Presentation used in the first lectures of the course in English "A General Understanding of Information" at the Hochschule München, Germany (WS 2012-13).

1. Philosophy: Philosphy of Information
Fakultät 13, Hochschule München, Wintersemester 2012-2013
Information:
Brücke
zwischen
José María Díaz Nafría (Universidad de León, Spain)
4. März 2011 Informationsphilosophie. Information und urbanes Systeme 1

2. A General Understanding of Information
1. Groundings [Monday-Tuesday]
a) The information age and the language of
information (historical perspective)
b) The Frame of the Mathematical Theory of
Communication
c) Semantic information
2. Information throughout the ladder of
complexity [W.-Th.]
a) Physical information
b) Biological Information
c) Human information (life-world, cultural-world)
3. General Theories of Information [Th.-Fr.]
a) Broadening the mathematical information
concept (complexity theory)
b) Situation theory
c) Information in a nutshell: GTI, UTI
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3. The origins of the information concept
Latin and Greek roots
• Material information case (Hefestos)
• Observation case (Subject)
• Speaking or Instructional case (communication)
Plato’s Forms
• Otherworldliness
• Digital communication model
Aristotle’s Inductions
• Form (actuality) and Matter (potentiality)
• The individuality of real things. Particular
form: essences
• General essences: being of species that can be
inductively grasped
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4. Bibliographic tips
• FLORIDI, L. (2010). Information. A very short introduction. Oxford:
Oxford University Press.
• DÍAZ NAFRÍA, J.M. (2011). Messages in an open universe. in Capurro, R.
and Holgate (eds.). Messages and messangers. Angeletics as an approach
to the phenomenology of of communication. Munich: W.Fink, 195-229.
• DIAZ NAFRIA (2011): Information, a multidimensional reality, in Curras and
Lloret. Nuria LLORET(2011). Systems Science and Collaborative
Information Systems. Hershey PA, USA: IGI Global
• HOFKIRCHNER, W. (2010). Twenty Questions About a Unified Theory of
Information. Arizona: Emergent publications.
• LYRE, Holger (2002). Informationstheorie. Eine philosophisch-
naturwissenschftliche Einführung. Munich: W.Fink Verlag.
• BURGIN, M. (2010). Theory of Information. Fundamentality, Diversity and
Unification. Singapore: World Scientific Publishing.
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5. Bibliographic tips
• DÍAZ NAFRIA, J.M., et al. (Koord.) (2010). Glossarium BITri: glossary of
Concepts, metaphors, theories and problems concerning information.
León: Universidad de León [online
http://glossarium.bitrum.unileon.es/glossary, http://wp.me/pzKNC-66]
• DÍAZ NAFRÍA, J.M. (2010). Information: a multidimensional concern.
TripleC, 8(1), 77-108 [online http://triple-
c.at/index.php/tripleC/article/view/76/168].
• DÍAZ NAFRÍA and SALTO (2009). What is information? An interdisciplinary
approach. Special issue TripleC, 7(2) [online http://wp.me/pzKNC-2G].
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6. Invitation to Complementary Activity
Social networks:
from indignation to change
(ethical, political and aesthetical aspects)
21-23.09.2012 in León, Spain
Cooperation:
Universidad de León – HM – UTI RG – MUSAC
With: Prof. R.E. Zimmermann (HM)
Prof. J.M. Díaz Nafría (ULE)
Prof. P. Fleissner (TUW), et al.
Certificate of assistance, Credits: 1 ECTS, No evaluation
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7. I. Groundings (the development of
the information understanding)
0. Towards a general understanding of
information
1. Development of the information concept:
Plato, Aristotle, Middle Ages, Modernity,
(technique and physics)
2. General understanding of Information
3. Mathematical Theory of Communication
4. Algorithmic Theory of Information
5. Information in the sciences
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8. 0. Towards a General
Understanding of Information
• In the Information Era we should be able to
understand what really information means
(Comparison to the Iron Era, iron vs cupper)
• The Nature of information is not solved
• Information can be considered as something
mediating between Objects and Subjects
• To this end, a general understanding of O. & S.
is also needed.
