Dear FISers,
There is 'something' in Terry's approach that I would like to refer to as
wisdom. Wisdom need not be thought of as esoteric, but to describe at least one
further level of recursive information processing in which, echoing Terry,
absent properties are as essential as present ones. In my conception, absent
means not only what is 'not there', but also what is repressed, potentialized,
temporarily forgotten, ignored, devalued or minimized. This is just a tiny bit
of what 'higher-order' properties and an inversion of perspective might involve.
Best Season's and New Year's Greetings,
Joseph
----- Original Message -----
From: Terrence W. DEACON
To: Francesco Rizzo
Cc: fis
Sent: Saturday, December 24, 2016 7:22 PM
Subject: Re: [Fis] What is information? and What is life?
Dear colleagues,
I am entirely in agreement with the sentiments about mutual respect that Loet
recommends and the "harmony of knowledge" that Francesco promotes. But I
believe that this must also include a willingness to recognize that there isn't
a most basic theory; only what we might characterize as a currently most
thoroughly worked out analysis. But this is an analysis at the most stripped
down level—and which therefore necessarily ignores much that is essential to a
fuller analysis of information.
In this respect Loet comments:
"In my opinion, the status of Shannon’s mathematical theory of information is
different from special theories of information (e.g., biological ones) since
the formal theory enables us to translate between these latter theories."
We are essentially in agreement, and yet I would invert any perspective that
prioritizes the approach pioneered by Shannon. This analysis of the signal
properties that are necessary for conveying information does not attempt to
address the "higher order" properties that we pay attention to in domains where
reference and functional value are relevant (e.g. biology, neuroscience,
sociology, art). It necessarily brackets these aspects from consideration. It
thereby provides a common necessary but not sufficient tool of analysis. More
than a half century of development along these lines has demonstrated that
there are critical features of the information relationship that cannot be
reduced to intrinsic signal properties.
I have argued that there are basically two higher-order general properties that
constitute information: the referential relation and the normative/functional
value relation (with the term 'meaning' often used somewhat ambiguously to
refer to one or both of these properties). I do not assume that these
completely characterize all higher-order properties, and so I would be open to
discussing additional general attributes that fall outside these domains, and
which we need to also consider.
So I am not a fan of prioritizing the statistical conception of information and
considering all others to be "special" theories.
My hope for the field is that we will continue to work toward formalization of
these higher-order properties with the aim of embedding our current "signal
property analysis" within this larger theory. In this respect, I would argue
that the "mathematical theory" as currently developed is in fact a "special
theory," restricted to analyses where reference and functional significance can
be set aside (as in engineering applications), and that the "general theory"
remains to be formulated.
Since its inception, it has been recognized that the "mathematical theory of
communication" has used the term 'information' in a highly atypical sense. I
think that we would do well to keep this historical "accident" in mind in order
to avoid "information fundamentalism." This demands a sort of humility in the
face of the enormity of the challenge before us, not merely a tolerance of
"special" domains of application that don't completely reduce to statistical
analysis.
My proposal is that agreeing on terminological distinctions that support such a
paradigm inversion might provide a first step toward theoretical convergence
toward a "general theory" of information. I would welcome such a discussion in
the new year.
Happy holidays to all, Terry
On Sat, Dec 24, 2016 at 2:22 AM, Francesco Rizzo <13francesco.ri...@gmail.com>
wrote:
Cari Tutti,
ho scritto più volte le stesse cose per cui sono d'accordo con Voi,
specialmente con gli ultimi intervenuti. E dato che sono un forestiero rispetto
alle Vostre discipline, ma non uno straniero dell'armonia del sapere o del
sapere dell'armonia, questo è una bella cosa. Auguri di buon Natale e per il
nuovo anno.
Francesco
2016-12-24 7:45 GMT+01:00 Loet Leydesdorff <l...@leydesdorff.net>:
Dear Terrence and colleagues,
I agree that we should not be fundamentalistic about “information”. For
example, one can also use “uncertainty” as an alternative word to Shannon-type
“information”. One can also make distinctions other than
semantic/syntactic/pragmatic, such as biological information, etc.
Nevertheless, what makes this list to a common platform, in my opinion, is
our interest in the differences and similarities in the background of these
different notions of information. In my opinion, the status of Shannon’s
mathematical theory of information is different from special theories of
information (e.g., biological ones) since the formal theory enables us to
translate between these latter theories. The translations are heuristically
important: they enable us to import metaphors from other backgrounds (e.g.,
auto-catalysis).
