The ID argument appeals to comp sci people like myself because we see an analogy between DNA and computer code. Evolutionary algorithms are pretty bad at generating useful code, even with a whole lot of intelligent guidance, hence our distrust of evolutionary theory claiming to produce even more spectacular outcomes with little to no guidance.
The feedback I usually see is that DNA is not computer code, and it is a false analogy. However, either (1) the whole DNA -> organism process is Turing reducible (thus DNA is computer code), or (2) it is not.
If (1) is true, then well known theorems like the law of information non growth means unguided (and probably guided) evolution cannot generate highly complex organisms through mutating DNA. This is identical to the ID claim that chance + determinism cannot generate CSI.
On the other hand, if (2) is true, then there is some super Turing process at work. This turns out to be identical to the ID claim that intelligence is necessary to generate CSI.
So, when considering the computational nature of DNA we are faced with a dilemma, and either alternative proves ID correct.
Thus, according to the law of disjunction elimination, ID must be correct, regardless of whether DNA is computational or not.
I’m thinking about it carefully, but I am almost entirely certainly #1 is not true because of how you are formulating the problem. I do not think that organisms are Turing reducible, and I am certain that DNA is not because it is not a closed system.
Not true. It is not the same. Look at what I showed you in: Computing the Functional Information in Cancer. This is central to the mathematical and logical error you are making. It was clear enough, and visual too, that several scientists understood and “endorsed” it on that thread. Understand that, and we can make some progress.
No, that is not true.
Just including the full system (which is unobservable large and detailed) might transform into a Turing process. There are processes that are not intelligence, also, that increase intrinsic information (as @PdotdQ@dga471 and I have discussed). In fact, intelligence itself might very well be Turing reducible. This is not escape hatch for you.
You have to demonstrate there is something (1) unambiguously observed in nature, and (2) this cannot arise without intelligence. On both these points CSI fails.
Logic of disjunction is vulnerable to failure of imagination. There is just other options you have not considered. Of course, if the goal is to make ones point, perhaps the failure of imagination is sometimes the design of the argument.
The alternatives are (1) DNA is Turing-reducible, and (2) DNA is not Turing-reducible. Are you arguing that all processes that are not Turing-reducible require intelligence?
I would really like to understand your proof better and the assumption that are required. I believe your conclusion is right here because of the combinatorial mathematical problem that sequences create but I have yet to understand how solid the proof you are advocating is.
@EricMH, I’m curious how you apply your conceptual framework to real biological systems. If the law of information non growth applies to DNA, does it prohibit the creation of any new information at all? We can observe the appearance of thousands of bits of functional information in the DNA within a single living organism. Should that be possible or not?
It seems important to emphasize that DNA sequences are essentially inert with respect to computation. “DNA” here must be a figurative reference to some larger computational system, of which DNA is only one of many artficts that are products and constituents of said system.
As someone who is a retired professor of computer science, I see only a very poor and misleading analogy. DNA is not at all like computer code, and computer code is not at all like DNA.
A computer program codes for actions. The DNA codes for physical components (such as proteins). The computer is an abstract logic machine. A biological organism is neither abstract nor a logic machine.
Well as a PhD in computer science and information theory, who studies biology and writes computer programs all day long, I disagree @colewd. The analogy breaks very quickly. It has a limited role in pedagogy of the basics, but also is far more likely to misguide students than help them.
Have you thought of other analogies that might work better?
No, I think the analogy works great. There are subtle differences but there are always subtle differences in analogies. In what way do you think the analogy is misleading?
It hard to know where to begin. There are far more differences than similarities.
Very important for the proofs being laid out, computer code executed on a computer is an essentially closed system. Turing machines are closed systems. In contrast, organisms are not closed systems.
Computer programs are understandable by humans and created by humans, and are unambiguously interpretable by human created machines. None of this is true for organisms.
Computer programs, when mutated, usually fail catastrophically. Organisms, when mutated, usually do not fail catastrophically.
Computer programs do not reproduce themselves usually, and when they do (like viruses), they do not have any ontegeny in that reproduction. Organisms do usually reproduce, and are defined by an ontogenic process.
Computer programs do not naturally produce variants in the wild and are not subject to selective pressures. Organisms usually do produce variants in the wild, and are subject to selective pressures.
Computer programs are usually required to operate at a very high level of reliability. Organisms operate at a much lower level of reliability.
Computer programs are designed in many ways to have “interchangeable components”, and these components are very frequently interchanged. Organisms are not this way at all, except in some very rare exceptions. We do not see interchangeability of components.
Computer programs are pure information, and separable entirely from their hardware, and usually independent of hardware. The same is not true of organisms at all. We have never seen the information in an organism required to recreate said organism (which is more than just DNA) separated from the hardware itself.
Computer programs use digital logic, but organisms use more analogue logic, even at the level of DNA.
I could go on and on. There are just so many differences. If you start from the “life is just a computer program” conceit, you can be certain you are totally confused about life actually is.
I disagree there is error correction at all levels.
I agree
Mostly agree
I disagree. Organisms require very high reliability to stay alive. We may just not be in sync on what “high reliability means”
I disagree but this is a longer separate discussion.
Interesting point. I need to think about this as analog means an entire wave form is relevant to function vs a digital wave where information is carried in two voltage levels. Instead of two voltage levels DNA information is contained in 4 molecules. Seems closer to digital information to me.
We have complete common ground here yet I still believe the analogy can be very useful in describe code and how it is translated.