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9. I.0 Information concept
(tangible)
Information
Time
t1 t2 t3
Object:
In opposition to
the Subject Subject of the change
of the change
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10. (0) Information concept
(immaterial)
Time
Information
t1 t2 t3
Object:
In opposition to
the subject of Subject of the change
the change (awareness) (in the awareness)
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11. (0) Clarifying
• Form: a particular configuration/Gestalt produced in
the subject.
• Subject: System which can adopt potential changes
• Object: what remains stable (in front of the subject)
causing the changes in the subject ~ Model
• Time: Run of the procedure (i.e. change of the
subject)
• O. vs S.: In strict sense, both sides change during the
process (O. & S. are only relative regarding the
corresponding change)
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12. (1) Evolution of the information concept
(a) Plato vs. Aristotle
Plato (idealistic tradition)
• Form is what exists in the first place and it is out of the
world, otherworldliness (a-spatial, a-temporal).
• Forms are participated by appearances (phenomena)
and souls. By these means the observer can really
recognize the forms.
• The innate ideas must be awaken (the observer
recognizes what already was in his soul).
• The observer returns to the truth, slept within himself.
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13. Plato: World of forms
Form Appearance
I
Ideas
Observer
Decontextualizing:
Die existing Forms belong
to the otherworldliness (a-
spatial, a-temporal)
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14. Plato and Signal Theory
• From the viewpoint of the modern signal
theory (Digital Transmission): Ideal of
transparence
Si Si’ Compared with Si
{S1, S2,… SN} {S1, S2,… SN}
Noise
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15. (b) Aristotle
• Form: embrace the essential properties of a
thing
• Matter: embrace the potential changes
• Every thing has its own form, its own essence,
which correspond to its being.
• The reality of a thing relates to its details, its
differences (dish in Plato and Aristotle)
• There is a general being, which corresponds to
the being of the species. One can inductively
recognize them by observation.
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16. (c) Information concept (Middle ages)
Augustine of Hippona: „Credo ut intellego“
Truth Revelation
Requirement:
God Noiseless Belief
channels
Anselm: „Fidens quarens intellectum“
endeavor towards understanding
Aquinas: Reality is understandable
Hermeneutic: Activity of Interpretation, Imagination-Ability
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17. (d) Information concept
(Modernity)
• Reformation and Enlightenment received significantly
the clarity and transparence of Augustine (transparency
≈ unmediated, No distance)
• Physics in that time had control over space, but not over
time -until 19.Century-. Newton:
“Absolute, true, and mathematical time, of itself, and from its own
nature, flows equably without relation to anything external.”
(Scholia to the definitions in PN-Principia Mathematica, Bk. 1, 1689)
• Time was left free to philosophy, where it was not
considered as an independent concept, but as something
inherent to processes (Leibniz, Kant, Heidegger,
Bergson).
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18. (e) Modern Communication theory
• The most important difference between early
and modern telecommunication concerns
transmission speed.
• Until end of the 19th c. I-transmission was
understood as an immediate event:
– The time of the transmission process disappears.
– The mediating space correspondingly disappears,
– One can only speak of the process of the E. and R.,
which must be synchronized.
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19. XIX C. Physics
• Late 19th Century Physics (e.g. Maxwell)
understood the being of time as attached
to processes:
– Entropy represents the irreversibility of
processes (Time: inevitable and
unidirectional run of the processes)
– Physics of fields understood Processes in
Space & Time > Change in the understanding
of EM transmission
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20. Mathematical Theory of
Communication (Shannon)
Original Decoded
message Codified message
Message
Emitter Coder Channel Decoder Receptor
Noise
Noiseless Channels
(magische Kanale)
This viewpoint (and alongside the oblivion of space) have many consequences in
the actual game of the globalization:
1. It technically enables the run of the economical processes at the international
level.
2. It technically enables the hiding of power relations.
3. Instead of facilitating social achievements, the power constellation (economical
domination) can easily reconfigure the network of economic agency.
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21. I.1(g) Computer technique and
Cybernetics, 20th C.
