A video recording of the presentation of this talk is linked from here:
(The presentation used an earlier version of these notes.)
The words "Matter", "Energy" and "Information", in the sense used here, cannot be explicitly defined but are implicitly defined by the theories that use the words, and the ways in which the theories are applied and tested.
Don't assume that the concepts we have now will prove adequate in the long run. Compare what happened to concepts of force, weight and mass between Newton and Einstein.
As regards information I think our concepts and theories are still VERY primitive.
Moreover research communities are dreadfully fragmented, using different systems of concepts with superficial overlaps at a verbal level.
E.g. am I the only person in this room interested in how evolution produced mathematical abilities like those of Euclid and Archimedes?
Or whether mathematical competences of humans fit Kant's theories about mathematical knowledge?
There's a vast amount of conceptual confusion and discussion/debate at cross-purposes.
--- and far too much mutual ignorance.
(That's a social, educational problem.)
There is much to be said about that -- some of it written by Schrödinger in
What is life? (1944).
(Annotated extracts from the book are available here.)
Evolution acquires information about opportunities, constraints, and possible designs for all sorts of organism.
How it does that keeps changing: one of the results of evolution.
I want to investigate ways in which evolution changes what individual organisms (or subsystems of organisms) can do with information, of many kinds:
Let's focus on acquisition and use of information by individual organisms, during their life, e.g. rather than information in the genome, and how that is acquired and used.
In particular organisms are able to acquire acquire "modal" information: information about what is and is not possible, and information about necessary consequences of realisation of some possibilities, i.e. mathematical information, e.g. the sorts of discoveries reported by Euclid, some of which individuals can easily make for themselves, e.g.
If a triangle has three equal sides then it must have three equal angles
Information about geometry and topology recorded by Euclid (and his predecessors and successors) has NOTHING to do with probabilities, which happen to be the main focus of most fashionable research on intelligent systems.
Going back to earlier organisms: evolution produced organisms able to acquire
and use more and more varieties of information:
- immediately usable control information
- information that can be used after it is acquired
- information about an need to seek new information
- information about extended terrain, not just immediate environment
- information about what is where even when it is not being perceived, and how to get to some items even when they are not perceived (e.g. learnt routes to sources of food, liquid, shelter, danger, etc.).
- We know how to make machines that can acquire and use some types of information, but not others: e.g. information about what is possible or impossible, e.g. theorems in Euclidean geometry and topology.
- Some examples of uses of information by animals and machines (Big Dog, by Boston Dynamics).
I am not using "information" in Shannon's sense: he realised too late that by using that word he had succeeded in confusing many people.
The older concept of information (e.g. used by Jane Austen in 1813) refers to something that is USED. There need not be any sender or receiver involved.
How information is stored or transmitted and the mechanisms required for storage and transmission are important questions, but not as important as:
While walking along a forest path, I may see that a tree has fallen across the path.
I then have information that my path is blocked, which I can use.
If I am about to turn back and go home I may not make use of the information, but if I want to continue on my way I may also acquire information that I could climb over the tree, or that I could go round the tree.
A bird, an insect, an elephant could also acquire information relating to the tree, but they would get different information.
If I see a beetle on the bark of the tree I can use the information acquired to control an action, e.g. delicately picking up the beetle, or moving down to peer at it.
The information acquired can trigger the formation of an intention.
The content of the intention may be
-- to get my finger and thumb on either side of the beetle,
-- to gently move them together so that I can pick up the beetle without
-- bring it to a position where I can inspect it visually,
-- in order to get more information about its shape, colour, etc.
-- and if I were an entomologist I might also be able to identify the
species, whether it is male or female, etc.
The information in the intention can control an action, in collaboration with additional visual information acquired at different times.
Many uses of information do not involve ANY use of probabilities, though as I move my hand I can get information about how to adjust the motion in order to bring finger and thumb on opposite sides of the beetle.
If I put the beetle in a box, that may remind me of Wittgenstein, though not because of any probability relation, or regular correlation.
Information acquired visually from a GO board or a chess board will be very different: using a different ONTOLOGY, including different RELATIONS, different POSSIBILITIES, different CONSTRAINTS.
Different views about visual information. Examples:
MARR: information about visible surfaces, distances, curvature, orientation, colour, illumination, etc.
BARROW AND TENENBAUM: Recovering intrinsic scene characteristics from images
GIBSON: what the perceiver can or cannot do, given its capabilities, needs, current knowledge etc.
GENERALISE GIBSON: information about what is possible or impossible in the environment, whether relevant to the perceiver's needs or abilities, or not.
NB: enormous complications if things are moving: huge explosion of possibilities.Things that can change include
types of motion
types of causal interaction (pushing, pulling, twisting, ...)
types of possibility,
types of constraint constraint,
I claim: what Shannon did is very important for engineering applications
involving storage or transmission of data, or minimising loss due to equipment
failures, noise, etc., but has nothing to do with intelligent action: several
research communities have been misled -- including many researchers in robotics
and artificial intelligence.
In 'Computing machinery and intelligence',
Mind, 59, 1950, Turing wrote:
"In the nervous system chemical phenomena
are at least as important as electrical"
Two years later he published:
The Chemical Basis Of Morphogenesis, in
Phil. Trans. R. Soc. London B 237, 237, pp. 37--72, 1952,
[NASA artist's impression of a protoplanetary disk, from WikiMedia]
By starting from a very powerful construction kit: physics+chemistry, and using natural selection to produce many branching layers of information-processing machinery, required for new forms of reproduction, new forms of development, new forms of intelligence, new forms of social/cultural evolution, via new types of construction kit.
As Turing seems to have realised: the forms of information-processing used were richer and more varied than those developed by computer scientists and engineers so far, and made essential use of chemistry.
(These notes will be expanded later. The presentation, in the video, used
an earlier version of this page, plus some local images and videos on my
Modality Possible Impossible Necessary Contingent Items needing structured internal information contents: questions, intentions, plans, hypothesis ... control information Introduction of theoretical terms Example videos: monkey-leap-MAH09900.webm parrot_using_tool.mov BBC_Home_Making_Weaver_Bird_medium.webm crow-movies/bending_trial7.wmv baby-on-rug Toddler with toy train (hooks and rings) WARNEKEN and TOMASELLO children_cabinet.mpg [Their focus is demonstrating that very young (e.g. pre-verbal) children can be spontaneously altruistic. My focus is on how pre-verbal children can *represent* information about the contents of the minds of others, including their beliefs, their lack of information, their intentions and states of affairs that will satisfy the inferred needs/goals of others.] BROOM broomshots/*.png fetched/josh-with-broom.mpg TRAIN child_train_hooks.mpg July 2003 about 19 months Baby_elephant_help_me_out_of_the_waterhole_medium.webm BigDog.wmv (Boston Dynamics) BIRDS HummingbirdBuildingNest.mp4 crow-movies/first_bend.wmv WARNEKEN and TOMASELLO children_cabinet.mpg children_flap.mpg children_books.mpg PENCIL http://www.cs.bham.ac.uk/research/projects/cogaff/movies/vid/pencil-video-cropped.mp4 GENERALISING WADDINGTON'S EPIGENETIC LANDSCAPE http://www.cs.bham.ac.uk/~axs/fig/evol-behav-rec-buffer.jpg CELL MACHINERY flashgot/cell-machinery/innerHi_BiovisionHighRes3.flv http://multimedia.mcb.harvard.edu/anim_innerlife_hi.html David_Bolinsky_Fantastic_voyage_inside_a_cell.flv
Last Updated: 25 Jul 2016
More information may be added later.
School of Computer Science
The University of Birmingham