---

---

NOTES FOR TALK
Cogs Seminar Presentation Sussex University
16th Feb 2021

Chemistry vs neurones -- pre- and post-natal spatial intelligence, in chickens, foals, and mathematicians!

Speaker: Aaron Sloman
Honorary Professor of AI and Cognitive Science
School of Computer Science
University of Birmingham, UK
http://www.cs.bham.ac.uk/~axs
School of Computer Science, University of Birmingham, UK

SPEAKER: Aaron Sloman BACKGROUND NOTE: I am very pleased to have this opportunity to present the latest developments in a line of research pursued at Sussex University from 1964 to 1991, extending my thesis work in Oxford, where I switched from mathematics to philosophy, in order to defend Kant's philosophy of mathematics against commonplace but misguided criticisms by philosophers. logicians and mathematicians. This talk continues that theme. EXTENDED ABSTRACT: I'll offer a new, biology-based, line of defence for Immanuel Kant's view of ancient discoveries in geometry, with implications for spatial consciousness in humans and other animals, including requirements for spatial consciousness in newly-hatched chicks, and other animals with sophisticated unlearned competences available soon after birth or hatching, e.g. foals that can walk to suckle, and can run with the herd to escape a predator soon after birth. Many animals have spatial competences before they have had time to learn them. I'll suggest that those competences, including human mathematical competences, are based on brain assembling chemical mechanisms -- not empirical learning. In humans and some other intelligent species those brain-assembling mechanisms can also provide mechanisms able to detect and make use of impossibility or necessity in spatial structures and processes -- key features of mathematical competences, which Kant pointed out (in 1781) could not be based on repeated failures or successes in empirical learning. Statistical/probabilistic reasoning cannot establish necessity or impossibility. Instead an overview of relevant possibilities and their structural limits is required. I'll sketch the outlines of a theory of how, during reproduction, chemical processes can produce not only physical structures but also spatial reasoning abilities used by ancient mathematicians. E.g. Pythagoras' theorm was discovered and proved many times long before Pythagoras was born. A key feature of the theory is that the chemical mechanisms that assemble many kinds of body parts also provide abilities to detect spatial necessity and impossibility. The need for that arises during genetically driven assembly of increasingly complex and varied structures. The earliest assembly processes are constrained/supported by the double helix structure of DNA, but as components become more complex so must the assembly mechanisms become more sophisticated, e.g. controlling construction and assembly of increasingly complex and varied physiological components of the new organism. In the early stages the items assembled within a cell are tiny molecular structures, with few components, but at later stages far larger, more complex and more varied multi-cellular structures are constructed and assembled in required spatial configurations. The chemical control mechanisms doing the assembly need to become increasingly sophisticated at later stages, e.g. using new kinds of information about spatial structures and relationships between parts that have already been assembled. Many scientists and AI engineers (e.g. the designers of Deep Mind) now believe that such intelligence has to be implemented in trainable neural nets, but that cannot apply to mechanisms building the neural nets before a functional brain has been constructed. Key idea: If the later, more complex, assembly processes require abilities to detect possibilities and constraints (impossibilities) in choosing what to do next by reasoning rather than trial and error (which would explode the time required for assembly, and possibly lead to too many fatal mistakes), then not only the components of the new organism, but also the components of the construction mechanisms building the organism, must be developed chemically, including their information-processing abilities required for controlling increasingly complex construction processes. In a subset of organisms, evolution seems to have found ways of making those spatial reasoning competences available also to the completed organism, as shown by spatial intelligence in squirrels, nest-building birds, foals that can run with the herd within hours of birth, and others. In a small subset of those species, most obviously humans, the processes of learning to detect and use spatial impossiblity and necessity continue after birth, presumably still somehow using sub-celluar chemical control mechanisms for spatial reasoning that were previously used to control assembly of the organism. In humans, additional reflective mechanisms continue to be built after birth, so that (as Piaget discovered) they can make proto-mathematical discoveries, such as the necessary transitivity of one-to-one correspondence in the fifth or sixth year. This is a pre-requisite for a full understanding of numbers and their uses in counting sets. There are many gaps still to be filled in this theory, including explaining in detail how the chemical bootstrapping mechanisms originally provided by DNA extend themselves at later stages in a developing organism so as to include useful abilities to detect impossibility and necessity, required for effective control of assembly of more complex physiological structures and mechanisms -- a process children playing with construction kits such as Meccano, Lego, Tinker-toys, Fischer-technic, etc. develop spontaneously and unwittingly and use in controlling more complex assembly processes. Other intelligent species seem to have similar abilities, though only humans seem to be able to go on to reflect on, discuss, and explicitly teach such competences. But the core mechanisms are needed in the initial assembly of all organisms that grow themselves starting from fertilised egg-cells. The requirements are different in organisms like trees that do not move about as a whole, though their life cycles involve many motions of parts. The genetically based mechanisms that develop spatial reasoning competences during reproduction are important because understanding of (e.g. spatial) impossibility (and necessity) cannot be learnt empirically, e.g. because no amount of failure proves impossibility. This also points to serious limitations of artificial neural nets whose learning is based entirely on collection of statistics and derivation of probabilities. More than mere failure, or success, is required to explain reasons for failure or success. It also requires insight into the structures of problems: the type of insight without which the development of many types and branches of mathematics, and their application in practical activities, e.g. making clothes, building shelters, building machines to help with construction processes, would have been impossible. The recently fashionable theory that mathematical competences depend on uses of symbolic, logic-based, reasoning cannot account for the much older forms of mathematical discovery based on spatial reasoning abilities, some of which seem to be partially shared with other intelligent species. So we need alternatives to both logic-based symbolic reasoning mechanisms and statistics-based probabilistic reasoning to explain spatial mathematical intelligence, or to replicate it in future machines. A related line of thought may have motivated Alan Turing's very surprising investigations of chemical morphogenesis, reported in his 1952 paper, but without any mention of this motive. However, there is a sentence about the importance of chemistry in brains in his Mind 1950 paper that seems to be relevant. Also relevant is the distinction he made in his thesis between mathematical ingenuity and mathematical intuition, claiming that unlike human mathematicians (Turing-equivalent) computers are capable of mathematical ingenuity but not mathematical intuition. He did not explain why not. These ideas are related to, but different from, claims made and developed by Roger Penrose since 1989 (in The Emperor's New Mind) and in subsequent work partly in collaboration with Stuart Hameroff, illustrated in a recent joint presentation online here: https://www.youtube.com/watch?v=xGbgDf4HCHU Consciousness and the physics of the brain May 12, 2020 They don't seem to have noticed the role of multi-stage chemistry-based intelligence required during construction of a new complex organism (including construction of brains) starting from a fertilised egg-cell, Perhaps the microtubules occurring during development of a foetus are relevant long before the microtubules in brains, emphasised by Hameroff. (See https://science.sciencemag.org/content/357/6354/882.1) There is still a vast amount of work to be done, combining and extending what has been learnt so far about biochemical mechanisms and processes. Perhaps, as Penrose suggests, current physical theory will need a major extension. Or perhaps implications of what is already known about quantum chemistry will suffice. There may already be important relevant insights in Schrodinger's later writings that I have not yet taken in.

