In previous articles, I demonstrated how substantial quantities of biological information cannot emerge through any natural process (see here and here), and I described how such information unambiguously points to intelligent design. Now, in posts today through Friday, I will address the mistakes typically made by critics who challenge these claims (see here, here, here, and here). Nearly always, the errors fall into three categories:
- Misapplying information theory.
- Misinterpreting research related to protein rarity.
- Misunderstanding the creative potential of evolutionary processes.
The Nature of Biological Information
We first note that, from a thermodynamics perspective, living cells are dynamic, open systems that continually exchange energy, entropy, and information with their surrounding environment…Thus there is plenty of opportunity for information to be transformed from one variable to another, from various physical states to useful information-bearing variables. Information in a cell is not conserved, just as entropy is not conserved in an open system.
His analysis reveals a common confusion between what is termed the Shannon measure of information and semantic information (more generally, specified complexity).
The former relates to the information needed to define a specific state in a system such as the positions and momenta of the molecules in a gas. The latter relates to the amount of meaningful information in some medium. The claim that “information” can exchange with the environment confuses these two categories. To illustrate, a sequence of Scrabble letters could spell out the first act of Shakespeare’s Macbeth. And, the tiles could constantly interact thermodynamically with the environment by absorbing and releasing heat. Yet a sudden change in the temperature of the surrounding air would never cause additional tiles to arrange themselves so as to spell out the first line of the play’s second act. Semantic information can never be appreciably increased by undirected physical processes.
The Genetic Code
Another common error is denying that the genetic code represents an abstract symbolic system. The same author cited above levied the following criticism against Stephen Meyer:
One possibility that could relate intelligent agents to a subset of CSI [complex specified information] is abstract symbolism. With the ability to carry out abstract reasoning as a trait uniquely attributed to intelligent agents, it would follow that abstract specificity would therefore require intelligent agents. Unfortunately, Meyer does not pursue the distinction between physical and abstract specificity. Since the functionality of DNA information resides in its physical-chemical action, no abstract specificity is evident in a living cell.
In addition, the abstract symbolism intrinsic to the genetic code has been widely recognized since Watson and Crick first discovered DNA’s structure and information-carrying capacities. Biologist and historian Ulrich Stegmann comments:
According to Crick, the coding problem centres around the mapping of four types of things to twenty types of things (see his quote in Section 2.1). Such mappings are relations between two sets, which can be described by means of set-theoretic notions like surjectivity. Since these features are the subject matter of a formal theory, it is reasonable to regard them as formal or abstract…The apparent conflict between the abstractness of coding schemes and their mechanistic commitments is thus dissolved.
The genetic code is an abstract symbolic system even through it is implemented through physical processes. The same holds true for most codes including the ASCII code executed in computers and the Morse code historically applied to signals transmitted over a telegraph wire.
Information in Biological Molecules
A related error is claiming that the information carried in biological molecules is not comparable to human-generated semantic information. Again, this claim stems from a misunderstanding of the nature of biological information. The fact that DNA, RNA, and proteins contain meaningful semantic information has been recognized by leading experts in the field such as complex systems researcher Anne-Marie Grisogono:
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.
The connection between the information residing in proteins and that information’s meaning/purpose is further articulated by philosophers of science Karola Stotz and Paul E. Griffiths:
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…In short, the enzyme mold here contains the core program for a sequential chemical reaction.
The information in proteins differs from human-generated information in that it directly corresponds to a proteins’ physical structure, but this difference in no way diminishes its semantic character or its association with abstract meaning. In fact, the connection between DNA, proteins, and the resulting biological structures in many ways resembles how information in CAD-CAM technology directs the production of airplane parts.
Proteins and Language
The striking similarity between proteins and human language is further elucidated by computational biologists Andrea Scaiewicz and Michael Levitt:
In this comparison, the vocabulary (domains) of proteins is built from an alphabet of amino acids. The syntax principles enable domain association to form multi-domain architectures, a process governed by hierarchical rules (grammar), that determine the structure and hence the biological function (semantics) of proteins.
These researchers felt compelled to describe biological information using such phrases as “coding schemes,” “carries meaning,” “core program,” and “hierarchical rules (grammar).” Such terminology clearly entails abstract reasoning and thus points to design even by the critics’ own criteria.
Tomorrow: Misinterpreting research related to protein rarity.