski's probability calculations. According to Martin A. Nowak , a Harvard professor of mathematics and evolutionary biology, the probability of the formation of an eye cannot be calculated because the information for this calculation is not available. In addition, the use of the specified complexity to infer design as an argument is rejected ad ignorantiam .

definition

Origin at organ

The term 'specified complexity' was originally used by the chemist Leslie Orgel (who did research on the origin of life) to distinguish animate from inanimate matter:

"In brief, living organisms are distinguished by their specified complexity. Crystals are usually taken as the prototypes of simple well-specified structures, because they consist of a very large number of identical molecules packed together in a uniform way. Lumps of granite or random mixtures of polymers are examples of structures that are complex but not specified. The crystals fail to qualify as living because they lack complexity; the mixtures of polymers fail to qualify because they lack specificity. "

- Leslie Orgel : The Origins of Life (1973), p. 189.

The term was later used in a similar way by physicist Paul Davies :

“[Living] organisms [are] so mysterious not because of their complexity per se, but because of their precisely specified complexity. If we want to understand how the non-living could become living, we not only have to know how biological information acquired its current, concentrated format, but also how biologically useful information is contained in the presumably quite random mixture of molecular building blocks that made up the first organisms have grown, so specific could become. "

- Paul Davies : Das fifth Wunder (1998), p. 119. Italics in the original.

Dembski

For Dembski, the specified complexity is a property that can be observed in living things. However, while Orgel uses the term for something that, in Darwin's theory, is supposed to arise through (unguided) evolution, Dembski uses it for something that, according to his own thesis, cannot arise through undirected evolution - and concludes that therefore one does so can draw conclusions about intelligent design. While Orgel has used the concept in a qualitative way, Dembski intends to use it quantitatively. Dembski's use of the concept is first found in his book The Design Inference (1998). Specified complexity forms the basis of his intelligent design approach, and each of his subsequent books is largely concerned with the concept. In his view: If there is a way to recognize design, then it is specified complexity.

According to Dembski, specified complexity is present in a configuration if it can be described by a pattern that shows a large amount of independently specified information and at the same time is complex, which he defines as the low probability of the pattern occurring. As examples to demonstrate his concept, he mentions the letter A as specified but not complex. A long sequence of random letters is complex but unspecified. A Shakespeare sonnet should be complex and specified at the same time.

In his early writings, Dembski defines complex-specified information (CSI) as being in a specified event with a probability of less than present. He calls this the universal probability limit . In this context "specified" is intended to mean what he later calls "pre-specified", something that is specified before information about the output is known. The value of the universal probability limit corresponds to the inverse of the upper limit calculated by Dembski for the complete number of possible specified events in cosmic history. Everything below this limit should contain CSI. The terms 'specified complexity' and 'complex-specified information' are used interchangeably. In more recent writings, Dembski has redefined the universal probability limit by referring to another number which corresponds to the full number of bit operations that could possibly be performed in the entire history of the universe. ${\displaystyle 1:10^{150}}$

According to Dembski, CSI exists in various features of living things, such as DNA and other functional biological molecules. He argues that it cannot arise solely from known natural mechanisms of the laws of physics and chance, or a combination thereof. This should be so, because information could only be shifted back and forth or lost due to regularities, but it cannot be generated in his eyes, and because only complex, unspecified information can arise by chance, but no CSI. It offers a mathematical analysis that is supposed to show that law and chance together cannot generate a CSI. In addition, CSI should be holistic , the whole more than the sum of its parts, and this should effectively exclude Darwinian evolution as its possible source. Dembski takes the position that through the elimination procedure CSI can best be explained by intelligence, and should therefore be a reliable indicator of design.

Information preservation

Dembski sends a law of conservation of information to the field:

"This strong proscriptive claim, that natural causes can only transmit CSI but never originate it, I call the Law of Conservation of Information. Immediate corollaries of the proposed law are the following: 1. The specified complexity in a closed system of natural causes remains constant or decreases. 2. The specified complexity cannot be generated spontaneously, originate endogenously or organize itself (as these terms are used in origins-of-life research). 3. The specified complexity in a closed system of natural causes either has been in the system eternally or was at some point added exogenously (implying that the system, though now closed, was not always closed). 4. In particular any closed system of natural causes that is also of finite duration received whatever specified complexity it contains before it became a closed system. "

- William A. Dembski : Intelligent Design as a Theory of Information (1998).

A paper does a careful analysis of Dembski's law of conservation of information. Its author concludes that it is mathematically baseless.

