Biosemiotics
DOI 10.1007/s12304-012-9155-3
O R I G I N A L PA P E R
The Meaning(s) of Information, Code … and Meaning
Anton Markoš & Fatima Cvrčková
Received: 13 December 2010 / Accepted: 22 November 2011
# Springer Science+Business Media B.V. 2012
Abstract Meaning is a central concept of (bio)semiotics. At the same time, it is also
a word of everyday language. Here, on the example of the world information, we
discuss the “reduction-inflation model” of evolution of a common word into a
scientific concept, to return subsequently into everyday circulation with new connotations. Such may be, in the near future, also the fate of the word meaning if, flexed
through objectified semantics, will become considered an objective concept
usable in semiotics. We argue that reducing meaning to a technical term essentially synonymous to code and stripped of most of the original semantic field is not a
necessary prerequisite for a meaningful application of the concept in semiotics and in
biology.
Keywords Meaning . Information . Reduction-inflation model
The conclusion seems inescapable that cells are able to sense the presence in
their nuclei of ruptured ends of chromosomes, and then to activate a mechanism
that will bring together and then unite these ends, one with another. […] [This]
is a particularly revealing example of the sensitivity of cells to all that is going
on within them. They make wise decisions and act upon them.
B. McClintock, Nobel lecture, 8 Dec. 1983
Genes and proteins, in short, are assembled by molecular robots on the basis of
outside instructions. They are manufactured molecules, as different from
A. Markoš (*)
Department of Philosophy and History of Science, Charles University Prague, Faculty of Sciences,
Viničná 7, CZ-128 44 Praha 2, Czechia
e-mail: [email protected]
F. Cvrčková
Department of Experimental Plant Biology, Charles University Prague, Faculty of Sciences, Viničná 5,
CZ-128 44 Praha 2, Czechia
A. Markoš, F. Cvrčková
ordinary molecules as artificial objects are from natural ones. Indeed, if we
accept the commonsense view that molecules are natural when their structure is
determined from within and artificial when it is determined from without, then
genes and proteins can truly be referred to as artificial molecules, as artifacts
made by molecular machines. This in turn implies that all biological objects are
artifacts, and we arrive at the general conclusion that life is artifact-making.
M. Barbieri 2008a, 579
Prologue
Situation 1, April 10, 2010: The Polish radio broadcasting (in Polish) the news
about the demise of the Polish President in an air crash.
Situation 2, April 6, 1994: The Polish radio broadcasting (in Polish) the news
about the demise of the Presidents of Rwanda and Burundi in an air crash.
On hearing the first message, an average Polish listener remains in a deep shock
and grief. An average Polish listener understands, of course, perfectly also the second
message, but no emotions will follow – well, it happens from time to time that this or
that potentate goes down in an accident.
On hearing the first message, an average citizen of Rwanda remains inert – even if
he may guess from the discomfit voice of the speaker (and by distinguishing words
like “Prezydent”, or “Polska”) that probably some tragedy has happened in Poland.
The second message leaves him completely indifferent – he hardly notices from the
monotonous flow of foreign speech that the message marks the beginning of his
country’s tragedy. An average inhabitant of, say, Bolivia, overhearing accidentally the
Polish broadcast, will probably react similarly as the Rwandan, but no consequences
will follow for him from any of both messages.
Disregarding the static, all three listeners received the same information, though
for two of them one of the messages was of utmost importance (even more for the
Rwandan). Only the Pole got rightly both, because he had an access to the language
code in which the messages were transmitted. In addition, in Situation 1 the universal
human code for sorrow was recognizable in the speaker’s voice – and all three
listeners realized it, but it was only part of the information. What fraction of
information, then, was contained in the message proper in Polish (which can be put
down on paper, or perhaps even quantified according to some criteria), and what in
the tremble of the speaker’s voice?
Both broadcasts represented signs of a tragedy – to or for a receiver who had the
access to a code. If our Bolivian and Rwandan would speak Polish, they would
interpret them in a different way, if a Bolivian has a Rwandan (or Polish) partner, she
would react differently, if… Each message (identical information) would represent a different, specific, perhaps personal meaning for any of the human
beings involved.
Here we are: In human affairs, information, sign, or meaning is always information, sign, or meaning to somebody or for somebody. Information must become a
sign, and the sign will be interpreted uniquely, according to the nature of the person
The Meaning(s) of Information, Code … and Meaning
deciphering it: the result of such interpretation will be its meaning to or for some
person, here and now. The meaning may change with contexts, of course.
Two questions will be dealt with in this paper:
1. Can information, sign, and meaning become scientific terms? Our tentative
answer is No; if Yes, only at a cost – we will, perhaps inevitably, have to ignore
exactly those aspects of our shared experience we wanted to grasp.
2. Can tentative concepts of information, sign, and meaning, as known in human
affairs, be extrapolated to the affairs of all living beings (including, e.g., bacteria,
plants…), and to different level of description (cells, embryos, individuals in their
ecosystem, etc.)? Our tentative answer is Yes.
