{"id":217,"date":"2016-04-30T13:00:25","date_gmt":"2016-04-30T17:00:25","guid":{"rendered":"http:\/\/theappleandthefinch.com\/?p=217"},"modified":"2017-01-12T10:06:08","modified_gmt":"2017-01-12T15:06:08","slug":"shakespeare-evolution-and-weasels","status":"publish","type":"post","link":"http:\/\/theappleandthefinch.com\/2016\/04\/30\/shakespeare-evolution-and-weasels\/","title":{"rendered":"Shakespeare, Evolution, and Weasels"},"content":{"rendered":"

Note: This article contains a number of interactive demonstrations which only work in the later versions of Chrome. \u00a0 They do not yet work in Internet Explorer or Edge.<\/em><\/p><\/blockquote>\n

Monkeys With Typewriters<\/h3>\n

\"\"<\/a>How long would it take for an infinite number of monkeys banging on typewriters to come up with the complete works of Shakespeare? Most of us would probably answer with “never”and dismiss the question as\u00a0one of those rhetorical questions that interest people with too much time on their hands. But suppose we lower the bar somewhat and ask the same question about a single monkey and a single line from a Shakespeare play.<\/p>\n

So let’s start over and ask how long it would take for a roomful of \u00a0monkeys to come up with the line, “Methinks it is like a weasel.” (Hamlet: Act 3, Scene 2)? This seems more manageable, and perhaps more interesting, because we can almost imagine the possibility that monkeys pounding away on typewriters might manage to come up with a particular line of Shakespeare that has only 27 characters (including spaces and punctuation). \u00a0It turns out that if you gave a monkey a typewriter and he managed to stay focused long enough to randomly hit 27 keys, the chances of him producing the weasel passage is 1 in 10^53 (1 followed by 53 zeros). \u00a0 It seems as if a monkey would not live long enough to accomplish this.<\/p>\n

But what is so special about that particular line of Shakespeare? Is the monkey less likely to produce that line than any other string of 27 characters. \u00a0The answer is no, not really. \u00a0Choose any string of 27 characters, such as “uvm(%%$ejis &<\/em>^ mcn..?\/[!}”, and the chances are the same 1 in 10^53 that the monkey will produce that particular string. \u00a0So mathematically, there is nothing special about the weasel passage or any other 27 character string.<\/p>\n

Shakespeare from Space<\/h3>\n

\"awesome<\/a>Intelligent Design proponent William Dembski<\/a> offers a different approach to this. \u00a0He asks us how we would react if we received a signal from deep space that had a phrase like, “Methinks it is like a weasel.”, compared to how we would react if we got some random 27 elements of gibberish. \u00a0In the first case we would be astounded, whereas in the second case we would not be surprised at all. \u00a0 His point is that although either string has the same mathematical probability, the weasel passage is recognizable by a criteria that stands outside of the mathematics. \u00a0It is not only a specific string, but it is specific to human English language. \u00a0It is not only specific but it has a “specification”, which in this case would be “a line of Shakespeare.” \u00a0His opinion is that an unlikely sequence or arrangement of things that can be described by a brief external specification is one sign that the sequence or arrangement is unlikely to arise out of natural random processes or natural laws of nature (repeatedly) , and must be signs of intelligent origin.<\/p>\n

Dembski’s Complex Specified Information<\/h3>\n

A line of Shakespeare, a line of English text of any sort, the carving of a human face, or a sequence of the first 50 prime numbers, are all examples of sequences or arrangements that have an easily identifiable specification. Dembski adds that when a sequence or arrangement of things is both highly complex and readily “specified” as we have just seen, the chances of it occurring without the benefit of guidance by an intelligence is vanishingly small. \u00a0For example, the complete works of Shakespeare is far more complex (has more integrated moving parts to it) than the one weasel passage, and it can be readily specified as “the works of Shakespeare.” \u00a0Dembski has defined this combination of complexity and specification as Complex Specified Information<\/a>, or CSI. \u00a0If the monkeys produced the works of Shakespeare or we received the works of Shakespeare in a signal from deep space, he says we would have to conclude that there was some from of intelligent guidance involved somewhere. \u00a0According to Dembski, a high degree of CSI\u00a0is a “signature” of the involvement of an intelligent agent.<\/p>\n

CSI in DNA<\/h3>\n

Dembski then turns our attention to living creatures and shines his CSI flashlight on the information that we find in the gene sequences of DNA. Genes consist of specific arrangements of four types of amino acids that specify the structure of a specific proteins that the cell should produce for a specific functions. Dembski says that gene sequences are both complex and specified to such a large degree that their arrangements could not have come about through any natural processes. He insists that an intelligence must have guided the formation of the information in DNA.<\/p>\n

He asks how a process like evolution that uses chance mutations that is as random as monkeys with typewriters could produce such complex information that specifies something as nuanced and functional as the human eye, for example. The usual answer from biology is \u00a0natural selection. \u00a0But for some that answer is not very satisfying since all it does is eliminate information. If natural selection is the “survival of the fittest”, how can a random process bring about the “arrival of the fittest”? \u00a0Or using the monkeys analogy, how could simply selecting out and discarding the pages that are not scenes from Shakespeare ever help the monkeys produce anything but gibberish?<\/p>\n

Dawkins’ Weasels and CSI<\/h3>\n

\"weasel\"<\/a>Way back in the days of the Apple II, evolutionary biologist Richard Dawkins wrote a simple computer program to demonstrate how random mutation and natural selection (RM + NS) could produce complex specified information. \u00a0His program is often called the Weasel Program<\/a> because the goal of the program was to use random mutation and selection to generate the line from Hamlet, “Methinks it looks like a weasel.” \u00a0WEASEL works as follows:<\/p>\n