Dembski notes that the term "Law of Conservation of Information" was previously used by Peter Medawar in his book The Limits of Science (1984) to describe the weaker claim that deterministic laws cannot generate new information. The actual validity and usefulness of Dembski's proposed law remains in doubt; it is neither cited nor discussed in the scientific literature.

Specificity

In a recent essay, Dembski offers what he believes is a simpler representation that is closer to the Fisher test . Dembski suggests interpreting the design conclusion as a statistical test that rejects a random hypothesis in a result space . ${\displaystyle \mathrm {P} }$ ${\displaystyle \Omega }$

Dembski's proposed test is based on the Kolmogorov complexity of a pattern that is present when an event occurs . Mathematically is a subset of , the pattern determines a set of outcomes in and is a subset of . Dembski writes ${\displaystyle T}$ ${\displaystyle E}$ ${\displaystyle E}$ ${\displaystyle \Omega }$ ${\displaystyle T}$ ${\displaystyle \Omega }$ ${\displaystyle E}$ ${\displaystyle T}$

"Thus, the event might be a die toss that lands six and might be the composite event consisting of all die tosses that land on an even face." ${\displaystyle E}$ ${\displaystyle T}$

- William Dembski : loc. cit. P. 16

Kolmogorow's complexity provides a degree of computational capacity that is necessary to specify a pattern (for example a DNA sequence or a series of letters from the alphabet). For a pattern there are a number of patterns that have the same or less Kolmogorov complexity. The number of such patterns is denoted by. therefore forms a hierarchy over the patterns, from the simplest to the most complex. As an example, Dembski claims that for a pattern describing the scourge of a bacterium, an upper limit of is obtained. ${\displaystyle T}$ ${\displaystyle \phi (T)}$ ${\displaystyle \phi (T)}$ ${\displaystyle T}$ ${\displaystyle \phi (T)\leq 10^{20}}$

Dembski defines the specified complexity of a pattern under the random hypothesis as ${\displaystyle T}$ ${\displaystyle \mathrm {P} }$

${\displaystyle \sigma =-\log _{2}[R\times \varphi (T)\times \operatorname {P} (T)],}$

where is the probability of observing the pattern and the number of replicational resources available to witnessing agents. can be roughly compared to repeated attempts to create and perceive a pattern. Dembski claims that with can be limited. This figure is justified in his eyes by the results of Seth Lloyd, in which he states that the number of elementary logic operations that could be performed over the full history of the universe does not exceed operations on bits. ${\displaystyle \mathrm {P} (T)}$ ${\displaystyle T}$ ${\displaystyle R}$ ${\displaystyle R}$ ${\displaystyle R}$ ${\displaystyle 10^{120}}$ ${\displaystyle 10^{120}}$ ${\displaystyle 10^{90}}$

Dembski's central assertion is that the following test can be used to infer design for a configuration: There is a target pattern that fits the configuration and whose specified complexity is greater than 1. This condition can also be expressed by the inequality ${\displaystyle T}$

${\displaystyle 10^{120}\times \varphi (T)\times \operatorname {P} (T)<{\frac {1}{2}}}$

to be discribed.

Dembski's explanation

Dembski's expression has no relation to a well-known concept from information theory, although he claims to be able to justify its relevance as follows: An intelligent actor observes an event and assigns it to a reference class of events . Within this reference class, he considers it meeting the specification . Then consider the number (where the "chance" hypothesis is): ${\displaystyle \sigma }$ ${\displaystyle \mathrm {S} }$ ${\displaystyle E}$ ${\displaystyle \Omega }$ ${\displaystyle T}$ ${\displaystyle \phi (T)\times \mathrm {P} (T)}$ ${\displaystyle \mathrm {P} }$

Possible goals with position in the complexity hierarchy and probability that do not exceed that of the achieved goal . Probability of union does not exceed ${\displaystyle T}$ ${\displaystyle \phi (T)\times \mathrm {P} (T)}$

"Think of as trying to determine whether an archer, who has just shot an arrow at a large wall, happened to hit a tiny target on that wall by chance. The arrow, let us say, is indeed sticking squarely in this tiny target. The problem, however, is that there are lots of other tiny targets on the wall. Once all those other targets are factored in, is it still unlikely that the archer could have hit any of them by chance? In addition, we need to factor in what I call the replicational resources associated with , that is, all the opportunities to bring about an event of 's descriptive complexity and improbability by multiple agents witnessing multiple events. " ${\displaystyle \mathrm {S} }$ ${\displaystyle \mathrm {T} }$ ${\displaystyle \mathrm {T} }$

