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The transmission sense of information

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Abstract

Biologists rely heavily on the language of information, coding, and transmission that is commonplace in the field of information theory developed by Claude Shannon, but there is open debate about whether such language is anything more than facile metaphor. Philosophers of biology have argued that when biologists talk about information in genes and in evolution, they are not talking about the sort of information that Shannon’s theory addresses. First, philosophers have suggested that Shannon’s theory is only useful for developing a shallow notion of correlation, the so-called “causal sense” of information. Second, they typically argue that in genetics and evolutionary biology, information language is used in a “semantic sense,” whereas semantics are deliberately omitted from Shannon’s theory. Neither critique is well-founded. Here we propose an alternative to the causal and semantic senses of information: a transmission sense of information, in which an object X conveys information if the function of X is to reduce, by virtue of its sequence properties, uncertainty on the part of an agent who observes X. The transmission sense not only captures much of what biologists intend when they talk about information in genes, but also brings Shannon’s theory back to the fore. By taking the viewpoint of a communications engineer and focusing on the decision problem of how information is to be packaged for transport, this approach resolves several problems that have plagued the information concept in biology, and highlights a number of important features of the way that information is encoded, stored, and transmitted as genetic sequence.

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Notes

  1. We think that Stegmann handles the misrepresentation issue even more cleanly with a shallow semantic notion of genes as conveying instructional, as opposed to representational, content (Stegmann 2004).

  2. In practice, it takes time to send information from one place to another, but the conventional Shannon framework suppresses this time dimension.

  3. A message need not be composed of multiple characters to meet this definition. Even a string of length one is a sequence; thus even a single character conveys information.

  4. Though see Shea (2007) for how a semantic view of information need not be incompatible with a focus on intergenerational processes such as evolution by natural selection.

  5. Similarly, Shea (2007) uses this fact to derive teleosemantic meaning in his account of biological information.

  6. Although causal-sense information is transmitted from the population at time t to the population at time t+1 in the population frequencies of haplotypes, this is not transmission-sense information because the function of these population-level haplotype assemblages is not to reduce uncertainty on the part of future populations.

  7. The source-channel separation theorem (Cover and Thomas 2006, Chapter 7, p.218) proves that in any physical communication system for error-free transmission over a noisy channel, one can entirely decouple the process of tuning the code to the nature of the specific channel from not only the semantic reference of the signal but, indeed, from all statistics of the message source. This follows because the theorem states that one can achieve channel capacity with separate source and channel coders—and in this setup, the source coder can always be configured so as to return output that maximizes the entropy given the symbol set.

  8. Using Shannon’s 1950 upper bound on bits per letter and his estimate of letters per word in the English language (Shannon 1950), we can estimate the bit rate of a touch typist as \( \frac{120\,\hbox{words}} {\hbox{minute}} \frac{1\,\hbox{minute}}{60\hbox{ seconds}} \frac{4.5\,\hbox{ letters}} {\hbox{word}} \frac{1.3\,\hbox{ bits}} {\hbox{letter}} =11.7\hbox { bits/second}.\)

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Correspondence to Martin Rosvall.

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Bergstrom, C.T., Rosvall, M. The transmission sense of information. Biol Philos 26, 159–176 (2011). https://doi.org/10.1007/s10539-009-9180-z

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