 <\/p>\n

    \n
  1. Generate a string of random characters and call it the Parent String.<\/li>\n
  2. Make 1000 copies of the Parent String and call them the Children Strings.<\/li>\n
  3. Go through each of the child strings one by one and make a small number of random mutations. \u00a0The mutations happen at random places in the string. \u00a0They can add or substitute a character for another randomly chosen character. \u00a0Or they can simply delete a character.<\/li>\n
  4. Compare each child string to the target string, “Methinks it is like a weasel.”<\/li>\n
  5. Select the child string whose mutations have brought it closer to being like the target string.<\/li>\n
  6. Declare the selected child string to be the new Parent String.<\/li>\n
  7. Repeat steps \u00a02 through 7 using the new Parent String.<\/li>\n<\/ol>\n

     <\/p>\n

    The important things to keep in mind is that the mutations that occur in step 3 happen randomly with no foresight about the target string about weasels. \u00a0After that step is complete, each child string is still very much like its Parent String, but each has a few of its own particular random variations. The selection process for choosing the “fittest” child string happens without knowing how the child strings were produced. \u00a0It simply selects from what it is given by comparing them with the target.<\/p>\n

    Since you have had the persistence to get this far, your reward is a demonstration of Dawkins Weasels right here in your very own browser. In the demo window below, you may enter a target string of your own or leave it as it is. \u00a0Press Reset, then press Run. \u00a0The program will cycle through a number of generations to evolve the initial random string into the target string (each generation is numbered to the right of its fittest string.) \u00a0When it has found its weasel, you can hit the Stop button or let it run for a while to see what happens (nothing happens).<\/p>\n

    Scenario 1: Dawkins’ Weasels<\/h3>\n

    %CODE1%<\/p>\n

    Notice that for a string about the size of the weasel passage it achieves its goal in somewhere between 30 and 60 generations. Pretty good for such a simpleminded process. But how did it get to its goal so fast when we already established that no amount of monkeys could do the same thing in their lifetime? Does the weasel program cheat? The answer is yes, but it “cheats” in the way that evolution cheats. \u00a0The secret is that there is a step in the weasel scenario that is not in the monkey scenario. \u00a0That would be step 6, where each “best” child becomes the parent of the next generation, allowing the next generation to start with a better string than the last one. \u00a0That way, the string for each new parent rachets towards the goal with small but relentless steps.<\/p>\n

    Weasels Cheat at Poker<\/h3>\n

    \"weasels_with_flowers_background_card_decks-rc9c83bc88aa04d21864f6d98d27729cb_zaeo3_324\"<\/a>In biology, this is called Inheritance. \u00a0 It cheats like you would be cheating if you kept the best cards in your pretty good poker hand for use in the next game, improving on the hand each game through discards and the random replacement cards from the top of the deck. In only a few games you could build yourself a\u00a0Royal Flush.<\/p>\n

    WEASEL is dramatic in that such a mindlessly simple program running on an Apple II demonstrates that a random process followed by a selection process can generate CSI repeatedly. \u00a0However, Dawkins’ critics in the Intelligent Design movement raised a number of objections claiming that the program cheats in other ways that are not found the process proposed by the theory of evolution. \u00a0Most of the objections were inconsequential, but one is interesting enough to spend some time on since it gets to the heart of another question that Intelligent Design proponents ask, which is “How can a process unguided by intelligence produce information?”.<\/p>\n

    Are Dawkin’s Weasels Guided?<\/h3>\n

    The complaint is that the WEASEL program has the actual target string built into it. \u00a0In other words, the information that the program is supposed to be generating through RM + NS, is already built into the program. \u00a0As such, it does not answer the question about how information can be generated by an “unguided” process such as evolution. \u00a0The first answer to this objection is that the program is carefully written so that the process that produces mutated children from the parent works in complete isolation from the process that evaluates each child in respect to the target string. \u00a0In other words there is an information barrier such that information only flows out of the genes of the children but never flowing in from the outside world.<\/p>\n

    Imagine two black boxes: a Copy Box and a Selector Box. \u00a0You place a weasel in the Copy Box, a bell rings, and you take out the 1000 children it has produced (all with slight random variations). \u00a0You place the 1000 children in the Selector Box which selects one child weasel and disposes of all the\u00a0others. \u00a0You take out the selected child weasel and put it into the Copy Box. \u00a0Rinse and repeat.<\/p>\n

    The Copy Box doesn’t know or care what criteria \u00a0the Selector Box used to select the one child weasel because the important point is that there is no information about that criteria flowing from Selector Box to the Copy Box. \u00a0The child producing process in the Copy Box is not informed by any information from the outside world. \u00a0It simply waits for someone to give it a weasel and then proceeds to make 1000 copies of that weasel. \u00a0But since the Copy Box is not perfect, the copies are not exact replicas of the original weasel. \u00a0They have a small number of random variations in their weasel strings. \u00a0The process that produces the variations is no more guided than the bounces of a well made pair of dice thrown against a wall.<\/p>\n

    Introducing Steiner Weasels<\/h2>\n

    So what happens if we model the same process with a computer program that does not have the target built into it? \u00a0Is that possible, and will it be able to produce CSI? \u00a0If CSI is defined as information that can be seen to have a separate specification, how can a simple computer program generate that kind of information if it does not already contain the specification?<\/p>\n

    Having got this far, please be entertained for a moment by running the next demo Scenario 1 below. \u00a0Hit Reset, then Run. \u00a0 After it seems to have settled down, hit Stop and read the explanation below it.<\/p>\n

    Scenario #1: Weasels Find Some Food Sources<\/h3>\n
    %CODE2%<\/div>\n