For example, one of us communicated with me why I was completely wrong, and
made the argument with reference to Kullback-Leibler divergence between two
probability distributions. Since we probably will not have “a general theory”
of information, the apparatus in which information is formally and
operationally defined—Bar-Hillel once called it “information calculus”—can
carry this interdisciplinary function with precision and rigor. Otherwise, we
can only be respectful of each other’s research traditions. J
I wish you all a splendid 2017,
Loet
----------------------------------------------------------------------------
Loet Leydesdorff
Professor, University of Amsterdam
Amsterdam School of Communication Research (ASCoR)
l...@leydesdorff.net ; http://www.leydesdorff.net/
Associate Faculty, SPRU, University of Sussex;
Guest Professor Zhejiang Univ., Hangzhou; Visiting Professor, ISTIC,
Beijing;
Visiting Professor, Birkbeck, University of London;
http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en
From: Fis [mailto:fis-boun...@listas.unizar.es] On Behalf Of Terrence W.
DEACON
Sent: Thursday, December 22, 2016 5:33 AM
To: fis
Subject: Re: [Fis] What is information? and What is life?
Against information fundamentalism
Rather than fighting over THE definition of information, I suggest that we
stand back from the polemics for a moment and recognize that the term is being
used in often quite incompatible ways in different domains, and that there may
be value in paying attention to the advantages and costs of each. To ignore
these differences, to fail to explore the links and dependencies between them,
and to be indifferent to the different use values gained or sacrificed by each,
I believe that we end up undermining the very enterprise we claim to be
promoting.
We currently lack broadly accepted terms to unambiguously distinguish these
divergent uses and, even worse, we lack a theoretical framework for
understanding their relationships to one another.
So provisionally I would argue that we at least need to distinguish three
hierarchically related uses of the concept:
1. Physical information: Information as intrinsically measurable medium
properties with respect to their capacity to support 2 or 3 irrespective of any
specific instantiation of 2 or 3.
2. Referential information: information as a non-intrinsic relation to
something other than medium properties (1) that a given medium can provide
(i.e. reference or content) irrespective of any specific instantiation of 3.
3. Normative information: Information as the use value provided by a given
referential relation (2) with respect to an end-directed dynamic that is
susceptible to contextual factors that are not directly accessible (i.e.
functional value or significance).
Unfortunately, because of the history of using the same term in an
unmodified way in each relevant domain irrespective of the others there are
often pointless arguments of a purely definitional nature.
In linguistic theory an analogous three-part hierarchic partitioning of
theory IS widely accepted.
1. syntax
2. semantics
3. pragmatics
Thus by analogy some have proposed the distinction between
1. syntactic information (aka Shannon)
2. semantic information (aka meaning)
3. pragmatic information (aka useful information)
This has also often been applied to the philosophy of information (e.g. see
The Stanford Dictionary of Philosophy entry for ‘information’). Unfortunately,
the language-centric framing of this distinction can be somewhat misleading.
The metaphoric extension of the terms ‘syntax’ and ‘semantics’ to apply to
iconic (e.g. pictorial) or indexical (e.g. correlational) forms of
communication exerts a subtle procrustean influence that obscures their
naturalistic and nondigital features. This language bias is also often
introduced with the term ‘meaning’ because of its linguistic connotations (i.e.
does a sneeze have a meaning? Not in any standard sense. But it provides
information “about” the state of person who sneezed.)
So as a first rough terminological distinction I propose using
1. physical information (or perhaps information1)
2. referential information (information2)
3. normative information (information3)
to avoid definitional equivocation and the loss of referential clarity.
I would argue that we use the term ‘information’ in a prescinded way in
both 1 and 2. That is, considered from the perspective of a potential
interpretation (3) we can bracket consideration of any particular
interpretation to assess the possible relational properties that are available
to provide reference (2); and we can bracket both 3 and 2 to only consider the
medium/signal properties minimally available for 2 and 3 irrespective of using
them for these purposes.*
Although 2 and 3 are not quantifiable in the same sense that 1 is, neither
are they unconstrained or merely subjective. The possible referential content
of a given medium or sign vehicle is constrained by the physical properties of
the medium and its relationship to its physical context. Normative information
captures the way that referential content can be correct or incorrect, accurate
or inaccurate, useful or useless, etc., depending on the requirements of the
interpretive system and its relation to the context. In both cases there are
specific unambiguously identifiable constraints on reference and normative
value.
There has been a prejudice in favor of 1 because of the (mistaken) view
that 2 and three are in some deep sense nonphysical and subjective. Consistent
with this view, there have been many efforts to find a way to reduce 2 and 3 to
some expression of 1. Although it is often remarked that introducing non
reduced concepts of referential content (2) and normative evaluation (3) into
the theory of information risks introducing non quantifiable (and by assumption
non scientific) attributes, I think that this is more a prejudice than a
principle that has been rigorously demonstrated. Even if there is currently no
widely accepted non reductionistic formalization of reference and significance
within the information sciences this is not evidence that it cannot be
achieved. One thing is clear, however, until we find a way to use the term
‘information’ in a way that does not privilege one of these uses over the
others and unequivocally distinguishes each and their relationships to one
another, the debates we engage in on this forum will remain interminable.
