Is intelligent design a possible cause of the origin of biological information?

In his 7th chapter Meyer discusses the nature of “historical sciences” such as geology and paleontology and evolutionary biology and argues that they use different methods to “experimental sciences” such as physics and chemistry.

He states that Stephen Jay Gould accepted this distinction and argued that historical scientific theories were testable by analysing their “explanatory power” (Gould, “Evolution and the Triumph of Homology”) Gould describes the process of testing in historical sciences as seeking “consilience”. Consilience is the situation where many facts can be explained well by a single proposition or theory.
Gould argues that historical sciences depend upon the knowledge of the laws of nature to make inferences about the past.

Meyer then asks whether a design hypothesis can be formulated as a historical scientific theory about what happened in the past.

Historical scientists cite the occurrence of an event or series of events in the past as the explanation for some observable phenomenon in the present.

Historical scientists use a distinctive mode of reasoning. Using their knowledge of cause and effect relationships historical scientists “calculate backwards” and infer past conditions and causes from present conditions and causes.

This type of reasoning is called “abductive” reasoning as opposed to inductive (in which a universal law is established from repeated observations) or deductive (in which a particular fact is deduced by applying a general law to another particular case.

Abductive logic was first described by Charles Sanders Pierce.

Despite the tentative nature of abductive reasoning we do make conclusive inferences about the past.

A conclusion of abductive reasoning is certain if we cannot explain the currently observed facts without the past cause.

An abductive conclusion is established by showing that it is either the best or the only explanation of the effects in question.

To address this problem in geology Thomas Chamberlain proposed a method of “multiple working hypotheses. This is also known as “inference to the best explanation”

Peter Lipton is associated with this way of reasoning arguing that it is used both in science and ordinary life. Discovering certain particular marks in fresh snow we infer that a person with snow shoes has passed this way. Lipton argued that the ability to explain particular facts sometimes mattered more than predictive success in the evaluation of a particular hypothesis.

The problem with this method of assessing explanations is exactly how we judge which is the best explanation as opposed to the explanation we like the best.
What makes an explanation the best?
1. A good explanation is causal.
2. A good explanation for a particular event is something which provides a “causal difference” in the outcome.

Historical scientists use the principle of causal adequacy. Causes that are known to produce the effect in question are better explanations. Charles Lyell expressed this as – “explanation of the past by causes now in operation.” Michael Scriven described this method as “retrospective causal analysis.” The candidate cause must provide independent evidence showing itself able to produce this effect on other occasions.

When there is only one possible cause for a particular effect the solution to the problem of what really happened is easy. This situation is where historical scientists can infer a uniquely plausible cause. For example an archaeologist who knows that scribes are the only known cause of linguistic inscriptions will, when they find a tablet containing ancient writing infer scribal activity. Where a particular past cause is known to be necessary to produce a subsequent effect, the occurrence of the effect is taken as sufficient to establish the occurrence of the cause.

Where there is more than one possible cause the situation is more difficult. In this case scientists will look for additional evidence that can help distinguish the explanatory power of the remaining explanations. They will look for additional facts for which there is only one adequate causal explanation. In practice the process of determining the best explanation involves examining a list of possible hypotheses. These will be compared for their known causal powers against the relevant evidence and then, like a detective, the scientist will progressively eliminate inadequate explanations until only one is left.

A second way of addressing this problem is to ask which of the adequate causes was actually present at the time of the event in question. Thus two criteria are needed:
1. causal adequacy
2. causal existence
To meet the second criteria historical scientists must show that the proposed cause is not only able to produce the event in question but that it was actually present at the right time and in the right place.
There are two ways of doing this
1. Showing the presently acting course must have been present in the past because this cause is the only known cause of the effect in question.
2. By examining a wider class of facts to show that only one other possible cause explains the whole collection.

Michael Scriven summarises situation. To establish a causal claim a historical scientist
1. needs to show that his proposed cause was present
2. that his proposed cause able to produce the effect under study
3. there is an absence of evidence of other possible causes.

Many scholars think that Charles Darwin structured his argument in the Origin to show that natural selection was both causally adequate and had causal existence. His theory of universal common descent could not be tested by predicting future outcomes under controlled experimental conditions. It could be demonstrated to be right by showing that it could explain already known facts in a more adequate fashion.