It may be worth emphasizing that the wording of the second question already
shows that, unlike some biosemioticians (e.g. Brier 2003), we do not aim towards
understanding, ultimately, the functioning of the human mind, brain or consciousness. Our main interest are those aspects of communication as signification that
appear to be common to all living beings – and our uniquely first-person experience
with the human affairs can provide nothing more, and nothing less, than a model
guiding our thinking about the processes taking place in, or performed by, beings not
endowed with a human-like mind.
It follows from our answers that some aspects of the living of utmost importance
cannot be formulated, i.e. studied, in the realm of contemporary biological science, at
least as far as this science claims to aim towards explaining (away) all biological
phenomena in terms ultimately reducible to those of chemistry and physics. In this
sense (and only in this sense) our position is vitalist, if we accept the Drieschian (i.e.
not the Bergsonian), definition of vitalism sensu lato: as the acceptance of the
premise that some aspects of living beings are specific to them and not found
elsewhere (Eigengesetzlichkeit, Driesch 1905), and that current concepts of sciences
such as chemistry or physics thus cannot grasp them in principle. It has to be,
however, noted that we do not follow Hans Driesch in his demands for some
measurable quantity specific to living matter (which is how his entelechy may be
understood). That elusive “own law” of life may well be … semiosis. Below, we shall
put our answers to the above two questions into contrast with opposite views,
personified mainly by one of leading figures of contemporary biosemiotics, Marcello
Barbieri.
What is in a Word: The Reduction-Inflation Model
Let us first examine the tangled pathways whereby a common word evolves into a
term, using as an example the generally accepted (though sometimes ill-defined)
concept of information, which, incidentally, also happens to be rather central to our
current discussion.
History of science has witnessed many examples of terminological misconduct
roughly corresponding to the following scheme: (1) Take a word of broad usage and
narrow its semantic field (scope) substantially, generating a technical term used in a
limited area. (2) Inflate this technical usage back to the whole realm of the previous
A. Markoš, F. Cvrčková
semantic field. (3) Proudly state that “today, in contrast to the dark ages of previous
generations, we already know what the term means.”
We shall pay attention to the concept of information here, but the same development can be demonstrated in many other scientific terms taken from ordinary
language, like force, light, heat, or black hole: everybody knows the words and has
developed a private semantic field (feeling) for them. When it comes to science, it is
very difficult to narrow the semantic field of such words, to apply scientific objectivism (sensu Lakoff 1987) and to work with the concept in frames of formal,
objective language.
It would perhaps be much more convenient to invent a new term with no counterpart in natural language, say “phenomenon Φ” for the black hole (or “guf” instead of
force). Perhaps cosmology would not be that popular in public as it is today. But
words have their fates. Entropy is an artificial word; in the 1950s, it seems, it still
remained somehow suspect in the vernacular. That is why C.P. Snow (2003) had
difficulties with “literary intellectuals” when he asked them to explain the term (and
should he have asked, say, biologists, he would be disillusioned too). By now,
however, it found its home in ordinary language as, roughly, a synonym of “disorder”
and everybody feels that he/she is at home with it. Even more illustrative is the
“transcription” of the term in different writing systems, like Chinese: the ideogram for
“entropy” tends to be read as an ordinary Chinese word (“shang”) having some 15
different meanings, none directly connected with the physics (see Mackay 2001).
In-formatio was understood since the Middle Ages as a process of molding of the
mind or character, by training, instruction, teaching, or even divine inspiration. Later
its meaning was somewhat narrowed to communication of knowledge concerning
facts, subjects, or events: intelligence, news, but not raw data! (see, e.g., The compact
Oxford Dictionary). For an early 20th century physiologist, information is something
that causes differences in response in the living body or its parts. Hence, the informed
subject had been gradually replaced by a contraption (e.g. a feedback device), and
information itself became but a difference that makes a difference (Bateson 1972).
Yet, even information in such a sense cannot be treated formally, nor can it be
measured, only discerned: it can affect its addressee through its quality or meaning
for this particular addressee, but there is no objective definition of information.
In 1948, Claude Shannon introduced the catchy technical term information to give
a name to the probability of transmission of a digital string of symbols through a
channel (Shannon 1948). Defined in such a way, suddenly information could be
mathematically defined, measured, quantified, stored, and manipulated by machines.
Even more, it became context-free (it requires no addressee to or for whom it confers
any meaning) and thus completely decoupled from meaning, hence objective and
palatable for scientific use. Consequently, such particular usage of the word had
immediately gained on popularity in scientific circles, and from there it quickly
infested many areas that had nothing in common with the original territory of use;
finally entering school curricula and creating thus a “memetic trap” that shapes our
thinking ever since. Both general public and experts now “know” precisely what
information is. One can, for example, find calculations of how many bits of information is contained in the human genome, in the net of the brains’ neuron connections,
etc. (e.g. Christley et al. 2008; Wang et al. 2003; Reber 2010). Even more, one often
encounters a statement that information belongs to fundamental physical quantities,
The Meaning(s) of Information, Code … and Meaning
besides matter and energy (e.g., Barbieri 2003). Note that the narrowing, reduction
the semantic field of the word was quickly followed by an inflation – a bubble of new
contexts where “information” is now being used in the vernacular. Yet, the old natural
language meaning of the word information still somehow manages to survive in the
everyday life. As much as we might argue about bits and bytes, hardly anyone would
think of looking for them at the information kiosk of a train station.