So I suggest that we commence a discussion of how best to accomplish this
terminological brush-clearing before further debating the relevance of
information to physics, logic, biology, or art. I apologize if this is already
accepted as “solved” by some readers, and would be glad to receive and share
your different taxonomies and learn of how they are justified.
— Terry
* Stan Salthe might organize them in a subsumptive hierarchy.
On Tue, Dec 20, 2016 at 4:19 PM, Mark Johnson <johnsonm...@gmail.com> wrote:
Dear all,
It's important that one should remain practical. Shannon's formulae are
practical. The correspondence with certain tenets of cybernetics such as
Ashby's Law, or Maturana's "Structural Coupling" presents Shannon as a window
for exploring *relations* empirically. This I understand to be Bob Ulanowicz's
focus too. I think Ashby's epistemology which accompanied his championing of
Shannon (and which seems to me to be quite radical) is worth a much deeper
exploration (it was eclipsed by second-order cybernetics in the early 70s).
Klaus Krippendorff wrote an excellent paper about this here:
http://repository.upenn.edu/cgi/viewcontent.cgi?article=1245&context=asc_papers
Information theory is counting - but it provides a way of measuring
relations, which I think marks it out as distinct from other statistical
techniques such as variance. It also provides the basis for questioning what we
actually mean by counting in the first place: you might call it "critical
counting". For example, Ashby makes the comment about "analogy" (a key concept
if we are to say that one thing is the same class as another when we count them
together)... (apologies because I can't find the reference to this right now,
but will send if anyone is interested):
"The principle of analogy is founded upon the assumption that a degree of
likeness between two objects in respect of their known qualities is some reason
for expecting a degree of likeness between them in respect of their unknown
qualities also, and that the probability with which unascertained similarities
are to be expected depends upon the amount of likeness already known."
Also, just to correct a possible misconception: I don't think counting
leads to populism. Econometrics has led to populism. Some of the greatest
economists of the 20th century saw the problem - this is why Keynes wrote a
book on probability, and Hayek wrote extensively criticising mathematical
modelling. In the end, I'm afraid, it's an American problem which goes back to
McCarthy and the distrust of criticality in the social sciences in favour of
positivist mathematical "objectivist" approaches. Those schools in the US which
championed mathematical approaches (Chicago, etc) got all the funding,
controlled the journals, whilst others were starved. The legacy from the 1950s
is still with us: it's still very hard to get an economics paper published
unless it's got crazy equations in it. In the end, it's just bad theory - and
bad mathematics.
We could well see a similar thing happen with climate science in the next
four years.
Best wishes,
Mark
On 20 December 2016 at 19:55, Bob Logan <lo...@physics.utoronto.ca> wrote:
Loet - thanks for the mention of our (Kauffman, Logan et al) definition our
definition of information which is a qualitative description of information. As
to whether one can measure information with our description, my response is no
but I am not sure that one can measure information at all. What units would one
use to measure information? E = mc 2 contains a lot of information but the
amount of information depends on context. A McLuhan one-liner such as 'the
medium is the message' also contains a lot of information even though it is
only 5 words or 26 characters long.
Hopefully I have provided some information but how much information is
impossible to measure.
Bob
______________________
Robert K. Logan
Prof. Emeritus - Physics - U. of Toronto
Fellow University of St. Michael's College
Chief Scientist - sLab at OCAD
http://utoronto.academia.edu/RobertKLogan
www.researchgate.net/profile/Robert_Logan5/publications
https://www.physics.utoronto.ca/people/homepages/logan/
On Dec 20, 2016, at 3:26 AM, Loet Leydesdorff <l...@leydesdorff.net> wrote:
Dear colleagues,
A distribution contains uncertainty that can be measured in terms of bits
of information.
Alternatively: the expected information content H of a probability
distribution is .
H is further defined as probabilistic entropy using Gibb’s formulation of
the entropy .
This definition of information is an operational definition. In my opinion,
we do not need an essentialistic definition by answering the question of “what
is information?” As the discussion on this list demonstrates, one does not
easily agree on an essential answer; one can answer the question “how is
information defined?” Information is not “something out there” which “exists”
otherwise than as our construct.
Using essentialistic definitions, the discussion tends not to move forward.