The question is now whether a case for an intelligent cause can be formulated and justified in this way. Is intelligent design a possible historical scientific explanation for the origin of biological information? Is it possible to formulate a case for intelligent design as an inference to the best explanation for the origin of biological information?

It is possible to conceive of the purposeful acts of an intelligent agent is a causal event. This clearly represents a known and presently acting adequate cause for the origin of information.

Our uniform and repeated experience indicates that intelligent agents produce information rich systems.

What causes now in operation produce digital code or specified information? Is there a known cause of the origin of such information? What does our uniform experience tell us?

Intelligent design must qualify at least as a possible scientific explanation for the origin of biological information.
Is intelligent design the only known or adequate cause of the origin specified information? If so then the past action of designing intelligence will be established as the strongest and most logically compelling form of historical inference.

Is ID Science?

This is not a simple or straight forward question. It is the question that Meyer addresses in his 7th chapter. I think I found this the most difficult chapter in the book.

Meyer discusses the nature of “historical sciences” such as geology and paleontology and evolutionary biology and argues that they use different methods to “experimental sciences” such as physics and chemistry. He states that Stephen Jay Gould accepted this distinction and argued that historical scientific theories were testable by analysing their “explanatory power” (Gould, “Evolution and the Triumph of Homology”) Gould describes the process of testing in historical sciences as seeking “consilience”. Consilience is the situation where many facts can be explained well by a single proposition or theory. Gould he says argues that historical sciences depend upon the knowledge of the laws of nature to make inferences about the past.
Meyer then asks whether a design hypothesis can be formulated as a historical scientific theory about what happened in the past.

Historical scientists cite the occurrence of an event or series of events in the past as the explanation for some observable phenomenon in the present. Historical scientists use a distinctive mode of reasoning. Using their knowledge of cause and effect relationships historical scientists “calculate backwards” and infer past conditions and causes from present conditions and causes.

This type of reasoning is called “abductive” reasoning as opposed to inductive(in which a universal law is established from repeated observations) or deductive (in which a particular fact is deduced by applying a general law to another particular case. Abductive logic was first described by Charles Sanders Pierce
Despite the tentative nature of abductive reasoning we do make conclusive inferences about the past.

A conclusion of abductive reasoning is certain if we cannot explain the currently observed facts without the past cause. An abductive conclusion is established by showing that it is either the best or the only explanation of the effects in question.

To address this problem in geology Thomas Chamberlain proposed a method of “multiple working hypotheses. This is also known as “inference to the best explanation”
Peter Lipton is associated with this way of reasoning arguing that it is used both in science and ordinary life. Discovering certain particular marks in fresh snow we infer that a person with snow shoes has passed this way. Lipton argued that the ability to explain particular facts sometimes mattered more than predictive success in the evaluation of a particular hypothesis.

The problem with this method of assessing explanations is exactly how we judge which is the best explanation as opposed to the explanation we like the best.

What is the relationship of ID to Science? Is it Science?

Image from here


In his sixth chapter of “Signature in the Cell” Meyer presents the view that the scientific enterprise is much wider than “doing experiments.”
Kekule famously “discovered” the structure of benzene while having a daydream about snakes seizing their own tails.

I turned my chair to the fire [after having worked on the problem for some time] and dozed. Again the atoms were gamboling before my eyes. This time the smaller groups kept modestly to the background. My mental eye, rendered more acute by repeated vision of this kind, could not distinguish larger structures, of manifold conformation; long rows, sometimes more closely fitted together; all twining and twisting in snakelike motion. But look! What was that? One of the snakes had seized hold of its own tail, and the form whirled mockingly before my eyes. As if by a flash of lighting I awoke... Let us learn to dream, gentlemen.