Claude Shannon is not to be blamed for the above-mentioned reduction (the less
for the inflation). His classical paper from 1948 contains also a warning, notoriously
known from basic textbooks in informatics: “Frequently the messages have meaning;
that is they refer to or are correlated according to some system with certain physical
or conceptual entities. These semantic aspects of communication are irrelevant to the
engineering problem.” Indeed, two messages of very different meanings, or even a
meaningful message and a meaningless one, may be indistinguishable in terms of
“information content” according to the technical definition (Shannon and Weaver
1949).
In other words, once we have accepted the Shannonian definition of information,
we should give up the notion of contents – or, rather, we should delegate it to
something else than information. Meaning?
Incidentally, Shannon’s warning contains also a summary of what meaning means:
reference, correlation, i.e. putting a message (a word, a letter, a sound) into the
context of a physical or conceptual entity. Even the most elementary usage of the
word (as in the phrase “different meanings of the same word”), not to speak about its
more sophisticated uses (e.g. intention, purpose, spirit of the told or written word,
interpretation, signification) points towards an intimate connection between meaning
and context; the same sentence, statement or text may mean different things for
different readers, or, occasionally, nothing at all, if a certain background context is
absent (just imagine the situation from the prologue, only substituting a Polish
newspaper to the radio broadcast). As P. Heelan (1998) noted, for a written text
“there is no single legitimate meaning relevant to all readers of, say, a text (or
suchlike material), for meanings depend on use.”
Thus, the external world, both synchronous and diachronous (acting through
memory and experience) always enters the discourse as a modulator of interpretation.
Only when we accept this, can we speak – in a natural language – of semiotics or
even hermeneutics performed by the living (Markoš 2002).
But can all this be extrapolated to non-human beings?
Organic Information – and Meaning
There is another brave attempt of introducing the term into science: M. Barbieri (e.g.
2008a) coins the term organic information as a basic physical entity (irreducible, i.e.
not derived from other physical entities) that is not a quantity but a nominable: it
cannot be measured but only named. He explicitly means aperiodic biological
polymers like DNA, RNA that cannot come into existence spontaneously (e.g.
through ordinary chemical reaction or by crystallization), but exclusively by copying
of pre-existing molecules of the same kind that serve as a template for the newly
made polymer. Similarly, proteins that can be synthesized, in cells, only thanks to the
A. Markoš, F. Cvrčková
existence of the genetic code. In short, for nominables – both molecules or man-made
texts – only a copying process, or some translating algorithm, will ensure their
continuing existence (or evolution) in time. (Note that both kinds of nominables
are, then, artifacts: below we shall return to the question of who wrote the templates.)
There are no rules – physical or chemical – how to decipher the sequence of
building block in such a nominable, they must be read one by one, and, if in a string
of 500 nucleotides or amino acids we know 499 units, we still have no hints what the
500th item (base, amino acid) would be.1 Thus, two such strings differing in a single
item represent two different, nominable, physical entities. Describing the sequences
in terms of Shannonian information would lead to two identical numbers revealing
but a trivial fact that the strings are of the same length.
Two problems should be further elaborated with organic information reified,
connected with nominability of strings at different levels of description.
Let us for this moment keep the paradigm of the central dogma stating that
“information [sic] flow can proceed from nucleic acids to proteins, not backwards”
(Crick 1958). In its simplest case, the unique (nominable) string of DNA is either
trans-coded into a complementary string of DNA (in a process called “replication”),
or trans-coded into a complementary string of RNA (in a process called “transcription”). One class of RNAs (called mRNA) may then be translated into the polypeptide
string of a nascent protein according to the genetic code. There is a match, via
mRNA, between the sequence of nucleotides in DNA, and the sequence of amino
acids in the nascent protein; almost as perfect as, say “A” is a match of “▪ –” in Morse.
Barbieri has a credit that he pointed to the fact that the existence of such codes is not
self-evident from the laws of physics as we know them: codes are products of
historical coincidence, i. e. proteosynthesis is “artifact-making”, not an ordinary
chemical reaction of polymerization (e.g. Barbieri 2008a). He goes on, however, by
stating that in this particular case the nominables in the set of DNA string represent
“signs”, whereas those in the set of proteins (results of decoding the information)
represent the “meaning” of those bits and pieces of information. “Meaning is an
object, which is related to another object via a code”, says Barbieri (2003, 5). “A” is
the meaning of “▪ –“(and vice versa, in this particular case). He then insists that this
may be the scientific, i.e. objective and reproducible, definition of meaning. It follows
from such a reduction (comparable to Shannonian treatment of information) that the
existence of codes is a necessary and sufficient condition for semiotic processes; i. e.
semiosis is completely decipherable in scientific terms provided that the codes are
known. Indeed, to model life as a hierarchy of codes (e.g. Trifonov 2008) is a very
catchy and respectful idea, yet, we feel that modeling living processes as a deterministic program-run machine (like a computer) belongs to physiology rather than to
semiotics – and physiology can do without the concept of meaning. Barbieri tries to
encompass the term of meaning in lines of the most venerable tradition of modern
science: by developing mechanistic models of life and especially levels of semiosis
present in living beings (see, e.g. Barbieri 2011a, b). As is apparent, we follow a
different path of investigation that, in future, may, or may not be, encompassed by
science.