- William Dembski

According to Dembski, replication capacities can be limited by the maximum number of bit operations that the known, perceptible universe could have performed throughout its billions of years of history, according to Lloyd . Such assessments have led to the misunderstanding that intelligent design is a milder form of creationism that a higher age would accept. However, Dembski only tries to conclude a stronger assertion, so that it should also apply to the assumption of an Earth age of billions of years, but even more so to the assumption of about 10,000 years, because the replication capacities there are much lower. ${\displaystyle 10^{120}}$

According to Elsberry and Shallit, however, the specified complexity was never formally published in a recognized, peer-reviewed mathematical journal and, to the best of their knowledge, has not been adopted by any scientist in information theory.

calculation

So far, Dembski has only made one attempt to calculate the specified complexity of a naturally occurring biological structure - the bacterial scourge of E. coli - in his book No Free Lunch . This structure can therefore be described by the pattern of a "bidirectional rotary motor-driven propeller". Dembski estimates that there are at most patterns that are described by four or fewer concepts, so his test of design will work if ${\displaystyle 10^{20}}$

${\displaystyle \operatorname {P} (T)<{\frac {1}{2}}\times 10^{-140}.}$

However, Dembski says that the exact calculation of the relevant probability has yet to be done ("has yet to be done"), although he also claims that some methods for calculating these probabilities are already available ("are now in place").

These methods assume that all of the components of the Scourge were created entirely by chance, a scenario that biologists do not seriously consider. He justifies this approach by citing Michael Behe's concept of irreducible complexity (IC), which leads him to believe that the Scourge cannot be the result of a gradual and gradual process. The validity of Dembski's special consideration therefore stands and falls entirely with Behe's IC concept. It is potentially vulnerable to any attempt to attack this concept, of which there are many.

In order to reach the upper limit of patterns, Dembski considers a specification pattern for the scourge, which is defined by the (natural language) predicate "bidirectional rotary motor-driven propeller" and which he regards as determined by four independently selected basic concepts. He also assumes that the English language has the ability to express at most basic concepts (an upper limit on the size of a dictionary). Dembski claims that you can get the approximate upper limit of ${\displaystyle 10^{20}}$ ${\displaystyle 10^{5}}$

${\displaystyle 10^{20}=10^{5}\times 10^{5}\times 10^{5}\times 10^{5}}$

for the set of patterns described by four or fewer basic concepts.

From the standpoint of Kolmogorov complexity theory, this calculation is questionable. According to Ellsberry and Shallit, the natural language specification without restrictions, as Dembski tacitly allows, seems problematic, since it leads, among other things, to the Berry paradox . According to the two authors, nothing speaks against a natural language specification if there was a clear way of translating it into Dembski's formal framework. However, there was no precise definition of the event space . ${\displaystyle \Omega }$

criticism

The validity of Dembski's concept of specified complexity and the validity of the arguments he makes with this concept have largely been heavily questioned. A common criticism (see Elsberry and Shallit) is that Dembski uses the terms "complexity", "information" and "improbability" as if they were interchangeable. However, they measure properties of things of different types: complexity measures indicate how difficult it is to describe an object (for example a sequence of bits), information determines how random a probability distribution is, and improbability indicates how unlikely an event is relative to a probability distribution is.

If Dembski's mathematical claims about the specified complexity are interpreted to be reasonably meaningful and conform to the minimum artisanal standards of mathematics, then they usually turn out to be false. Dembski often evades these criticisms by responding that it is not his job to provide rigorous mathematical evidence that material mechanisms cannot create a specified complexity. Nevertheless, he claims that he can prove his thesis mathematically:

"In this section I will present an in-principle mathematical argument for why natural causes are incapable of generating complex specified information."

"In this section I will present a fundamentally mathematical argument for why natural causes cannot generate complex-specified information."

- William Dembski, No Free Lunch , p. 150

Others have pointed out a critical calculation error on page 297 of No Free Lunch , with a deviation by an approximate factor . ${\displaystyle 10^{65}}$

Dembski's calculations show that for a simple smooth function (like ) no increase in information is possible. He concludes from this that there has to be a designer so that CSI can arise. However, natural selection is characterized by branching from one individual to many (reproduction), followed by reducing the many back to a few (selection). Dembski does not model these increasing and decreasing figures at all. In other words, Dembski's calculations do not take birth and death into account. This fundamental mistake, however, makes all subsequent calculations and considerations in No Free Lunch irrelevant, as its basic model does not reflect reality. Since the foundation of No Free Lunch is based on this flawed argument, the entire thesis of his book collapses completely. ${\displaystyle y=x^{2}}$