Meyer uses the example of Watson and Crick who relied on other people’s experimental results and their own model building to present the structure of DNA. Once they had the idea…it was obviously right!
Copernicus, Newton and Einstein are among the most famous scientists but none of them were outstanding in terms of their laboratory experiments.
Darwin is not a famous scientist because of his experimental results on seed dispersal or worms or movement in plants.
Meyer reminds us that for the early days of science intelligent design was not a controversial or career breaking interest. A. N. Whitehead is quoted:
“There can be no living science unless there is a widespread conviction in the existence of an Order of Things, in particular, of an Order of Nature.”
This Whitehead argues was provided by the Christian belief in the rationality of God.
Steve Fuller has amplified Whitehead’s observation. Science began because theists believed that an intelligent God made the universe to be intelligible to human beings made in his image.
Why has intelligent design which was so important in the origin of science become so completely rejected from modern science?

The experiment that launched evolution.

"Charles Darwin did little experimental science. He did make several descriptive studies of barnacles and worms and some experimental studies about how species spread through seed dispersal and other processes. Yet his masterpiece, On the Origin of Species by Means of Natural Selection, contains neither a single mathematical equation nor any report of original experimental research. Yet he formulated a great scientific theory."

Stephen Meyer - Signature in the Cell p139

The Axe-Meyer Axis.

This is an attempt to state more clearly what I tried to say before...
How is Axe's published work relevant to ID?

Past posts for reference:
I was thinking...
J.Mol.Biol- 2000 -301-585-595
Controversial paper
Appearance of design


Making a functional protein from scratch is difficult. This is relevant in two situations(a) In a prebiotic soup making a protein to help stabilise or increase the function of a precellular replicon.
(b) after the origin of life the development of a brand new structural or functional protein which enhances the reproductive capacity of the organism.

The following argument is my version of what Stephen Meyer says on p206 and following in Signature in the Cell.

Most functional proteins are over 150 amino acids long. The average is estimated at around 300 amino acids long. With 20 different amino acids a protein 150 amino acids long gives a very large number of possible sequences - 10¹⁹⁵ (which is a pretty big number)

Firstly in a prebiotic soup with an abundance of amino acids there are a number of possible ways in which amino acids can link up- however to get a folding protein we need peptide bonds. The probability of forming a peptide link is about 1 in 2.

To get a 150 amino acid molecule with peptide bonds the whole way along will be a probability of 1 in 10⁴⁵.

Secondly in a prebiotic soup there will be 2 optical isomers of each amino acid. All the functional proteins in nature use only L isomers.

To get a 150 amino acid molecule with only L isomers the probability is also 1 in 10 ⁴⁵.

Thirdly there are constraints in terms of the exact order of amino acids that will produce a protein that can fold into a globular shape with the possibility of having a function.

Fourthly there are constraints in terms of the exact order of amino acids that will produce a protein that has a function.

The fourth issue was investigated by Robert Sauer in the late 1980's at MIT. Cassette mutagenesis was used to examine the tolerance to sequence change at a number of locations in a variety of proteins.

The results showed that the probability of acheiving a functional sequence in several small proteins was very low. In other words there are very few different combinations of amino acids that allow the function to be maintained.

The chance of hitting on one of these by chance was about 1 in 10⁶³.

Doug Axe was interested in Sauer's work and began to wonder if he had underestimated how much protein sequences can vary and still retain function.

He developed a more rigorous mechanism to test this. The results in a paper published in 2004 were particularly important. On the basis of these results Axe was able to demonstrate that the ratio of functional sequences to non functional sequences for the enzyme beta-lactamase was 1 functional sequence to every 1 x10^77.

Axe's work also allowed him to calculate the probabilities of finding any functional sequence amongst the possible sequences. This was done by looking at the probability of sequences being able to form stable folds (a necessary pre-requisite for stable 3D structure)

On the basis of his work he calculated the ratio of sequences able to form stable 3D structures to those which were not able to as 1 to 10 ⁷⁴.


A comparison of these odds:

The odds of finding a 150 amino acid sequence able to fold into a stable 3D shape is equivalent to finding a single marked atom out of all the atoms in a a billion Milky Ways (that is the galaxy[this is the star system rather than the chocolate bar] rather than the chocolate bar)

These are unpromising odds to say the least.

For a functional protein in a prebiotic soup the odds are considerably worsened.

For a complex of functional proteins occuring at the same time the odds are also considerable worsened.

The odds of a 150 amino acid protein with stable 3D shape in a prebiotic soup is 1 in 10 to 164 this is well below the entire probabalistic resources of the entire history of the entire universe.