1
But grammar may sometimes help with such a spelling: not all sequences will give sense.
The Meaning(s) of Information, Code … and Meaning
The description above aspires to belong to the realm of objectivist semantics
(Lakoff 1987). Here, meaning and rationality become transcendent, i.e. perfectly
communicable and identical to all participants of such an information exchange. As
will be further discussed below, semiotics has no place in such an objective construct;
semiotic processes will confer meaning to or for a particular being. Indeed, Barbieri
in his earlier work (2003) uses the term semantic biology; the switch towards semiotics was, on our opinion, infelicitous.
Code
What, then, is a code? If we put aside juridical and biblical usage of the word, we are
left with signals, abbreviations, or signs serving for either simplified (compacted) or
protected (encrypted) transmission of messages, originally in fields such as e.g. the
military, transport or telegraphy. For instance, shortwave radio enthusiasts are, even
now, using not only the notorious Morse code, but also the “92 code” originally
designed in 1859 by Western Union railway telegraph operators, and the “Q code”
originating from the abbreviations established for communication among British
commercial ships before WW I.
Nowadays, cybernetics, computing or molecular biology are just additional situations where one-to-one correspondence between the original and received message –
transmitted via the code – is often necessary or at least desirable. It follows that
machines or machine-like devices able to perform the coding and decoding (or even
code-breaking) can be built. They do so using hardwired tables of codes, which can be
stored, transferred, public or hidden. No intrusion of mind, intentionality, understanding
of the context – some of the basic components of meaning in the old, broad sense
known from the natural language – is required, despite the fact that the code is a
specific case of meaning.
To return to the definition quoted above: meaning0mutual relation of two objects
via a code. The narrowed contents of such a technically defined meaning covers
therefore only a fraction of the original semantic field of the word – as is usual when
objectivization is desired. Like in the case of information, we are at risk of falling into
another version of the old memetic trap: the technical, narrowed-down definition of
meaning may come back into the natural language. Everyone will know from now on
that meaning is just a matter of coding and decoding – maybe more complicated than
the Morse code, but “in principle” one only needs to understand how Morse works to
grasp it all.
However, even in the realm of codes, old meaning is not dead, as long as human
beings enter the chain of message transmission and interpretation. The railway telegraph operators who designed the “92 code” more than 150 years ago were undoubtedly busy men working with low-throughput transmission channels of limited
reliability, and the code table is thus as compact as possible. Yet, since the very
beginning, 73 has been reserved for “best regards” – nowadays perhaps the most
frequently used code word of this table (and 88 stood for “love and kisses”, long
before the neo-Nazis gave it another, more sinister meaning). For deciphering meaning, codes will represent only a subset of necessary preconditions to understand signs
which never are objects.
A. Markoš, F. Cvrčková
Objects and Signs
Let us first examine the seemingly innocuous notion of an “object”, the concept
which plays such a prominent part in M. Barbieri’s definition of meaning. We shall
follow the terminology of J. Deely (2008, 2009a, b, 2010), who works up the
tradition of semiotics going through Middle Ages via C.S. Peirce up to our Postmodern times – contrasting to the tradition of Modernity. We should start with a little
terminology we are rather unused to, or even worse, the same words have an opposite
meaning in the terminology of Modernity.
According to this concept, the world is full of things – known or unknown to us –
which abound with different qualities and relations, all modeled by their history.2
Nobody is able to list all the properties of a thing – however well known. Such
subjectivities of the surrounding world can give themselves (or can be perceived) to
senses, receptor molecules and/or structures of a living being: we stress again – any
living being, not only that endowed with mind.
What follows, however, has been elaborated for humans or – at most – animals;
generalization of some semiotic concepts is our task here. Sensations, in cooperation
with our nature, experience, language competences, learned knowledge, historical
and community context, etc., will give rise to a suprasubjective sign. A sign cannot be
pointed at with a finger – it is a relation. Signs then will be processed – interpreted –
into objects of mind. Objective reality, then, is a product of our minds, and is
inhabited by objects and their relations. Object may point toward some aspects of
things (subjectivities) in the world, or they can even be created independently of the
world, inside the minds (like numbers, geometrical objects, or objects of physics.
Objective reality – a transcendent artifact of human mind – can be communicated
(and learnt) across the society by means of a class of signs called words. In short,
objective reality is our creation, resulting from evaluating the meaning of everchanging signs in the flow of our experience (remember our Prologue).
Objective reality is an evolutionary invention, characteristic for Homo sapiens,
who is able to distinguish between things and objects. It may be that other animals
also build their umwelten from objects that they, however, cannot distinguish from
things. Yet we shall maintain here that creatures other than animals are also able –
without access to objects and language – of deciphering sings and their meaning,
depending on their nature, genetic databases and programs, evolutionary as well as
individual experience, learned knowledge, historical and community context, etc.,
thus interpreting their situation in the world. In other words, we aspire to persuade the
reader, that cells, plants, bacteria are able to “make wise decisions and act upon them”
(see epigraph).
