Can More Time Make up for Deficiencies in Intelligence?
|April 20, 2005||Posted by William Dembski under Intelligent Design|
Here are three letters from the New Scientist, the first and the last tacitly supporting ID. The last letter raises the interesting question to what degree throwing time at a problem can make up for deficiencies in intelligence. There is a research question here that needs cashing out.
Gods of the gaps
John Athanasiou, Tilbury, Essex, UK
New Scientist, 12 March 2005, page 27.
Your list of ingredients for artificial life — containment, heredity, metabolism and evolution — comes with an extraordinary omission (12 February, p 28). It fails to take into account the painstaking contribution of the research teams. The degree of collective effort by the research teams is directly proportional to the degree of complexity of the task. As the intellectual input increases, the probability of success increases in direct proportion. If the task were simple it would require little or no input for success. This project and others like it demonstrate (scientifically) that probability for biogenesis is highest where intelligent input is greatest. The laboratory pattern – matter coordinated intelligently – affords the only model we actually have upon which we can legitimately (that is, rationally, as opposed to through some freaky leap of faith) base our understanding of how life began on Earth.
Your omission of the contribution of the research teams in the Los Alamos Bug project is modelled on the same omission on a grander scale in the popular belief that life arose spontaneously from inorganic matter. This belief lacks rational foundations and furthermore has no known model to support it.
Give it time
New Scientist, 2 April 2005
John Athanasiou is quite correct that the quality of research input from the Los Alamos team trying to create artificial life will have a big effect on the success of the project (12 March, p 27). However, he fails to explore his thesis fully. If the quality of the research input is very good then the team may have to try a few dozen combinations of chemicals and conditions in a few tens of litres of fluid, and will achieve their goal after a few years of effort. If the quality of the input is not as good then they may need to try several hundred combinations in hundreds of litres of fluid and take several decades. If the quality is lower still then the team may have to pass the challenge on to the next generation of researchers, who may produce life after trying many thousands of combinations and … [The complete article is 301 words long.]
Gordon Ackerman Edinburgh, UK
New Scientist, 16 April 2005, page 29
Erik Foxcroft seems to suggest that there is some sort of linear relationship between
intelligent input to research and other resources and time required to produce a result –
such as artificial life (2 April, p 29).
I think this unfounded. Consider the time taken by, say, an 18-year-old to demonstrate in class a mathematical task such as integration by parts. Say they take 5 minutes. Will a pupil with half the intelligence resources, or half the Ã¢â‚¬Å“research inputÃ¢â‚¬Â or training – say a 13-year-old – take 10 minutes, or even 5 hours? I think it more likely you would never get a clear demonstration of that solution from that pupil, and you would be still less likely to get one if you reduced further to an 8-year-old. It seems that the time would rapidly run off to infinity as the research input was reduced to some required minimum. Paul Davies clearly showed that some quite simple problems are incomputable in the age of the universe (5 March, p 34). Simply throwing bigger times and volumes at some problems is not sufficient.
Following FoxcroftÃ¢â‚¬â„¢s letter, Steve Welch argues against John AthanasiouÃ¢â‚¬â„¢s suggestion of the need for an intelligent input to the origin on life on the ground that it does not show a first cause. No theory does. The concept of the big bang only pushes back the question further as to what caused the initial conditions that could allow it. All theories have initial assumptions. Athanasiou simply argues that his assumptions seem to give him a better explanation of his observations.