1940s Pioneering work of Alan TURING, J. VON NEUMANN
1950s Machine-model of neuronal systems (McCULLOCH et al.):
Connectionism
40s-60s First Cybernetics (N. WIENER, R. ASHBY) and System Theory
(L. von BERTALANFFY, CHURCHMANN…)
60s-70s Artificial intelligence (NEWELL, SIMON, MINSKY): Symbol
Processing (z.B. LISP) > MACKAY
60s-80s Codification and Pattern recognition (KOLMOGOROV,
SOLOMONOFF, CHAITIN): Theory of complexity and
Algorithmic Information Theory
1970s- Second Cybernetics (MATURANA, VARELA, van FOSTER)
and complexity theory (MORIN, ZIMMERMANN)
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22. Aspects of a general
understanding of information
• Semiotic: Theory of signs and symbols (Morris, 1938)
– The Syntax concerns the occurrence of individual information
units and their mutual relations.
– The Semantic concerns the meaning of information units and
their mutual relations.
– The Pragmatic concerns the effect of information units and
their mutual relations.
A complete understanding of information unfolds in the
dimensions: Syntax, Semantic and Pragmatic
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23. I.2. Aspects of a general
understanding of information
• Timely aspects of information (Weizsäcker):
– Actual: already present and effected information
– Potential: the possibility to obtain actual information.
Namely, the difference between past and future is grasped by
the information concept.
Actual information exists factually, whereas potential
information exist only in relation to possibilities.
Therefore AI can be regarded ontologically, whereas PI is
intrinsically relational.
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24. I.2(a) Syntax and Probability
I = - ld p = - log2 p
Extensive measure:
I-Content of a dual system: I(cont) = I(1) + I(2)
• Probability & potential syntactic information
are equivalent concepts for the quantification
of possibilities.
• The concept of probability can be regarded as a
sub-concept of a general information concept.
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25. (I.2.a) Example: information measurement
through unveiling a card
32 Cards: 8 cards / type (clubs, spades, hearts and diamonds)
1-8 Clubs 1-8 Spades 1-8 Hearts 1-8 Diamonds
Mínimal # of questions –in average- for yes/no answers
Q1: Black?
A1: No
Q2: Heart ?
A2: No
Q3: > 4?
A3: No
Q4: > 2?
A4: Yes
Q5: 4?
A5: Yes
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26. I.2(b) Semantic and Pragmatic
• The necessary entanglement of semantic and pragmatic
aspects of information within semantic-pragmatics
offers the possibility to an objectification of semantics.
• Context always presuppose context, I. always
presuppose I.
• Information exist only relative in respect to a
difference between 2 semantic levels.
• The philosophical key issues in the research of the I-
concept concern the epistemological and ontological
aspects. Both questions are actually interdependent.
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27. I.3. Telecommunication
Information theory
• Shannon’s Information-Entropy
Ii=- log2pi
P={1/2, 1/4, 1/8, 1/8 }; Dice
p1=p; p2=(1-p)
• Theory of codification
In order to transmit the maximal amount of
information content in the minimal time:
Redundancy-free Source (Morse, 4 symbols ex.)
Huffman method: lk~Ik, Prefix-feature
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28. I.3. Telecommunication
Information theory
• Firstness (Erstmäligkeit) and Confirmation
“The word information, in this theory, is used in a special sense
that must not be confused with its ordinary usage. In particular,
information must not be confused with meaning… In fact, two
messages, one of which is heavily loaded with meaning and the
other of which is pure nonsense, can be exactly equivalent, from
the present viewpoint, as regards information... In the theory of
communication, information relates no so much to what is said but
to what could be said. information is a measure of the freedom of
choice communicators have when they select a message.” (Weaver)
The telecommunication I-Theory treats Information
under syntactical aspects
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29. I.3 Telecommunication
Information theory
Is there information without confirmation?
– Phenomenon, manifestation underlying reality
– Perception, stating that something is the case requires
confirmation
– A confirmed phenomenon provides no information
Information
Shannon (MTC)
Pragmatic-semantics
0 1/2 1 Confirmation (Redundancy)
1 0 Firstness (Novelty)
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30. I.4. Semantical approach to
Information
GDI (data + meaning)
σ is an instance of information (understood as semantic information)
if and only if
1) σ consists of n data, for n≥1
2) The data are well formed
3) The wellformed data are meaningful
Dd datum
X being distinct from y, where x and y are 2 uninterpreted variables
and the relation of being distinct as well as the domain are left
open to further interpretation.
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31. I.4. Semantic approach to
Information
Environmental information
2 systems a & b coupled in such a way that a’s being F is correlated
to b being G, then carrying the information for the observer of a the
Information that b is G.