For example, Stuart Kauffman’s and Bob Logan’s (2007) definition of information
“as natural selection assembling the very constraints on the release of energy
that then constitutes work and the propagation of organization.” I asked
several times what this means and how one can measure this information.
Hitherto, I only obtained the answer that colleagues who disagree with me will
be cited. J Another answer was that “counting” may lead to populism. J
Best,
Loet
----------------------------------------------------------------------------
Loet Leydesdorff
Professor, University of Amsterdam
Amsterdam School of Communication Research (ASCoR)
l...@leydesdorff.net ; http://www.leydesdorff.net/
Associate Faculty, SPRU, University of Sussex;
Guest Professor Zhejiang Univ., Hangzhou; Visiting Professor, ISTIC,
Beijing;
Visiting Professor, Birkbeck, University of London;
http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en
From: Dick Stoute [mailto:dick.sto...@gmail.com]
Sent: Monday, December 19, 2016 12:48 PM
To: l...@leydesdorff.net
Cc: James Peters; u...@umces.edu; Alex Hankey; FIS Webinar
Subject: Re: [Fis] What is information? and What is life?
List,
Please allow me to respond to Loet about the definition of information
stated below.
1. the definition of information as uncertainty is counter-intuitive
("bizarre"); (p. 27)
I agree. I struggled with this definition for a long time before realising
that Shannon was really discussing "amount of information" or the number of
bits needed to convey a message. He was looking for a formula that would
provide an accurate estimate of the number of bits needed to convey a message
and realised that the amount of information (number of bits) needed to convey a
message was dependent on the "amount" of uncertainty that had to be eliminated
and so he equated these.
It makes sense to do this, but we must distinguish between "amount of
information" and "information". For example, we can measure amount of water in
liters, but this does not tell us what water is and likewise the measure we use
for "amount of information" does not tell us what information is. We can, for
example equate the amount of water needed to fill a container with the volume
of the container, but we should not think that water is therefore identical to
an empty volume. Similarly we should not think that information is identical
to uncertainty.
By equating the number of bits needed to convey a message with the "amount
of uncertainty" that has to be eliminated Shannon, in effect, equated opposites
so that he could get an estimate of the number of bits needed to eliminate the
uncertainty. We should not therefore consider that this equation establishes
what information is.
Dick
On 18 December 2016 at 15:05, Loet Leydesdorff <l...@leydesdorff.net> wrote:
Dear James and colleagues,
Weaver (1949) made two major remarks about his coauthor (Shannon)'s
contribution:
1. the definition of information as uncertainty is counter-intuitive
("bizarre"); (p. 27)
2. "In particular, information must not be confused with meaning." (p. 8)
The definition of information as relevant for a system of reference
confuses information with "meaningful information" and thus sacrifices the
surplus value of Shannon's counter-intuitive definition.
information observer
that integrates interactive processes such as
physical interactions such photons stimulating the retina of the eye,
human-machine interactions (this is the level that Shannon lives on),
biological interaction such body temperature relative to touch ice or heat
source, social interaction such as this forum started by Pedro, economic
interaction such as the stock market, ... [Lerner, page 1].
We are in need of a theory of meaning. Otherwise, one cannot measure
meaningful information. In a previous series of communications we discussed
redundancy from this perspective.
Lerner introduces mathematical expectation E[Sap] (difference between of a
priory entropy [sic] and a posteriori entropy), which is distinguished from the
notion of relative information Iap (Learner, page 7).
) expresses in bits of information the information generated when the a
priori distribution is turned into the a posteriori one . This follows within
the Shannon framework without needing an observer. I use this equation, for
example, in my 1995-book The Challenge of Scientometrics (Chapters 8 and 9),
with a reference to Theil (1972). The relative information is defined as the
H/H(max).
I agree that the intuitive notion of information is derived from the Latin
“in-formare” (Varela, 1979). But most of us do no longer use “force” and “mass”
in the intuitive (Aristotelian) sense. J The proliferation of the meanings of
information if confused with “meaningful information” is indicative for an
“index sui et falsi”, in my opinion. The repetitive discussion lames the
progression at this list. It is “like asking whether a glass is half empty or
half full” (Hayles, 1990, p. 59).
This act of forming forming an information process results in the
construction of an observer that is the owner [holder] of information.
The system of reference is then no longer the message, but the observer who
provides meaning to the information (uncertainty). I agree that this is a
selection process, but the variation first has to be specified independently
(before it can be selected.
And Lerner introduces the threshold between objective and subjective
observes (page 27). This leads to a consideration selection and cooperation
that includes entanglement.
I don’t see a direct relation between information and entanglement. An
observer can be entangled.
Best,
Loet
PS. Pedro: Let me assume that this is my second posting in the week which
ends tonight. L.
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