Here we enter an unsafe terrain. Neither Barbieri nor Deely will provide us a
guide, (each for different reasons, see their exchange in Barbieri 2008b; Deely
2009b), not only because they build on different premises (which, on itself, does
not exclude the more than welcome possibility of reaching, independently, similar
conclusions), but also because they differentiate between beings dwelling on different
levels of scala naturae. Deely only grudgingly accepts zoosemiotics, but does not
2
Actually, Deely is very close to similar characteristic of things in Heidegger (e.g. 1971; see also Markoš
and Faltýnek 2011.)
The Meaning(s) of Information, Code … and Meaning
admit semiotic accomplishments to beings devoid of brains or at least nervous
system. Barbieri accepts Deely’s platform as one (the highest) step of his three-step
semiosis, but he does not allow two lower steps any interpretative abilities; hence
both thinkers degrade beings different from humans (or humans plus some animals)
to programmed machines.
The only difference from machines (or mechanistic models of reality – see Barbieri
2011b) is that living beings are neither copied nor produced (made), but born from
other living beings. But this difference makes the very difference between living
beings and automata. Life is not art, neither artifact-making: it’s life who makes
artifacts and fine arts and even writes down its experience into quasi-digital strings of
biological polymers (to read, i.e. interpret the script in various contexts). We endeavor
to claim that there is only one and single “grade of semiosis”, accessible to all living
beings – because all share the same world and all carry with them 4 billion years of
experience – written in their genetic material, or – somehow – transmitted by their
bodies and interactions with other living beings – conspecific or not. We shall further
concentrate on the first “level”: aperiodic linear biopolymers and their interactions.
Levels of String Classification
Let us explain the difficulties on the simplest model, that of the informationtransmission pathway DNA–RNA–protein as presented by Barbieri.
a. A protein-coding sequence in DNA may give birth to a single string of protein.
This is a very simple example of simple decoding, as it can be demonstrated in
laboratory models. Nevertheless, it does not automatically follow that in the
“world of bodies”, as discussed below, such a protein string will also reach the
same spatial conformation, as folding of the protein depends on the kinetic
parameters of its synthesis, which may well be affected even by the structure of
the RNA being translated (Kimchi-Sarfaty et al. 2007). (Even at this level some
paradoxes may arise: If two alleles of a protein-coding sequence in DNA differ in
a single nucleotide, they represent two different nominables, i.e. they deserve 2
names; yet due to the code degeneration, both may code but for a single protein.)
b. A protein-coding sequence in DNA can give rise – via alternative processing of
transcripts – to a plethora of unique, hence nominable, protein strings.
c. A native protein is often further processed by cutting or splicing peptide strings
and/or chemical modification of amino acid residues. In such a case the number
or quality of amino acids in the string will get changed, i.e. a set of unique
nominables, sometimes very large, would arise from a single native protein;
moreover, the process may be reversible, hence we experience a floating world
of incessant name-changing (for histone proteins, see Markoš and Švorcová
2009).
It follows from the last two points that the number of entities during the “information processing” (or better, transforming one class of organic information into
another) may increase even into the innumerable. Moreover, if the final issue of the
string depends on a number of modifying “epigenetic” influences (like, e.g. protein
kinases/phosphatases, methylases/demethylases, acylases, etc.) a question arises how
A. Markoš, F. Cvrčková
much information is coded in the information entity (i.e. string of DNA) and how
much arrives from the structured environment (structures, ecosystem of proteins, etc.,
see below). Can one, then, put a sign of equation between “information processing in
different contexts” and “interpretation dependent on context”?
To reflect the obvious fact (in case of the nucleic acid – protein relationships),
Barbieri sticks to an idea of a “codes upon codes” contraption. As we said above, the
model is meaningful, but it has nothing to do with semiosis and seeking for meaning
in the original sense (see the Prologue). Another reductionist move must thus be done
in order to justify it. Barbieri (2008b, 2011b) introduces the idea of 3-steps semiosis,
with steps evolving from code semiosis through signaling semiosis up to interpretative (cultural) semiosis; hence, only the third step involves interpretation, and only
humans are capable of pursuing this last step. On the lower levels, then, interpretation
does not take place, and meaning comes out of coding-decoding, i.e. of grammatical
or semantic processes. By such a trick, biosemiotics (at least its lower levels) could be
incorporated into the standard science of biology. At the point when no interpretation
except decoding is allowed, we can abandon the concept of semiosis easily – after all,
most textbooks do so.
Body
The situation with sequence multiplicity in proteins will get even more complicated
when we abandon the string-focused view and take into consideration the fact that the
protein molecule is a body with a great plasticity of shapes. Even in the simplest case
discussed in point a above, the protein’s body (molecule) is not a crystal-like
structure, even if it tends to adopt some preferred shape(s). Not only physical factors
like temperature, pH, ionic strength etc. (such factors will in some way influence all
proteins present) participate in “guiding” a nascent protein molecule towards this
shape, but above all targeted (allosteric) regulation of the given protein by a great
plethora of regulators that bind to the molecule – be it “messengers” or other proteins
present in its surroundings here and now. Or should we reverse the optic? Should we
say that the protein (or a protein team – a supra-protein structures like, say a ribosome
or microfilaments) take all those inputs as cue, to be able to react in a meaningful way
(to make wise decisions and act upon them in a given context)?
