Creation of information
Posted: Sun Oct 20, 2019 12:51 am
In a video https://www.youtube.com/watch?v=Y6j8Yp6s6E8 Behe discusses the behaviour of Darwinian evolution, and he says that observed beneficial mutations do not involve adding information to DNA, instead observed beneficial mutations involve some replacements but mostly deletions. Which speaks to the inability of "random" mutation to add new information to life.
This is repeated again and again in the videos by ID proponent, for instance Meyer: “If you try to explain an event in the remote past, you want to draw on the knowledge of cause and effect. If the effect is a lot of new information, we know the cause that can do that and it’s the mind or the intelligence.” https://www.youtube.com/watch?v=FDSpLBNQk5I 0:02 – 0:12.
Also he repeats this in https://www.youtube.com/watch?v=7c9PaZzsqEg
What is assumed is that intelligence is needed to create new information and hence that a natural process of mutations and selections (evolution) can’t produce new information. I think this is wrong and will try to show why.
Let’s look at a simple labyrinth with four forking paths. If you want to find the midpoint you may have to go to the left, to the right, to the right again and then to the left. Let’s denote this LRRL. If I stroll around in the labyrinth I will find out the best way LRRL, and if I want to tell you how to go to the middle I tell you go LRRL. I have found the information about the best way and have informed you about it and the information is precisely “LRRL”, assuming you know the context. If a rat explores the labyrinth it will soon learn LRRL and will remember that piece of information in the future. Rats are good at that.
If you represent the labyrinth in a format that is computer readable you can write a program that finds out the optimal way. For instance if the labyrinth is drawn on a squared paper then data how the squares are connected to each other is sufficient for a simple program, perhaps less than 30 lines of code. So if I feed the computer with data about my labyrinth it will very quickly find out the best way, LRRL. If I feed the computer with other labyrinths it will find the optimal paths in those cases also. (I assume that all labyrinths fit some requirements put by the programmer to keep the program simple. Perhaps not too big, being two dimensional, no loops). Those optimal paths is new information created by the program, new for each labyrinth. Some would argue that the information was put there by the programmer. This is wrong for two reasons. First, the programmers only knew the basic features of the labyrinths but they had no idea about the actual labyrinths so the information that the program supplied to them about the optimal paths was new also to them. Secondly, if the labyrinth is big enough, perhaps more than 20 times 20 squares the possible variants of the labyrinth are so many that there is more information in a single labyrinth than in the whole program.
The idea that programs can create information or knowledge is used extensively in different research areas. One example is network theory where for instance internet traffic over a complicated network is simulated. In those cases the program is rather straight forward. It simulates traffic generation (sending of messages) at the end points and checks what happens in a simulated network, looking for instance for congestion and evaluating delays. In that way an experimenter can use the program to find out for instance the optimal configurations of the network, given the type of traffic. He or she gets new information from the program; information about the reality of networks that perhaps is not known before. More advanced programs use so called genetic or evolutionary code that mimics biological evolution. They generate a lot of copies of a simple solution to a problem, insert mutations i.e. changes in the solution, use an evaluation algorithm to find the best changes and discarding the bad one. Then they start a new session generating copies, inserting mutations, evaluation and discarding bad solution. If this is repeated a great number of times new information may be generated, information that would be impossible to find in other ways. This is a powerful but expensive method and requires months or years of computer time.
If new information can be created by computers there is no reason why it couldn’t be created by biological evolution and this is precisely what the evolution theory assumes. Information isn’t created by intelligences alone.
Note that when Meyer discusses genetic programs he compares the RNA's genetic code with program code and that is a confusion. The equivalence in biology to the program code is our environment and the physical laws. The equivalence to the genetic code is the instruction LRRL (the labyrinth example) . The genetic code is instructions to for instance proteins to build biological structures and the labyrinth code LRRL is an instruction for a person or machine how to find the labyrinth centre. In https://www.youtube.com/watch?v=7c9PaZzsqE about at 3:30 he erroneous compares the program code with the genetic code.
Nils
This is repeated again and again in the videos by ID proponent, for instance Meyer: “If you try to explain an event in the remote past, you want to draw on the knowledge of cause and effect. If the effect is a lot of new information, we know the cause that can do that and it’s the mind or the intelligence.” https://www.youtube.com/watch?v=FDSpLBNQk5I 0:02 – 0:12.
Also he repeats this in https://www.youtube.com/watch?v=7c9PaZzsqEg
What is assumed is that intelligence is needed to create new information and hence that a natural process of mutations and selections (evolution) can’t produce new information. I think this is wrong and will try to show why.
Let’s look at a simple labyrinth with four forking paths. If you want to find the midpoint you may have to go to the left, to the right, to the right again and then to the left. Let’s denote this LRRL. If I stroll around in the labyrinth I will find out the best way LRRL, and if I want to tell you how to go to the middle I tell you go LRRL. I have found the information about the best way and have informed you about it and the information is precisely “LRRL”, assuming you know the context. If a rat explores the labyrinth it will soon learn LRRL and will remember that piece of information in the future. Rats are good at that.
If you represent the labyrinth in a format that is computer readable you can write a program that finds out the optimal way. For instance if the labyrinth is drawn on a squared paper then data how the squares are connected to each other is sufficient for a simple program, perhaps less than 30 lines of code. So if I feed the computer with data about my labyrinth it will very quickly find out the best way, LRRL. If I feed the computer with other labyrinths it will find the optimal paths in those cases also. (I assume that all labyrinths fit some requirements put by the programmer to keep the program simple. Perhaps not too big, being two dimensional, no loops). Those optimal paths is new information created by the program, new for each labyrinth. Some would argue that the information was put there by the programmer. This is wrong for two reasons. First, the programmers only knew the basic features of the labyrinths but they had no idea about the actual labyrinths so the information that the program supplied to them about the optimal paths was new also to them. Secondly, if the labyrinth is big enough, perhaps more than 20 times 20 squares the possible variants of the labyrinth are so many that there is more information in a single labyrinth than in the whole program.
The idea that programs can create information or knowledge is used extensively in different research areas. One example is network theory where for instance internet traffic over a complicated network is simulated. In those cases the program is rather straight forward. It simulates traffic generation (sending of messages) at the end points and checks what happens in a simulated network, looking for instance for congestion and evaluating delays. In that way an experimenter can use the program to find out for instance the optimal configurations of the network, given the type of traffic. He or she gets new information from the program; information about the reality of networks that perhaps is not known before. More advanced programs use so called genetic or evolutionary code that mimics biological evolution. They generate a lot of copies of a simple solution to a problem, insert mutations i.e. changes in the solution, use an evaluation algorithm to find the best changes and discarding the bad one. Then they start a new session generating copies, inserting mutations, evaluation and discarding bad solution. If this is repeated a great number of times new information may be generated, information that would be impossible to find in other ways. This is a powerful but expensive method and requires months or years of computer time.
If new information can be created by computers there is no reason why it couldn’t be created by biological evolution and this is precisely what the evolution theory assumes. Information isn’t created by intelligences alone.
Note that when Meyer discusses genetic programs he compares the RNA's genetic code with program code and that is a confusion. The equivalence in biology to the program code is our environment and the physical laws. The equivalence to the genetic code is the instruction LRRL (the labyrinth example) . The genetic code is instructions to for instance proteins to build biological structures and the labyrinth code LRRL is an instruction for a person or machine how to find the labyrinth centre. In https://www.youtube.com/watch?v=7c9PaZzsqE about at 3:30 he erroneous compares the program code with the genetic code.
Nils