Dembski's critics note that specified complexity, as originally defined by Leslie Orgel, is exactly what one would expect to result in Darwinian evolution. To this end, a whole series of arguments is put forward that show individual errors in reasoning even under the assumption that the rest of the work would be fundamentally correct. It is emphasized that Dembski uses the term 'complex' for what would normally be described as 'absurdly improbable'. It is also argued that the argument is a tautology: CSI cannot arise because Dembski defined it that way. Therefore, in order to demonstrate the existence of CSI, it would be necessary to show that some biological traits would undoubtedly have an extremely low probability of arising from any combination of any natural occurrence, something that Dembski does not seriously attempt. Such calculations depend on an accurate assessment of the various contributing probabilities, the determination of which is often necessarily subjective. Therefore, CSI can in principle at most provide an apparently very high probability, but never a certainty.

Another point of criticism concerns the problem of arbitrary but specified results. For example, any given person is unlikely to win a lottery, but nonetheless there are regular winners. To argue that any particular player is very unlikely to win is not the same as proving that no one will win at all with the same probability. Similarly, the objection was raised that a space of possibilities is merely explored, and that people, as pattern-seeking animals, only interpret patterns, and thus purpose, in retrospect. Another criticism concerns the often redundant information in the genome, which makes its information content much less than the number of base pairs used.

Alongside such theoretical considerations, critics cite reports of the type of spontaneous generation that Dembski claims is too unlikely to occur naturally. For example, in 1982 BG Hall claimed to have shown that after removal of a gene used to digest sugar from certain specific bacteria, new sugar-digesting enzymes formed very quickly and replaced the removed ones as soon as they were grown on a high-sugar medium.

literature

• William A. Dembski, The Design Inference: Eliminating Chance through Small Probabilities. (Cambridge: Cambridge University Press, 1998). ISBN 0521623871
• William A. Dembski, No Free Lunch: Why Specified Complexity Cannot Be Purchased without Intelligence. (Lanham, Md .: Rowman & Littlefield, 2002). ISBN 0742512975
• Paul Davies, The Fifth Miracle. In search of the origin of life (Bern, Munich, Vienna: Scherz Verlag, 2000). Original: The Fifth Miracle: The Search for the Origin and Meaning of Life (London: Allen Lane and New York: Simon & Schuster, 1998)

See also

• Proof of God

Web links

• Not a Free Lunch But a Box of Chocolates - A critique of William Dembski's book No Free Lunch by Richard Wein, TalkOrigins
• Information Theory and Creationism William Dembski of Rich Baldwin, from Information Theory and Creationism, compiled by Ian Musgrave and Rich Baldwin
• Critique of No Free Lunch by H. Allen Orr of the Boston Review
• Dissecting Dembski's "Complex Specified Information" by Thomas D. Schneider.
• William Dembski's treatment of the No Free Lunch theorems is written in jello by David Wolpert

