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Claim CF005:

The second law of thermodynamics applies to information theory. It follows that genetic information will become increasingly degraded as it gets repeatedly copied over time.


Kofahl, Robert E., and Kelly L. Segraves, 1975. The Creation Explanation: A scientific alternative to evolution. Wheaton, IL: Harold Shaw, p. 37.
Morris, Henry M., 1974. Scientific Creationism, Green Forest, AR: Master Books, pp. 38-40.


  1. While statistical information theory has a quantity called "entropy", it does not have anything equivalent to the second law of thermodynamics. In a general information processing/transmitting system, entropy can freely decrease or increase.

  2. There are some classes of information systems in which information can only decrease, for example a deterministic, causally isolated system with discrete states. However (at least in this case) the information loss corresponds to a decrease in entropy.

  3. Information theory does sort of have a principle of degradation, but it is only applicable in certain situations (which evolution isn't one of). It implies, essentially, that information change is irreversible: information gets more and more different from how it started out, and the more it gets changed, the harder it is to tell how it started out. In a communication or information storage system, where the goal is to transmit or replay the original message intact, change is necessarily bad, so this corresponds to degradation. In evolution, change is not necessarily bad, so this is not a principle of degradation.


Davisson, Gordon, 4/18/2001. Information and microevolution. Message-ID ,

Davisson, Gordon, 7/14/2002. Re: Simple Thermodynamics Argument. Message-ID ,

Davisson, Gordon, 2001. Macroscopic and molecular entropy.

Further Reading:

Shannon, Claude E., 1948. A mathematical theory of communication. Bell System Technical Journal, 27: 379-423 and 623-656. Reprinted in Claude E. Shannon and Warren Weaver, The Mathematical Theory of Communication, University of Illinois Press, Urbana, 1949; (Shannon's seminal paper on information theory; technical)

created 2003-9-15