The role of highly structured cellular interior harboring thousands of different
proteins (who modify the nascent protein in a meaningful way allosterically or
by”changing the name” of the very string (as above b,c), is, then, the very information matrix that gives the protein its final shape, location, or function. Not only this:
even the very thesaurus of DNA sequence nominables represents bodily structures
(not speaking of RNAs) and will be readily molded by the cellular interior (so the
central dogma becomes somewhat blurred): simple bending of the string will change
the gene expression, not mentioning frequent recombination processes, and chemical
modifications of particular bases. Is a bent string a different item from the straight
one? Should a string with one cytosine modified to methylcytosine mark a new
nominable, or should we ignore such “diacritics”?
Confronted by the enormous body of data provided by contemporary biological
research, we feel that biosemiotics can hardly aspire to become a (natural) science,
The Meaning(s) of Information, Code … and Meaning
unless we accept that nearly all molecular biologists could be labeled as cryptobiosemioticians. The alternative is becoming, or remaining, a branch of semiotics proper.
If so, interpretation should be admitted at all levels of the living, with non-reduced
meaning of the concept of meaning. This requires searching for analogies between
natural language and the organization of the living (first attempts in such a direction
see Markoš et al. 2009; Markoš and Švorcová 2009; Markoš and Faltýnek 2011;
comparison of Barbieri’s and our approach see Markoš 20103). Because proteins are
born into preexisting cells (and such preexisting cells give rise to a multicellular
body), the way (language) how cells process their heritage (be it DNA or not), how
they understand, interpret this heritage, may give us cues how to understand life. But
we doubt that only pre-established, reifiable tables of codes work in the background.
Cells do not arise by copying and they never emerge de novo according to a blueprint:
they are born and they keep the tradition how to understand, among others, the
genetic script. They decide what should be processed in what contexts. The codes are
necessary but not sufficient preconditions for life (like vocabulary and grammatical
rules/codes are not sufficient for a meaningful speech or text).
A Place for Meaning – and for (Bio)Semiotics?
Meaning never sits somewhere ready to use; it must be negotiated all the time.
Negotiation to extract meaning, negotiation to maintain its vigor, negotiation to
control its historical development. Let us now outline two strategies aimed towards
grasping the living, both respectable but mutually incompatible to a large extent.
First, accepting the program of biologization of physics, we might discover lifelike properties in the universe itself, and adjust our model accordingly (Markoš and
Cvrčková 2002). While remaining safely in the realm of objective sciences, we could
thus hope to get rid of the uneasiness associated with fitting the phenomenon of life
into an objective model of machine-like deterministic universe – as universe itself
will be perceived alive (Jantsch 1979; Ruyer 1974; even Deely 2010 with his
pansemiotic statements). Modeling epigenesis, or ontogeny, as reconstruction from
incomplete information (Barbieri 2003), or attempts to describe the inner workings of
a cell in terms of a network of modules connected by a set of protocols (e.g. Csete and
Doyle 2002), may also fall into this category.
The second strategy will be expanding the study of living beings beyond the limits
of biology (understood as an objective science), and entering the realm of the “lifeworld” studies, of which classical biology would represents only a special case.
Living beings will be recognized not as push-‘n-pulled objects, detached in a
detached world, but as active participants in affairs that encounter on their lifepaths, taking care of themselves, actively influencing their world, lives, ontogeny
and even evolution by modifying the very rules how the universe behaves. The realm
of the lifeworld can be reached even from within sciences – as demonstrated, e.g., by
S. Kauffman’s (2000) model of the biosphere of autonomous agents, taking care of
3
Surprisingly, not only biological sciences succumbed to the reduced version of information: the same
process took place in linguistics, too. By language metaphor, then, we do not mean making analogies with
formal languages that are subject to scientific study (Markoš and Faltýnek 2011).
A. Markoš, F. Cvrčková
themselves and incessantly changing the properties of the universe. Semiotics,
hermeneutics, and similar disciplines of the humanities open the gate into this realm,
supplying methods and thought patterns unknown in natural sciences (Markoš 2002).
However, such an enterprise is not free of risk. First of all, you will be given
names:”vitalist” the mildest among them. As we have already seen, not unjustly. The
(not yet entirely consensual) biosemiotic axiom that life and semiosis are co-extensive
provides a perfect example of “life’s own laws” that H. Driesch considered a defining
feature of his vitalist theory.4
Science is focused on measurable and repeatable phenomena, albeit in biology
these are usually reached only in special model organisms under strictly controlled
conditions, and wise biologists are ready to accept this fact as a necessary limitation
inherent to the scientific method (see, e.g., Trewavas 2003). Nevertheless, from such
data obtained under specially designed circumstances, extrapolations are being made
to the whole realm of the living. Physiology, biochemistry, and molecular biology are
full of examples of molecular homeostatic machines. What cannot be forced into such
a mechanical model is considered deviation, non-standard behavior, or, at best,
accepted as being out of the scope of the scientists’ interest. Hence difficulties with
non-cyclic and non-deterministic phenomena or events, like origins of life, or evolution, as well as the frustration from our inability to construct an “epigenetic machine”
(an oxymoron, on our opinion). This cozy certainty that phenomena of the real world
are deterministic, predictable, available to the tools of the scientists’ trade, will be, of
course, lost.