Factual semantic information
p qualifies as factual semantic information if and only if p is
(constituited by) well-formed, meaningful and veridical data
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32. I.4. Algorithmic Information
Theory
• The algorithmic information content is a measure of
the syntactical diversity or complexity
• The very shortest description: Ialg(s)=L(pmin s)
• Differences with the shannonian concept:
1. Syntactic vs. Minimal complexity as usage of that semantic providing
a minimal syntactic effort.
2. Potential vs. Actual Information
3. Objective vs. Relative quantitative concept: Complexity in relation
to regularities that are readable from a selected semantic space.
• The algorithmic I-content measures actual I. under both
syntactic and semantic aspects. It represents no absolute
quantity but a relative one.
• It is not computable, i.e. it is related to subjects.
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33. I.5. The information concept in
the sciences
• Symtem theory (Bertalanffy, Wiener)
• S.S. (Luhmann), B.S. (Maturana u. Varela)
• Th. of open systems (Weizsäcker)
• Linguistics (Chomsky, Eco)
• Economy (N. Georgercu-Roegen)
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34. I.5. The information concept in
the sciences
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35. I.5. The information concept in
the sciences
Objective or subjective?
Relational
concept, Subjective
Ontological category
dependent on: concept
independent
Subjectivity or Intencionality
Release
Uncertainty, Interpretable mechanism
probability Measu- Structure Structure and and Abstract General Human
rement and process behaviour, generating
Evolution
Theory of Ciber-
Objective
nétics Dependent of
Information Biology
Objecti- Semantic Maturana, Varela
General Algorithmic Unified
Wiener MTC Theory of Information Theory of vised Theories of
2nd O. Cibernetics
V. Foerster Relevance
Stonier Karpatschof
Günther Measure Theory Information
Seman- Information Cognitive Decision T.
Gitt tics (Activity Dretske Racionality T.
ment Inf. Hermeneutics
Shannon Theory)
Capurro
Weaber v. Neuman Solomonoff Hoffkirchner
Weizsäcker
Bar-Hillel & Carnap
Situational Intersubj. Knowledge
Kolmogorov Fleissner
Brillouin Lyre (Quantic T. of Inf.) Barwise, Perry, Oeser
Chaitin Fenzl
Mähler Matsuno (Diacronic I.) Seligman, Israel
Lazlo
Truthfulness
Brier (Cibersemiotics) Floridi
mental Difference
Flückiger
Selfreferent. Sist T.
Luhmann
Cognitive Science
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36. I.5. The information concept in
the sciences
Syntactical Semantic Pragmatic Syntactical
How is it expressed? What does it represent? Is it true? What value does it have? How is it expressed?
MTC (Shannon, Logical empiricism (Bar-Hillel, Algorithmic Information Theory (Solomonoff, Kolmogorof, Chaitin)
Weaver) Carnap)
Holographic Universe Cognitive constructivism Theory of purpose-oriented action (Janich)
(Bekenstein) (Dretske)
Quantum Theory of Information Situational semantics (Barwise, Perry, Aesthetic Theory of Information (Bense,
and Measurement (Lyre, Seligman…) Moles)
Mahler…)
Fuzzy semantics (Zadeh, Activity Theory (Karpatschof)
Pérez-Amat…)
Theory of Self-referential Systems (Luhmann)
Objectivised semantics (Weizsäcker, Lyre) Theory of Objective Information (Stonier, Gitt)
Unified Theory of Information (Hoffkirchener, Fleissner, Fenzl, Lazlo, Brier,…)
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37. II. Information in the physics
It is still not a physical concept as E, M, S, T
Central role?
1. Thermodynamics
Principles (1., 2., 3.)
2. Field theory
Appearance and Perception
3. Quantum theory
Measurement theory
4. Space-time Theory
Relativity theory, Quantum Gravity
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38. II.1 Thermodynamics
1. Entropy and 2nd Principle
– (1., 2., 3.) Principles
dS = Qrev/T, dS 0 Qirr irreversible Processes
– BOLTZMANN, MAXWELL, GIBBS: phenomenologic-
macroscopic Th. microscopic-mechanical
– BOLTZMANN (1896): Entropy as quantitative concept:
S = –k B ln p S = –k B piln pi
Information entropy and thermodynamic entropy are formal
identical. Both quantities are equal, if one considers Entropy as
potential Information, as quantity of the number of possible micro-
states in a macro-state.
