Hi Dr. Miller,
I’d like to thank you for commenting on this thread. Re semantic information: the distinction between syntax and semantics is a vital one in linguistics. The sentences “Cows flow supremely” and “Cheetahs run swiftly” both conform to the rules of English syntax, but only the second sentence has a semantic meaning. What parallel distinction can you adduce in the field of biochemistry?
I’d now like to address a few of your comments.
…[A] small fraction [of amino acid sequences] form into a stable enzyme which drives some essential reaction for a cell. Sequences which perform such functions are considered by many experts in the field to have semantic information…
The most important points of similarity between letters in a sentence and protein sequences are the rarity and the connection to something external.
The rarity of protein sequences is better compared with the rules of syntax, rather than semantic meaning. Only a very small proportion of word sequences conform to the rules of English syntax (“Cows flow supremely” does, but “Wanted the about” does not). This does not guarantee, however, that these sequences of words possess semantic meaning.
A protein sequence, taken as a whole, does bear a connection to something external, but in a meaningful English sentence, not only the sentence as a whole, but also the individual words, have to bear a connection to something external. Sentences are about some state of affairs, but the words that make up these sentences possess their own “aboutness.” I see no analogue to this two-level “aboutness” in proteins. Nor do I see any analogue to the rules of English grammar.
While I’m at it, I’d like to highlight another significant difference between protein sequences and human language:
Human language is unique in comparison to other forms of communication, such as those used by non-human animals. Communication systems used by other animals such as bees or apes are closed systems that consist of a finite, usually very limited, number of possible ideas that can be expressed. In contrast, human language is open-ended and productive, meaning that it allows humans to produce a vast range of utterances from a finite set of elements, and to create new words and sentences. This is possible because human language is based on a dual code, in which a finite number of elements which are meaningless in themselves (e.g. sounds, letters or gestures) can be combined to form an infinite number of larger units of meaning (words and sentences). [Wikipedia article: Language]
Let’s move on.
The fact that protein sequences operate hierarchically in life – amino acids form proteins which form metabolic reaction sequences which form a functional cellular metabolism – highlights the probabilistic challenge.
I see what you’re getting at, but if you’re going to talk about a probabilistic challenge that points to intelligent design, then you need to quantify it. There must be some very small probability p which places an event beyond the reach of chance. What’s your cut-off point? As I mentioned above, Dryden, Thomson & White argue that up to 4×10^43 different amino acid sequences could have been explored since the origin of life. Additionally, there are thought to be 10^24 planets in the universe. Not all of these will support life, but it seems to me that if you want to err on the safe side, you need to allow for about 10^65 amino acid sequences that might have been explored in the history of the cosmos. So, how rare are proteins? I used to believe Dr. Axe’s figure of 1 in 10^77 for the rarity of protein sequences, but after reading articles like this one over at The Skeptical Zone, I am no longer able to take such a figure seriously. See also my review of Axe’s book, Undeniable, and scroll down to the section, “The odds against building a 150-amino-acid protein by chance,” for further arguments against Dr. Axe’s estimate.
Now it’s true, as Dr. Meyer points out in Signature in the Cell, that even the simplest modern-day living organisms need around 250 kinds of proteins in order to survive. But it would be a mathematical fallacy to argue that even if Dr. Axe’s estimate is wrong and the odds of a functional protein sequence are (say) 1 in 10^12, the odds of getting 250 proteins is 1 in (10^12)^250, or 1 in 10^300, which is well below the threshold of 1 in 10^65. I’m sure you don’t need me to point out why.
The heart and soul of all this is the information contained in the protein mold. There is a nook in that mold for every piece and enough information passes hand for three functions: (1) the recognition of each piece, (2) the optimal positioning of the pieces relative to one another, and (3) the weakening or splitting of certain bonds in the pieces or the making of new bonds for welding the pieces together. [Loewenstein]
This doesn’t sound anything like semantics to me. It sounds more like putting Lego pieces together. Comparing it to semantic meaning is unhelpful at best and misleading at worst.
The fact that such information carries meaning, implications about something other than its own instantiation, places it in a unique category, which we might call semantic information, and its existence raises many deep and important questions and considerations… [Grisogno]
As we have seen, “aboutness” is not sufficient to warrant a comparison to semantic meaning. It has to be multi-layered.
I’d also like to point out that Grisogno contends that what she refers to as the “semantic information” of life could have evolved by natural processes. For example, on page 93, she discusses the origin of the “semantic information” in the form of coded replication:
Increasing evolvability and specificity seem to play a part. As more efficient catalysts evolved, they also became more specific, since the closer a catalyst’s fit to one set of reactants, the less it would fit alternate reactants with slightly different properties. A set of highly specific catalysts that vastly accelerate a particular process and have little effect on others lays a foundation for the transition from analogue to digital processing, and for the emergence of complex control structures and for the kind of self-organised criticality behaviour (Adami, 1995; Halley and Winkler, 2008) that seems to be required for autonomous choice.
Note that Grisigno talks about structures in the passage above - in other words, functional information, rather than truly semantic information. Grisogno goes on to express her confidence that “billions of years and massively parallel searches in possibility space” could account for the origin of the “extraordinarily complex processes we see today” (p. 94).
Dr. Miller, you appear to be arguing that semantic information is (i) found in life and (ii) only generated by a mind. The sources you cite who agree with you on (i) also make it quite clear that they do not accept (ii).
Over to you.