I apologize for not getting right to the point. I can’t. Everybody’s premises are wrong, and it requires work to set them right. I also apologize if you get this twice. Substack had this in its scheduler, but didn’t send it; it says it there, but I can’t access it, so I’m creating the post anew.
I think the young people enjoy it when I “get down” verbally, don’t you? Which is why pop-culture references are never amiss. So let me ask you: seen Wargames?
There’s a scene at the end where a computer named Joshua is about to destroy the world by launching the USA’s nukes, but it can’t until it has figured out the “launch code”, which happens to be “JPE 1704 TKS”. Dabney Coleman announces the computer “is sending random numbers to the silos”. Some woman said the computer’s guessing will “hit the launch code in 5.3 minutes.”
A screen is shown flashing a sequence of 10 letters and numbers, the two spaces being ignored. Suddenly, the “4” position stops moving and glows “4”. The good-evil doctor who built the computer says the computer has figured out the 4 and when it gets the rest, Doomsday. Drama occurs as the hero tries tricking the computer into playing a game. As that happens, more and more digits are fixed.
The movies ends with the computer getting the code and launching The Science into the air, killing everybody.
Forget that and let me ask you, and pay strict attention, what is the probability of guessing a launch code “randomly”? Stick with me on this. It matters to “evolution”.
If you have taken my Class, and assimilated everything I have taught you, you know the answer instantly. If you have not taken the Class, or not assimilated its lessons, you will begin to calculate. As a neo-Darwinian would. Which is why they make so many mistakes.
The answer is: there is no probability.
Nothing has a probability. I told you that was the One Central Lesson of the entire Class, and that if you learned it, you have learned most of what you need to know.
Probability is a measure, sometimes quantitative, of how certain a proposition is, given evidence that is assumed true. Probability is in your mind, and not in the world. Your intellect is not material, and neither is probability.
So if I ask you what is the probability of guessing a launch code, the launch code becomes the proposition. But what is the evidence? The possibility of the launch code being a number? An integer number? Who says? How do you know? Are you making this stuff up?
If it is an integer, then the probability is 0, since there an infinity of integers. What if it’s an alpha-numeric number? Still 0, since there just as many countably infinite alpha-numeric as numeric numbers.
What if we restrict it to ten digits? Then we are getting somewhere. Harder to do, though, and maybe impossible, because there is no single alphabet. How do you it’s only ten digits, and how do you know it’s only Latin upper case letters? Who told you? I said “launch code”, I didn’t say Joshua’s code. Could be any code.
If we do know it’s ten digits, plus our English upper-case alphabet, then the probability of guessing correctly is 1 in 36^10≈3.66×10^15. If Joshua could guess every number in this set, and do this in 5.3 minutes, it would run at a speed of about 1.15×10^13 numbers a second. This is possible given computers these days.
Computer launch codes do not work like in the movie anyway. They are not like tumbler locks, where it is possible in some locks to get one digit at a time until you get them all. Computer codes are all-or-nothing. You either get all ten digits right at once, or it doesn’t work. And you have to know it’s ten, and you have to know the set of possible digits. Nine won’t do it, and anyway you won’t know if you have nine right. Or any number right. It’s right or wrong for every possible combination, and that’s it.
Now some time ago people asked me to look at Vox Day’s critiques of neo-Darwinian “random” mutations. I finally had time. I agree with his conclusion, that evolution by accumulation of small “random” mutations is absurd, but I’m not wholly with him on all of his argument.
The fixation rate in a population genetics context refers to the frequency at which a particular mutation becomes present in every individual of a population, effectively replacing all other versions of that gene. Let’s break down the concept of fixation rate using a simplified example…
Step 2: Determine Fixation Probability
For a beneficial mutation, the fixation probability can be higher than that of a neutral mutation. If we assume this mutation offers a slight survival advantage, let’s denote the selection coefficient by ?s, where ?s is small, say 0.01 (1%).
The fixation probability (P) for beneficial mutations can be approximated using the formula:
Let me ask you this: what is an (any) organism’s fixation probability?
Then let me ask you this: what is an (any) organism’s fixation rate?
Your answers should and must be: there isn’t one, and there isn’t one. Nothing has a probability, and nothing has a rate.
What you can do is go back and measure, in this or that species, how fast a certain mutation spreads in individuals from a sample of the population. Its “progress” can be tracked, the scare quotes to remind us most mutations are not beneficial. That average measure may be said to be its observed-rate: one word, not two. That’s the change you saw in your sample.