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39. II.1 Thermodynamics
2. Maxwell’s Daemon
The molecules have the same different average speed
average speed
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40. II.2 Field theory (natural limits of information)
φύσις κρύπτεσθαι φιλεῖ
«Nature loves to hide»
Heraclitus of Ephesus
Bounding surface Structure of the phenomenon
2
2 1 Ψ r, t
Ψ r, t
S
2 2
v t
D
Observed reality
(Object)
Observer
(Subject)
Arbitrary
complexity
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41. II.2 Field theory (natural limits of information)
Phenomena
Wavefunction
1 1
G ( u 1 , v1 , x n , y n , z n )
N N
Ψ   fn ψn fn T f wo ψ n 
n 1 n 1
M M
G (u M , v M , x n , y n , z n )
Source:
(Real or predicted equivalent)
What is the complexity of the phenomenon?
Namely, haw much information does it convey?
1) The solution is univocal only for a discrete
projections over a given bounding surface.
2) The details are regularly distributed (~λ/2)
3) The highest gathered information does not Bounding surface
(Huygens Principle)
depend on the accuracy of the observation but on
the dimension of the ψ ( a2)
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42. II.2 Field theory (natural limits of information)
Observation domain z 1) The field of an arbitrary structure is computed
Arbitrary on an observed domain.
structure 2) From this „observation“ a projection over the
perfect polyhedron is determined.
3) The field of both the original structure and the
E projected in the prediction domain are equal.
a E
Domain of Domain of observation
prediction
x y
Polyedron of
projection
Uniqueness solution for the selected projection distribution
1
f Projection [T T ] T Ψ OBS
/ min d T f Projection , Ψ OBS
f Domain of prediction
Trans-Operator: f → ψ
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43. II.2 Field theory (natural limits of information)
Trans-Operator: s → ψ
Projection-Operator: ψ → s
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44. II.3 Quantum theory (Limits of information)
It is possible to speak of potential and actual (Weizsäcker)
Zeit
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45. (II. Appendix) Perception: Consequences of
the physical limits in the human perception
a) regular hole or irregular coloured b) irregular protuberance or regular
protuberance coloured hole
• The preferred perceptions tend to be those corresponding
to the simplest configurations (Ockam’s razor)
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46. (II. Appendix) Perception
Examples of ambiguos perception
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47. (II. Appendix) Perception
Solution of ambiguities
Initial hypothesis
G1-1 G2-1 G3-1 GN-1
k k k k ●●● k
Ob{ Ψ 1 } Ob{ Ψ 2 } K{ s } Ob{ Ψ 3 } Ob{ Ψ N }
G1 G2 k k 1
G3 GN
d {s , s }
N N N
f , Ψ1 ... ΨN
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48. III. Information in Biology
The actual decoding of human genome brings in
biology the information theoretical aspects to the
fore
1. Genetics
Theory of heritage, Molecular-biology
2. Evolution theory
Appearance and Perception
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49. III.0 Historical remarks
Darwin: “tiny germs” / mutations
Galton: „lineages“ (used in ontogenesis)
Mendel (1856): a carrier for every individual
character
Correns, Tschermark, and de Vries
rediscover the heritage theory, Molecular biology
Miescher (1869): nucleotide of cell kernel (DNA).
Müller (1925, Mutations of Drosophila)
Bateson: “Genetics“, Johannensen: “Gen“
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50. III.0 Historical remarks
Avery (1944): Transformations as f(DNA)
Hershey and Chase: experiment with bacteriophagus
Schrödiger (1944): „a-periodical crystal“
Watson and Crick: Nature of the DNA Molecule
Not the chemistry of the DNA but the molecular structure:
Information theoretical paradigm
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51. III.1 Genetics
Transcription Translation
DNA RNA Polypeptid
Replication Since discovery
of Retrovieren
• Central dogma of the molecular biology
• 4 Bases:
(A) Adenine, (G) Guanine, (T) Thymine, (C) Cytosine
• Chargaff’s rules: {A & T}, {G & C} equivalent molar amounts
The DNA heritage-molecule represents in its nucleotide-
structure a genetic code –i.e. syntactical information- for the
production of RNA and Proteins.
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