What, then, is the position and role of mechanisms, of the measurable and
repeatable? How can they be accommodated into the lifeworld? Let us conclude with
a hypothesis, perhaps far-fetched, but at least suggesting a basis for mutual understanding between classical biology and lifeworld studies.
Life sooner or later delegates to machine-like behavior all those processes which
can reliably go on without continuous control. In such cases, hardwired coding will
be preferred to endless decision-making process and negotiation. We automatically
perform activities like walking, breathing, digestion, protein synthesis, driving cars,
pumping ions across membranes, even filling forms or answering our sweethearts,
but we can jump out from such automatisms and behave as sentient beings whenever
the context of situation becomes pushing. While we read poetry or write papers, our
cells and organs do their automatic jobs; similarly, we may not be aware when they
jump out from hardwired regimes. And let us not be mislead into anthropomorphism:
a similar argument can be developed even for plants, possibly the least “sentient”
macroscopic living beings imaginable (Trewavas 2003; Cvrčková et al. 2009).
If we extend this analogy to the whole realm of the living, we may came closer to
understanding ontogeny as a hermeneutic achievement based in the experience of the
given lineage, as opposed to a result of blind deterministic forces acting from the
outside. Lifeworld will become the true realm of information and meaning.
Back to biosemiotics: does biology gain more than what was lost by reducing
meaning to the result of decoding? If not, then we should perhaps renounce a
manageable definition of meaning in favor of a more specific term that can be defined
4
You will also be accused of laziness, because instead of hard work in the lab you kill your time by
“philosophizing”. But this is not the point we want to touch.
The Meaning(s) of Information, Code … and Meaning
without substantial loss of contents. Code itself would probably do, and M. Barbieri’s
later narrowing of meaning to organic meaning (Barbieri 2008a) can be taken as a
welcome step in this direction. Another alternative may perhaps be the notion of
protocols (analogous to those known from the computing field) connecting functional
modules at various levels of biological organization (see, e.g., Csete and Doyle 2002).
At the same time, we still believe that some aspects of meaning in the “old” sense, not
covered by the concept of code, remain highly important if we really strive to
understand life (to more details see the “language metaphor” of life, see Markoš
and Faltýnek 2011). While we cannot prove our point, we hope we can at least
illustrate it using the analogy of the game of chess as a metaphor for some aspects of
the scientific endeavor.
Coda
To make our view more palatable, we invite the reader to compare two games: chess
and ice hockey. In chess, the chessboard, the pieces and the rules (a code) governing
their behavior represent the world. The whole inventory of the world exists beforehand, objectively, no hidden elements (such as a piece called, say, Prime Minister) are
allowed, and no new elements or rules can arise throughout the game. The game is
different every time, sometimes interesting, sometimes dull, depending on the qualities of the players (like the models of the world provided by science, and their
interpretations). However, essentially it is nothing but push-‘n-pull of pieces on the
board, although the players may differ in their strategy. The pieces themselves have
no say in the ongoing game. The chess game is the analogy of the universe as studied
by scientists: those who push the keys are, of course, laws of nature. The world of
chess can be deduced from the properties of its elementary building blocks and from
laws that determine their behavior. Knowing everything about this basic level of
description is the safest way towards revealing all properties of such a world and
developing a winning strategy. Of course, there is a price. There is no space for
“Why?” questions like “Why is that piece called King, and why is it irreplaceable?”
Compare this with ice hockey: The world of the game is also limited by the
mantinels, rules (that evolve with time), and interpretation of those rules by the
referees. Yet, it’s the “pieces” – i.e. players, who create the game within the given
limits. They are not pushed and pulled by external forces, they themselves govern –
or better, “negotiate” – the dynamic of the match. Each of them enforces his fitness
upon the given world, they take risk, they recognize the meaning of their doings – and
the output is by far not the result of decoding. An interesting biological counterpart of
the hockey game has come from the group of S. Linquist (Rutherford and Lindquist
1998; Sangster et al. 2004; Taipale et al. 2010; see also Bergman and Siegal 2003).
Evolution in their view is in hands of the dynamic protein networks (players?) whose
activity is controlled, buffered, and kept in a chosen regime by special “chaperonin”
proteins (referees?) in the hubs of such networks. Mutation of the code, effect of the
environment, internal relations may be buffered for many generations (no changes in
phenotyope, i.e., species-specific appearance of the game), just to switch suddenly
from time to tome (change of rules). Compare this with chess pieces, which simply
“exist” and have no participation on rules applied from outside.
A. Markoš, F. Cvrčková
Let us allow to draw a primitive analogy between the ice hockey-like games and
life: the players (proteins, cells) are largely similar in different games (species), it is
the rules (genes, coded contraptions, etc.) and the overall settings (playground of
ecological interactions and historical contingencies) that makes each game a distinguishable “species”, with evolution. Such a historically achieved network of interactions allows the players to model their world “specifically”, to give it meaning.
Acknowledgements This work was supported by grants from the Czech Ministry of education
(MSM0021620845 to AM and MSM0021620858 to FC).
References
Barbieri, M. (2003). The organic codes. An introduction semantic biology. Cambridge University Press.
Barbieri, M. (2008a). Biosemiotics: a new understanding of life. Naturwissenschaften, 95, 577–599.