Listen: the observed-rate does not cause the spread. No organism has a rate of mutation that can be a cause.
Mutations are passed on, sexually or asexually, the causes of which vary and are conditional on the environment and other circumstances, and this variation is at the individual, not species level. You know this already, but saying species have rates is a mistake. Mutation spread has causes and conditions, which may be modeled by rates.
The model is not Reality. To think so is to commit the Deadly Sin of Reification.
It is the same with probability. That equation Day has, or anybody has, is a model of our thoughts, it is a model of how the uncertainty in a thing changes with correlates of causes, here N for “population size”, and s for “selection advantage”. That latter term also does not exist. It is itself a model, put into another model, the probability. That probability is a model of a model.
It does not mean it is not a useful model. But, as I never tire reminding you, all models only say what they are told to say. These do, too. Which means you can’t back cause out of them. Correlates of causes, and the conditions which allow the causes to be exercised, are put into models.
This means the models used by neo-Darwinian “randomists”, and models used by Day, have only limited appeal, as crude predictions after assuming causes of speciation. They are not proof of cause.
The real reason neo-Darwinian randomists are wrong is because they are bluffing. Remember what random means: unpredictable, or unknown cause. You cannot simultaneously claim to know the causes of evolution while claiming those causes are unknown! If you really want to hear them bluff, ask them to explain biogenesis. The Big Muscles Fallacy is in wide use: this is when an intelligent person says “Because I, even I, cannot think of another reason, my reason must be correct.”
It is known how some (very few) mutations are caused, and these can be tracked, sometimes. That small mutations build up and “suddenly” a new species emerges after a long time accumulating single mutations is, however, an unconfirmed guess. Incomplete, too, since there is no direct objective measure which says “After N genes change, the progeny is a new species”. And we don’t even know how all genes work together (as we’ll see in a moment) to create an organism. Worst of all, the slow accumulation guess does accord with Reality, in which new species appear, or seem to appear, almost at once.
The reductionist mindset—reductionism in science was at first fruitful but is becoming a mind-block—of randomists is wrong. Their direction of cause is backwards. They envision tinker toys (genes) being put together in various configurations, with genes themselves tinkering the toys. None of this is coherent, as Day (and many others like David Stove, David Berlinski, Stephen Meyer, and so and on) point out.
Genes don’t act, organisms do. This is becoming more obvious, hence epigenetics, that which is above reductionist tinker toy control. There are only a handful of genes that can be said to be specifically and uniquely for something. We learned this recently in “Limitations Of Biological Determinism: Ideas In Our Reenchantment & Rectification” (blog/Substack). Genes are part of an organism like hydrogen and oxygen are part of water. Which is to say, they are no longer in water; their combination is water. They do not act as single atoms, doing their thing and interacting; they become something new, their individual characters vanish, though extracting them and using them as models may have certain uses. When oxygen and hydrogen join only water remains. The oxygen or hydrogen do not, and cannot, cause the water to act. As Gibbs said (and amplified so beautifully by Jaynes) “The whole is simpler than the sum of its parts.”
It is the same with genes. This is the lesson Denis Noble has been trying to teach people, most recently in his book Dance to the Tune of Life. Which we will review shortly and in depth (he uses the water example to great effect). But for those who want some fun, here he is schooling his old pupil, Ricard Dawkins, who holds with reductionist “selfish genes”.
Change must occur more like how the computer acted in War Games. If “JPE 1704 TKS” is the destination (a new species, say), then metaphorically it can get the “4” right first. Then another of the other digits, and so on, sometimes more than one digit at a time. In a simple model to explain the difference, we saw above that guessing 10-digits code to try to unlock the launching of a new species, there were about 3.66×10^15 possibilities. A large number. But in our model, only a maximum of 36 guesses need to be tried for the first digit, and the same for all ten digits, meaning there are at most only 360 possibilities. This is ten trillion times easier!
I don’t mean this literally, but as a sort of comic guide: it is only a weak analogy. Because if it were that easy to get new species, we’d see them being created all the time. We do not, and, as far as I know, have never. No, something much deeper and more interesting is happening than “random” change.
Scientists would be more open to these ideas if they didn’t start hyperventilating every time somebody criticized evolutionary theory on the hersterical fear that Christianity will sneak back into science. Well I got news for you, pal, it never left (blog).
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You demonstrate the difference between knowledge and understanding. Thank you and bless you.
“No, something much deeper and more interesting is happening than “random” change.”
Oh yes, it’s a quantum phenomenon, which, you see, instantly explains everything.