Ontic Cafe Four Beans Difficulty (Detailed but written to be accessible to laypersons)
This post is the first of two. The material is from a quite complex field of the philosophy of biology and information theory in biology. It would normally be at least 5 Ontic Café Beans, but I have watered it down to about three. Nonacademic philosophers should be able to get a reasonable idea what is going on and benefit from an introduction to one of the hottest topics in the philosophy of information and biology.
Different Conceptions of Information
Let’s start with a rapid introduction to the philosophy of information.
There are several conceptions of the nature of information – of what information
actually is. These conceptions vary dramatically in their details and
ontological commitments – the things that are taken to be necessary to have for
there to exist some information (in philosophical language we day “the
necessary conditions” for information to exist.) Here a couple of quick
examples will be instructive.
The most common understanding, and the most common scientific
one, is that of quantitative information theories. In these theories one has
information on a statistical or probabilistic basis. According to these conceptions
information exists when there is a reduction in uncertainty about what is
happening at an information source. An information source is any physical process
that can be modeled statistically – about which you can say there is a certain probability
of the next state of the source based on the current one. A simple example is
you reading this sentence. Each word makes the next word more or less likely
because of the structure of the English language and the rules (grammar and
meaning) for making English sentences. The source is the text you are reading. This
is the very example most used by the founder of modern quantitative information
theory – mathematician Claude E. Shannon (The Mathematical Theory of
Communication, 1948.)
The main alternatives to quantitative statistical theories
are algorithmic theories. These involve measuring the complexity of strings of
symbols or what are called data objects. Any sequence of elements can be a data
object. The longer and more complex the data object – the more information it
has. The most famous is that developed
by Russian materialist mathematician Andre Kolmogorov. In Kolmogorov’s
theory the amount of information in a data object is given by the length of the
program or description required to generate or construct the data object.
Semantic Information
Quantitative statistical measure based conceptions and
definitions of information have often been seen as inadequate because as Claude
Shannon himself wrote in The Mathematical Theory of Communication, they do not
attempt to capture any meaning of the symbols that are transmitted. His
predecessor R.V.L Hartley wrote that ``[i]t is desireable therefore to
eliminate the psychological factors involved and to establish a measure of
information in terms of purely physical quantities'' (Transmission of Information, 1928, 536.)
Shannon’s peer and mentor Warren Weaver first observed that
in future it would be desirable to formulate a conception of information that accounted
for meaning. Later theorists came to refer to such conceptions as theories of
semantic information. There have been
several of these – mostly naturalistic – offered by both mathematicians and
philosophers. The first notable attempt was by the famous Vienna circle
mathematician and philosopher Rudolph Carnap. Carnap joined with mathematician
Yehoshua Bar-Hillel to formulate a theory of semantic information in which the semantic
information content of a sentence was determined according a to a logical
formulation (1953.) In lay terms the information content of a sentence is the
set of all sentences that are false if that sentence is true.
Later various other conceptions of semantic information. Philosopher Fred Dretske adapted elements of
Shannon’s theory (1981 – Knowledge and the Flow of Information.) Mathematician
Keith Devlin produced another logical conception (1995- Logic of Information.)
More recently, Luciano Floridi has produced a theory of semantic information
that extends and adapts ideas put forward by Devlin and Bar-Hillel and Carnap.
It is different in that it requires information to have alethic value – to be
based upon data which are truthful according to certain fairly complex criteria
(Floridi, Information in The Blackwell Guide to the Philosophy of Computing and
Information - 2004, Information – A Very
Short Introduction - 2011, The
Philosophy of Information - 2012.)
The idea of semantic theories of information is that
information and meaning are directly related somehow. Usually meaning is
thought to involve truth value of some kind.
Meanwhile in Physics and Biology
An enormous part of the story of our understanding of the nature
of information comes from physics. I will not say much about that here, except
to say that physicists often regard information to be a physical thing. Another
pioneer of information theory – the father of Cybernetics Norbert Weiner – once
said that “information is information, not matter or energy...no materialism
that does not admit this can survive...'' (1962, Cybernetics: or Control and
Communication in the Animal and the Machine.) No physicist has claimed that information
is matter or energy, but quantum computing pioneer Rolf Landauer was sure that it is physical (Information
is a Physical Entity, 1996.)
An enormous amount of philosophical and technical thought
about information comes from biology. This is not so surprising
given the importance of the concept of information to genetics and DNA science.
Inherited traits from one generation to the next of phenotypes (organisms) are
described in terms of information. So is what is referred to as the central
dogma of molecular biology: that information cannot go from the phenotype (the
developed body) to the genotype (the gene/DNA.) In other words, if I cut my
hand it will not mean that any child conceived by me in the future will have
the same cut on their hand. More recently the central dogma has come under
challenge from the field of epigenetics. In epigenetics, other things in
addition to the gene – the DNA itself – are thought to contribute heritable
information or information that is passed from one generation to the next. This
can include processes within the cytoplasm of the cell, or even things in the
organisms environment like the structure of nests in which young are reared. Still - it is often information transmission that is of interest.
At least since Crick and Watson’s discovery of the double
helix structure of DNA in 1971, biologists and philosophers of biology have been
contemplating and arguing about the nature of information and information
transfer in DNA and biosynthetic processes. Biosynthetic processes are
processes in which smaller molecules are combined to form more complex
molecules that have some more complex function (processes involving such things
as the manufacture of protein and other biological structures from genetic
material.) Such processes are frequently
described in terms of information.
Codes, encoding, transmission, and even information compression
have been discussed as real in the processes of genetic material.
This all raises a question, however. We saw in the previous section
that there are many conceptions of information. So which is the right one for
biology? Molecular bioscientists and philosophers of biology are still trying
to figure that out. There are even arguments about whether genetic information is semantic or not - if it has meaning and if so in what way (See recent work by Nicholas Shea on what he calls Infotel semantics. The idea is that the meaning of genetic information is determined by its function.) Some philosophers of biology even have what is known as an
eliminative conception of information in biology: they eliminate it from the
discussion completely or partly as a useless metaphor that is confusing and
does not explain anything real (See Griffiths, Paul E. Genetic Information – A Metaphor
in Search of a Theory http://philsci-archive.pitt.edu/89/1/Genetic_Information_etc.pdf.)
Are There Informational Laws in Genome Evolution and the Evolution of Protein Synthesis?
This entire area of the nature of information in molecular
bioscience is complex and keenly debated. However, in this two part series I am
interested in a very specific part of the debate – one that is perhaps the most
exciting and relevant to philosophy in general and not a little evolutionary
science today. It involves the question of how protein synthesis evolved by
natural selection. The process of protein synthesis is an incredibly complex
biosynthetic process that has only recently come to be well understood. The
complexity of the processes of protein folding and gene splicing meant that the
details of these processes were wholly mysterious up until recently. How such
processes came to evolve naturally to their current state is an even more
challenging mystery.
Above is an artist's representation of the proces of protein synthesis from DNA via processes of DNA transcription and translation into a chain of amino acids and finally into a folded protein. The process is staggeringly complex, with only the most basic fundamental steps represented here. Molecular bioscientists usually take it for granted that there is information transmitted form the DNA to the protein. A much larger question, however, is how the information of the entire process and the structures involved in it came to be as it is by evolutionary processes. Eugene V. Koonin has proposed that "Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as “laws of evolutionary genomics” in the same sense “law” is understood in modern physics." (http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002173) The details of this theory involve the laws being expressed largely as statistical and informational.
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