Sources and Notes

1. ^ Rich Baldwin: Information Theory and Creationism . talkorigins (2005)
2. ^ Mark Perakh: Dembski "displaces Darwinism" mathematically - or does he? . talkreason (2005).
3. ↑ Jason Rosenhouse: How Anti-Evolutionists Abuse Mathematics ( Memento of the original from May 16, 2005 in the Internet Archive ) Info: The archive link was automatically inserted and not yet checked. Please check the original and archive link according to the instructions and then remove this notice. . The Mathematical Intelligencer 23 : 4 (2001), pp. 3-8. 
4. ↑ Wesley Elsberry , Jeffrey Shallit : Information theory, evolutionary computation, and Dembski's “complex specified information” . In: Synthesis . tape 178 , no. 2 , January 2011, p. 237-270 , doi : 10.1007 / s11229-009-9542-8 : "Dembski's work is riddled with inconsistencies, equivocation, flawed use of mathematics, poor scholarship, and misrepresentation of others' results" (p. 238). Freely accessible preliminary version (2003): talkreason.org (PDF file; 535 kB).
5. ^ Martin Nowak: The Evolution Wars. In: Time Magazine . August 15, 2005, p. 32 , accessed on July 29, 2015 : “ We cannot calculate the probability that an eye came about. We don't have the information to make the calculation. " 
6. ↑ In German, for example: In short, living organisms are characterized by their 'specified complexity'. Crystals usually serve as the prototypes of simple well-specified structures because they consist of a very large number of identical molecules packed together in a uniform manner. Chunks of granite or random mixtures of polymers are examples of structures that are complex but unspecified. The crystals cannot be considered alive because they lack complexity; the polymer mixtures cannot be considered living because they lack specificity.
7. ^ "If there is a way to detect design, specified complexity is it", William A. Dembski: No Free Lunch (2002), p. 19.
8. ↑ "A single letter of the alphabet is specified without being complex. A long sentence of random letters is complex without being specified. A Shakespearean sonnet is both complex and specified", William A. Dembski: Intelligent Design (1999), p. 47 .
9. ^ "The total number of [possible] specified events throughout cosmic history," William A. Dembski: The Design Revolution: Answering the Toughest Questions About Intelligent Design (2004), p. 85.
10. ↑ In German, for example: I call this very restrictive assertion that natural causes CSI never arise, but can only transfer it, I call the Information Conservation Act. Direct consequences of the law are: 1. The specified complexity in a closed system remains constant or decreases. 2. The specified complexity cannot arise spontaneously or endogenously and cannot organize itself (as these terms are used in origins research). 3. The specified complexity in a closed system, on which only natural processes act, was either always present or was brought in from outside at a time (from which it follows that the system, although currently closed, was not always closed). 4. In particular, every closed system of finite persistence, on which only natural processes act, has acquired any specified complexity before it became a closed system.
11. ^ "That the Law of Conservation of Information is mathematically unsubstantiated", Erik: On Dembski's law of conservation of information (2002). (PDF file; 195 kB)
12. ↑ "to describe the weaker claim that deterministic laws cannot produce novel information", Searching Large Spaces: Displacement and the No Free Lunch Regress , pp. 15-16 (356k PDF; 365 kB) on an argument by Michael Shermer in How We Believe : Science, Skepticism, and the Search for God (2003), 2nd edition.
13. ^ William A. Dembski: Specification: The Pattern that Signifies intelligence (2005; PDF; 392 kB).
14. ↑ In German, for example: So the event could be the throw of a die showing six, and could be the composite event of all throws that land on an even number. ${\displaystyle E}$ ${\displaystyle T}$
15. ^ Michael Sipser: Introduction to the Theory of Computation (PWS Publishing Company, 1997).
16. ^ Seth Lloyd : Computational capacity of the universe. Phys. Rev. Lett 88 : 23 (2002), 790 1-4, arxiv : quant-ph / 0110141 .
17. ↑ In German, for example: You have to imagine trying to find out whether an archer who has just shot an arrow on a large wall accidentally hit a tiny target on that wall. Once all the other targets have been factored in, is it still unlikely that the archer hit any of the targets by accident? In addition, we need to include what I call the associated reproductive capacities, all opportunities, so to speak, that an event of descriptive complexity and improbability is caused by multiple actors perceiving multiple events. ${\displaystyle \mathrm {S} }$ ${\displaystyle \mathrm {T} }$ ${\displaystyle \mathrm {T} }$
18. ↑ "the maximum number of bit operations that the known, observable universe could have performed throughout its entire multi-billion year history"
19. ↑ Wesley Elsberry , Jeffrey Shallit : Information theory, evolutionary computation, and Dembski's “complex specified information” . In: Synthesis . tape 178 , no. 2 , January 2011, p. 237–270 , doi : 10.1007 / s11229-009-9542-8 : "[specified complexity] has not been defined formally in any reputable peer-reviewed mathematical journal, nor (to the best of our knowledge) adopted by any researcher in information theory " (p. 244). Freely accessible preliminary version (2003): talkreason.org (PDF file; 535 kB).
20. ↑ "Natural language specification without restriction, as Dembski tacitly permits, seems problematic. For one thing, it results in the Berry paradox" and "We have no objection to natural language specifications per se, provided there is some evident way to translate them to Dembski's formal framework. But what, precisely, is the space of events here? " (loc. cit, p. 24) ${\displaystyle \Omega }$
21. ↑ for example "I'm not and never have been in the business of offering a strict mathematical proof for the inability of material mechanisms to generate specified complexity", William A. Dembski: If Only Darwinists Scrutinized Their Own Work as Closely: A Response to "Erik" (2002).
22. ↑ Jeffrey Shallit: A review of Dembski's No Free Lunch (2002) Dembski's answer
23. ↑ Thomas D. Schneider: Dissecting Dembski's "Complex Specified Information" ( Memento of the original from October 26, 2005 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. (2002) 
24. ↑ "A space of possibilities is merely being explored, and we, as pattern-seeking animals, are merely imposing patterns, and therefore targets, after the fact", William A. Dembski: Intelligent Design as a Theory of Information (1998).
25. ^ BG Hall: Evolution of a regulated operon in the laboratory. Genetics 101 : 3-4 (1982) 335-44. PMID 6816666