A Weasel Implementation

Telic Thoughts commenter computerist wrote this in the linked comment:

Since there is much talk about weasel (plus JAD's request) I thought I'm probably missing out on all the hype and fun so to pass up on the opportunity to code a weasel implementation would be like a kid passing up the opportunity to bag candy during halloween.

Here is the external link (since I'm unable to syntax highlight/format on TT's) to the C code for anyone who is interested:

http://computerist29.wordpress.com/

Just compile and run!

In a follow-up comment computerist wrote:

To add to my previous comment, I'm not pretending the program what Dawkins or Dawkins-fans says it should do, its a very simple latching implementation, I'm sure Dawkins-fans out there have more "realistic" implementations. Weasel type algorithms show nothing except that it takes intelligence to select potential pre-function to reach functional "targets" from the onset and that these algorithms take advantage of intelligently designed computers. If you find a weasel program/algorithm that doesn't run on top of a intelligently designed system please give me a shout. If weasel simulates evolution in any way it should also be true that the same algorithm applies to explain all the pre-existing hardware and software its running on top of.

As Dembski and Marks might put it Dawkins had to front load problem-specific information to facilitate successful searches. That in turn indicates that far from being blind, the watchmaker had 20/20 vision.

Glycine Found in Comet Particles

The Los Angeles Times article Ingredient for life detected in comet dust mentions the finding of the amino acid glycine in comet material. Glycine is the simplest of the 20 standard amino acids found in living organisms. The article quotes a research scientist as mentioning the possibility that life was seeded on earth by cosmic material. This is not a new theory for previous findings of biochemical building blocks were discovered in meteorites.

This type of evidence for the origin of life falls within a building block rubric which is characteristic of OOL research. Different types of biomolecules are found in different conditions and theories are woven as to how more complex molecules and biological systems developed from these initial meager starts. Some amino acids here, some there. Some nucleotides here, other types there. Enclose them within lipid chains, add some enzymes, hope for some replication and whala, whala, we're on our way.

The last few sentences of the article are telling:

Just having the right materials is no guarantee that life will begin, of course, any more than leaving a hammer, nails and planks lying around will cause a barn to rise. Brownlee pointed out that many of the 30,000 or so meteorites that have been found on Earth bear traces of organic compounds, and there also is evidence that they were once warm and wet, all necessary conditions for life. Yet none of the meteorites has shown any evidence of life forms.

"They are all failed places where life could have arisen," Brownlee said.

The universe is one big lab and the real evidence for life arising in lifeless environments is paltry to put it kindly.

HT: Clare

More About Measuring the Cost of Success

Continuing with William A. Dembski, and Robert J. Marks II and their paper Measuring the Cost of Success. Quoting from the remainder of the abstract:

We propose three measures to characterize the information required for successful search: 1) endogenous information, which measures the difficulty of finding a target using random search; 2) exogenous information, which measures the difficulty that remains in finding a target once a search takes advantage of problem-specific information; and 3) active information, which, as the difference between endogenous and exogenous information, measures the contribution of problem-specific information for successfully finding a target. This paper develops a methodology based on these information measures to gauge the effectiveness with which problem-specific information facilitates successful search. It then applies this methodology to various search tools widely used in evolutionary search.

Three different information measures are defined and we are told the paper develops a methodology based on them "to gauge the effectiveness with which problem-specific information facilitates successful search." This could make possible a distinction between a "blind watchmaker" and a process evidencing foresight front loaded into it.

About Measuring the Cost of Success

William A. Dembski, and Robert J. Marks II authored the paper Measuring the Cost of Success. Quoting from the abstract:

Abstract—Conservation of information theorems indicate that any search algorithm performs, on average, as well as random search without replacement unless it takes advantage of problem-specific information about the search target or the search-space structure. Combinatorics shows that even a moderately sized search requires problem-specific information to be successful. Computers, despite their speed in performing queries, are completely inadequate for resolving even moderately sized search problems without accurate information to guide them.

The subject matter is relevant to origin of life and evolutionary scenarios since both must account for the development of information systems in biological organisms. Search algorithms should accurately model biological processes. If genetic changes are random with respect to the reproductive fitness of a self-replicator, then how would a moderately sized search for a target enhancing reproductive fitness succeed without front loading the search with the problem-specific information needed to locate the target?

Counterarguments to Behe's irreducible complexity concept have suggested specific intermediate evolutionary structures and functions en route to the evolution of the systems Behe cited. This paper of Dembski and Marks appears applicable to those types of scenarios. Behe's search target is specified and precursor biological systems nominated as plausible candidates by Behe's critics.

Curious Behavior of NAs

TT commenter John A. Designer wrote the following comment:

The thing I like about Ruse is that he believes in using persuasion in his arguments rather than coercion. Persuasion means finding common ground, using good logic and reason to craft and refine your arguments. The so called new atheists, on the other hand, aren’t interested in finding common ground or making carefully reasoned arguments. Their main weapons in public discourse are stereotypes and ridicule. But, as David Heddle pointed out on another thread they are doing little more than preaching to their own choir.

So I wonder is that how these people became atheists? They were subjected to so much ridicule that they eventually saw the true enlightened answer? Does ridicule ever work?

Of course, the problem with persuasion is that it is hard rather than easy. It means that you have to actually think about what you say and believe and listen to the other side.

Motives for unpersuasive tactics are curious. Surely hostility is part of this. Simple venting explains much New Atheist behavior. Listening to the other side and hostility tend to be mutually exclusive.

Material Reduction of Intelligence

In the signatures of minds thread commenter Rock wrote:

Most people when asked what is “intelligence,” including most scientists who investigate intelligence, will tick off a short list of skills, abilities, or attributes that they consider intelligent. You don’t have to see many of these list to realize there is a definite pattern, a “Basic Skills Set” “defining” intelligence, in the common conception. Operationalizing these skills involves further decomposition into mechanical actions or operations, materially reproducible, as is always required by science. That’s mostly what AI researchers do.

Based on this comment this looks like a pattern:

Intelligence (manifested by skills)--> Mechanical actions or operations--> Material or physical evidence

Guest Posts

aiguy, a Telic Thoughts commenter with expertise on artificial intelligence, is interested in submitting a guest post to TT. If you are out there aiguy kindly forward your proposal to Nathan Munson. I'll get hold of it and after reviewing it will post it at the site.

Commonly Employed Arguments Against ID

Uncommon Descent has a web page devoted to frequently cited but weak arguments against Intelligent Design. Anyone involved in these debates for very long will recognize some of the arguments. The topic 27] The Information in Complex Specified Information (CSI) Cannot Be Quantified is appropriate for a blog identified to a great extent with William Dembski.

39] ID is Nothing More Than a “God of the Gaps” Hypothesis may be the most common anti-ID argument. This from the link:

ID is not proposing “God” to paper over a gap in current scientific explanation. Instead ID theorists start from empirically observed, reliable, known facts and generally accepted principles of scientific reasoning:

(a) Intelligent designers exist and act in the world.

(b) When they do so, as a rule, they leave reliable signs of such intelligent action behind.

(c) Indeed, for many of the signs in question such as CSI and IC, intelligent agents are the only observed cause of such effects, and chance + necessity (the alternative) is not a plausible source, because the islands of function are far too sparse in the space of possible relevant configurations.

(d) On the general principle of science, that “like causes like,” we are therefore entitled to infer from sign to the signified: intelligent action.

(e) This conclusion is, of course, subject to falsification if it can be shown that undirected chance + mechanical forces do give rise to CSI or IC. Thus, ID is falsifiable in principle but well supported in fact.