Barbieri, M. (2008b). The code model of semiosis: the first steps toward a scientific biosemiotics. American
Journal of Semiotics, 24, 23–37.
Barbieri, M. (2011a). A mechanistic model of meaning. Biosemiotics, 4(1), 1–4.
Barbieri, M. (2011b). Origin and evolution of the brain. Biosemiotics, 4(3), 369–399.
Bateson, G. (1972 [1969]). Double bind. In Steps to an ecology of mind (pp. 271–278). New York:
Ballantine Books.
Bergman, A., & Siegal, M. L. (2003). Evolutionary capacitance as a general feature of complex gene
networks. Nature, 424, 549–552.
Brier, S. (2003). The cybersemiotic model of communication: an evolutionary view on the threshold
between semiosis and informational exchange. TripleC, 1, 71–94.
Christley, S. Y., Lu, C., Li, C., & Xie, X. (2008). Human genomes as email attachments. Bioinformatics, 25,
274–275.
Crick, F. H. C. (1958). On protein synthesis. Symposia of the Society for Experimental Biology, XII, 139–
163.
Csete, M. E., & Doyle, J. C. (2002). Reverse engineering of biological complexity. Science, 295, 1664–
1669.
Cvrčková, F., Lipavská, H., & Žárský, V. (2009). Plant intelligence: why, why not, or where? Plant
Signalling and Behavior, 4, 394–399.
Deely, J. (2008). Descartes & Poinsot. The crossroads of signs and ideas. Scranton: University of Scranton
Press.
Deely, J. (2009a). Augustine & Poinsot. The protosemiotic development. Scranton: University of Scranton
Press.
Deely, J. (2009b). Pars pro toto from culture to nature: an overview of semiotics as a postmodern
development, with an anticipation of development to come. American Journal of Biochemistry, 25,
167–192.
Deely, J. (2010). Purely objective reality. Berlin: Mouton de Gruyter.
Driesch, H. (1905). Vitalismus als Geschichte und Lehre. Leipzig: Barth.
Heelan, P. A. (1998). The scope of hermeneutics in natural science. Studies in History and Philosophy of
Science, 29, 273–278.
Heidegger, M. (1971 [1950]). The thing. In Poetry, language, thought (pp. 161–184). S. Francisco: Harper.
Jantsch, E. (1979). The self-organizing universe. Pergamon.
Kauffman, S. A. (2000). Investigations. New York: Oxford University Press.
Kimchi-Sarfaty, C., Oh, J. M., Kim, I.-W., Sauna, Z. E., Calcagno, A. M., Ambudkar, S. V., & Gottesman, M. M.
(2007). A “silent” polymorphism in the MDR1gene changes substrate specificity. Science, 315, 525–528.
Lakoff, G. (1987). Women, fire, and dangerous things. What categories reveal about the mind. Chicago
University Press.
Mackay, A. L. (2001). Character-building. Nature, 410, 19. Macroevolution. Springer, 3–14.
Markoš, A., (2002). Readers of the book of life. Conceptualizing evolutionary developmental biology.
Oxford University Press.
The Meaning(s) of Information, Code … and Meaning
Markoš, A. (2010). Biosemiotics and the collision of modernism with the postmodernity. Cognitio (Sao
Paulo), 11, 69–78.
Markoš, A., & Cvrčková, F. (2002). Back to the science of life. Sign System Studies, 30, 129–147.
Markoš, A., & Faltýnek, D. (2011). Language metaphors of life. Biosemiotics, 4, 171–200.
Markoš, A., Grygar, F., Hajnal, L., Kleisner, K., Kratochvíl, Z., & Neubauer, Z. (2009). Life as its own
designer: Darwin’s origin and western thought. Springer.
Markoš, A., & Švorcová, J. (2009). Recorded versus organic memory. Biosemiotics, 2, 131–149.
Reber, P. (2010). What is the memory capacity of the human brain? Scientific American Mind, May 2010.
Rutherford, S. L., & Lindquist, S. (1998). Hsp90 as a capacitor for morphological evolution. Nature, 396,
336–342.
Ruyer, R. (1974). La gnose de Princeton. [The Princeton gnosis]. Paris: Fayard.
Sangster, T. A., Lindquist, S., & Queitsch, C. (2004). Under cover: causes, effects and implications of
Hsp90-mediated genetic capacitance. Bioessays, 26, 348–62.
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(379–
423), 623–656.
Shannon, C. E., Weaver, W. (1949). Mathematical theory of communication. Univ. Illinois Press.
Snow, C. P. (2003 [1957]). The two cultures. Cambridge University Press.
Taipale, M., Jarosz, D. F., & Lindquist, S. (2010). HSP90 at the hub of protein homeostasis: emerging
mechanistic insights. Nature Reviews Molecular Cell Biology, 11, 515–28.
Trewavas, A. (2003). Aspects of plant intelligence. Annals of Botany, 92, 1–20.
Trifonov, E. N. (2008). Codes of biosequences. In M. Barbieri (Ed.), The codes of life. The rules of
macroevolution (pp. 3–14). Springer.
Wang, Y., Liu, D., & Wang, Y. (2003). Discovering the capacity of human memory. Brain and Mind, 4,
189–198.