Joined: April 2007
gpuccio on the EV ware thread:
Wonderful work! As it is evident from most of the discussions here at UD, demonstrating that algotithms cannot generate CSI remains the main point of ID. While we rely on the work of our theorists (Dembski and Marks) to get ever better theorical demonstrations of that, your practical implementation showing clearly to us non mathematicians what is really at stake is extremely useful. I have often used your weasel ware GUI to help friends who are not familiar with mathematical concepts what is really happening in the different models. The ev ware is another precious tool.
I can’t understand why some people find it difficult to understand the fundamental intuition behind these analysis: these softwares already know the target! They just refrain from giving you immediately the correct answer, because otherwise there would be no game, and give it to you in small pieces. But they know the answer!
The evolutionary process, as it is conceived, does not know the answer. Indeed, it is not even interested in it. Natural selection can only select function, not information. GAs, instead, select information. Their only meaning, in practice, is to sow that: if I already know information, I can select it. What an achievement!
I have always thought that the only true evolutionary simulation should be like that: take a system (a computer) and implement in it simple digital replicators subject to random variation (possibly at an adjustable rate). And then just wait for their “evolution”. We have all that is necessary. One could say: but where is NS? Well, NS is in the same place where it is supposed to be in natural history: it is in the rules of the system and in the rules of the replicator. The replicator has all the chances to become more efficient by random variation and profit of the rules of the system to become something better. So, just wait!
But the moment the programmer, tired of that infinite wait, starts saying: well, let’s help it a bit; after all, we know what we want to achieve.
Well, I suppose that’s exactly what a patient designer has been doing…
“The question is, what is meant by “information” in this context? Information in DNA, for example, if it can be said to exist at all, does not appear to be the same as the information being conveyed in these posts. There is no ‘meaning’ in the sense of that which is intended by a sender or that which is apprehended by a recipient.”
Your question shows probably a lack of familiarity with the ID concepts.
Of course there is meaning in DNA, and that meaning corresponds to the specified information. As you probably know, information in the ID theory means that some result is fixed out of all possible theoretical results (in a system). So, if we are talking of a binary string of 130 bits, for instance, like in the example Atom makes commenting the GUI, any single random string is information with a complexity of 1 : 2^130. That kind of information is only a probability, and has nothing to do with meaning. Indeed, in Shannon’s information theory, meaning is not even an issue. Shannon’s theory is a theory about information in this blind sense, and not about meaning.
On the contrary, specified information corresponds broadly to our intuitive concept of meaning. Specified informations is a subset of all possible information, usually a very small one. “Specified” means all information which has some properties which allow us (intelligent observers” to distinguish that information from a generic random information.
There are many ways that information can be specified (see Dembski). Bit for our purpose, only one is important: functional specification. An information is functionally specified when, in the right context, it can do something which would be impossible without it.
Going back to your example (DNA and these posts): both are examples of functionally specified complex information. These posts are information which, in the context of english language, transmit to the reader some specific knowledge or thought. DNA (the protein coding genes) are information which, in the context of the language of the DNA code, transmit to the translation system the correct functional sequence of a protein.
In both cases the meaning is abstract, and is encoded in a symbolic language. Both cases are examples of a functional message being conveyed through a symbolic language. Both cases are CSI.
Just to show you the similarity. I can use this post to send a message to you, a fellow biologist, saying:
Hey friend, this is the protein whose properties you should study. Just synthesize it and study how it folds. Here is the sequence:
As you can see, I have used this post exactly to do what DNA does; to convey a specific useful information.
I can agree that these posts can convey a grater variety and complexity of meanings, but after all DNA is only a static mass memory, while we are using these posts to communicate in almost real time. But there is CSI, and therefore meaning, in both.
This is just a request for information, in order to uderstand better. Indeed, I don’t know in detail the ev program, so I would like to be sure I understand how it works.
I have tried to read the paper, and i am interested to understand how the selection process works, because I think that is the most relevant point.
|blah, blah, blah [...] blah, blah|
I don't have the slightest clue of what I am talking about.
"[...] the type of information we find in living systems is beyond the creative means of purely material processes [...] Who or what is such an ultimate source of information? [...] from a theistic perspective, such an information source would presumably have to be God."
- William Dembski -