Re: [asa] Information and knowledge

*Communication theory deals with syntax and only syntax. Design is a
semantic concept and not a syntactical one. Application of Shannon or any
derivatives of Shannon tells us nothing about design because it deals only
with syntax. ID's application of communication theory to infer intelligent
design is thus a category error.*
**
True, if you delineate those categories as strictly and narrowly as you
have. But that kind of sharp deliniation appears to be arbitrary. Floridi
notes that it is not at all clear where, if anywhere, the break betwees
syntactic and semantic information comes. In fact, he suggests that
communications theory (syntactic information) might "supply the necessary
conditions" for the theory of semantic information. He distinguishes
reductionist and non-reductionist approaches to a "unified theory of
information":

 The reductionist approach holds that we can extract what is essential to
understanding the concept of information and its dynamics from the wide
variety of models, theories and explanations proposed. The non-reductionist
argues that we are probably facing a network of logically interdependent but
mutually irreducible concepts.

It seems to me, then, that none of this is as neat and clean as you would
like. "Syntactic" and "semantic" information may be deeply related
concepts, not entirely separate categories.

Where I agree with you is in the view that the strong ID program based on
communications theory claims to prove too much. In the sense that
communications theory cannot "prove" the existence of God, I agree there is
a category mistake -- but it is between the category of empirical modeling
of communications channels and the category of the metaphysics of being. ID
tries to avoid this problem by arguing that the "designer" need not be God
-- essentially, the "designer" can be any intelligent information source.
Tied with the idea that information is ontologically separate from energy
and matter, it seems to me that this results in a "designer / God" that *is*
*in essence* "information." My biggest beef with this aspect of the strong
ID program, then, is really a theological one: it seems to reduce God to a
data stream that is ontologically part of the creation.

In more detail, Floridi summarizes different perspectives on "information"
and how they might ultimately be unified (or not) as follows:

Information is often approached from three perspectives: information as
reality (e.g. as patterns of physical signals, which are neither true nor
false), also known as *ecological *information; information about reality
(semantic information, which is alethically qualifiable and an ingredient in
the constitution of knowledge); and information for reality (instruction,
like genetic information, algorithms and recipes). Many extensionalist
approaches to the definition of information as/about reality provide
different starting points. The following list contains only some of the most
philosophically interesting or influential, and I shall say a bit more about
each of them presently. They are not to be taken as necessarily alternative,
let alone incompatible:

    1. 1. the communication theory approach (mathematical theory of
   codification and communication of data/signals (Shannon and Weaver [1949
   rep. 1998]; see also the chapter by Topsøe and Harremoës) defines
   information in terms of probability space distribution;

    2. 2. the algorithmic approach (also known as Kolmogorov complexity,
   Li and Vitâanyi [1997]; see also the chapters by Grunwald and Vitâanyi and
   by Adriaans) defines the information content of *X *as the size in
   bits of the smallest computer program for calculating *X *(Chaitin
   [2003]);

    3. 3. the probabilistic approach (Bar-Hillel and Carnap [1953],
   Bar-Hillel [1964], Dretske [1981]; see also the chapter by Dretske), is
   directly based on (1) above and defines semantic information in terms of
   probability space and the inverse relation between information in *p *and
   probability of *p*;

    4. 4. the modal approach defines information in terms of modal space
   and in/consistency (the information conveyed by *p *is the set of
   possible worlds excluded by *p*);

    5. 5. the systemic approach (situation logic, Barwise and Perry
   [1983], Israel and Perry [1990], Devlin [1991]) defines information in terms
   of states space and consistency (information tracks possible transitions in
   the states space of a system);

 6. the inferential approach defines information in terms of inferences
space (information depends on valid inference relative to a person's theory
or epistemic state); 7. the semantic approach (Floridi [2004c], Floridi
[2005b]) defines information in terms of data space (semantic information is
well-formed, meaningful and truthful data).

Each extentionalist approach can be given an intentionalist reading by
interpreting the relevant space as a doxastic (i.e. belief-related) space,
in which information is seen as a reduction in the degree of uncertainty or
level of surprise given a state of knowledge of the informee (see the
chapters by Baltag, Moss and van Ditmarsch and by Rott).

Communication theory in (1) approaches information as a physical phenomenon,
syntactically. It is not interested in the usefulness, relevance, meaning,
interpretation or reference of data, but in the level of detail and
frequency in the uninterpreted data (signals or messages). It provides a
successful mathematical theory because its central question is whether and
how much data, not what information is conveyed.

The algorithmic approach in (2) is equally quantitative and solidly based on
probability theory. It interprets information and its quantities in terms of
the computational resources needed to specify it.

The remaining approaches all address the question "what is *semantic
*information?".
They seek to give an account of information as semantic content, usually
adopting a propositional orientation (they analyse examples like "The earth
has only one moon"). Do (1) or (2) provide the necessary conditions for any
theory of semantic information in (3)-(7)? Are all the remaining semantic
approaches mutually compatible? Is there a logical hierarchy? Do any of the
previous approaches provide a clarification of the notion of data as well?
Most of the problems in PI acquire a different meaning depending on how we
answer this cluster of questions. Indeed, positions might be more compatible
than they initially appear owing to different interpretations of the
concept(s) of information involved.

On 4/13/07, Rich Blinne <rich.blinne@gmail.com> wrote:
>
>
>
> On 4/13/07, David Opderbeck <dopderbeck@gmail.com> wrote:
> >
> >
>
> I do not, however, entirely agree with this. The mathematics of
> information theory have potential philosophical consequences. Read the
> blurb from Floridi and check out his resources on Philosophy and Ethics of
> Information. It's a burgeoning field that has nothing directly to do with
> ID, and it most certainly draws on Shannon, Weiner, etc.
>
> Floridi correctly identifies what he calls communication theory and the
> rest of the world calls information theory deals with syntactic information.
> There are other theories that deal with semantic information which he
> unfortunately also calls "information". Since the word information is being
> equivocated here I will just proceed with using the terms communication
> theory, syntax, and semantics. Communication theory deals with syntax and
> only syntax. Design is a semantic concept and not a syntactical one.
> Application of Shannon or any derivatives of Shannon tells us nothing about
> design because it deals only with syntax. ID's application of communication
> theory to infer intelligent design is thus a category error. The irony of
> this should not escape anyone because a category error is a
> syntactically correct statement that is semantically meaningless.
>
>

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Received on Fri Apr 13 16:23:41 2007