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.