Further notes

There is fragmentary evidence that Alan Turing was thinking about a project of this sort when he wrote his 1952 paper on chemistry-based morphogenesis, explaining formation of surface patterns on organisms, while his unstated long-term intention was much deeper and more important than explaining how visible patterns form. The label "Meta-Morphogenesis" was introduced to refer to that more ambitious project in Sloman(2013).

\cite{Sloman-Turing--4}. Continued development of the project since then is reported in a growing collection of online documents referenced in
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html , which include a theory of evolved construction-kits, including construction-kits created during processes of development of individual organisms in fertilized eggs, or seeds.

There seems to be little or no recognition of these processes and their implications in current philosophy of mind, psychology, neuroscience and AI. So theories developed in those fields are incapable of producing adequate explanations of a variety of phenomena, including spatial learning and reasoning in many species, ancient processes of mathematical discovery in geometry and topology, long before Euclid, and important aspects of human consciousness, including forms of proto-consciousness involved in multiple layers of increasingly complex information-based control mechanisms during development from fertilised eggs. Insofar as the key processes crucially involve both discrete and continuous change they cannot be fully replicated on digital computers, though they can be implemented in chemical processes for reasons pointed out in Schrödinger's 1944 Book, though he apparently did not notice their importance beyond explaining the possibility of reliable biological reproduction.

Background

Development of this "tangled network" of ideas began in 1958/9 when I switched from mathematics to philosophical research on the nature of mathematical discovery, defending Kant's view of mathematical knowledge as non-empirical, synthetic (not derived from definitions using logic), and concerned with necessary truths and necessary falsehoods (impossibilities). This led to a DPhil thesis (Oxford) in 1962. I later felt the claims and arguments could be improved, after encountering Artificial Intelligence, and learning to program, starting around 1970. A book, The Computer Revolution in Philosophy, resulted in 1978. It was later digitised and placed online at http://www.cs.bham.ac.uk/research/projects/cogaff/crp/ then repeatedly updated/extended with references to related AI topics and projects.

A full account of what minds and brains can do would have to explain how ancient mathematical brains made discoveries in geometry and topology centuries before Euclid, using forms of spatial reasoning processes that make it possible to detect examples of impossibility and necessity. I don't think anyone currently understands how brains represent and detect, spatial/geometric impossibility and necessity.

This is not a general requirement for models of mind, e.g. models of affective states and processes, e.g. desires, emotions, attitudes, etc. using information-processing architectures containing multiple interacting sub-systems, discussed in
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/vm-functionalism.html

In contrast, pre-verbal human toddlers, illustrated in http://www.cs.bham.ac.uk/research/projects/cogaff/misc/toddler-theorems.html nest-building in weaver-birds and crows, and spatial intelligence in squirrels, elephants, orangutans, dolphins, octopuses and many other species, require abilities to represent and reason about necessity and impossibility, closely related to ancient mathematical abilities. Probabilistic neural nets cannot represent or reason about these modalities.

There is still a great deal to explain about varieties of spatial monitoring and control not only in whole organisms but also in enormously complex and little understood chemical control and assembly processes in eggs that produce chickens, alligators and other animals, and in related construction processes and mechanisms in mammalian reproduction.

I am sure that if Alan Turing had not died in 1954 he would by now have taken these ideas much further than I have -- and in the process explaining his obscure distinction between mathematical intuition and mathematical ingenuity. https://www.cs.bham.ac.uk/research/projects/cogaff/misc/turing-intuition.html

I suspect Turing would have agreed that Mary Pardoe's (re-) discovery of the non-standard proof of the triangle sum theorem, presented above, was an example of use of mathematical intuition. She found that her students understood and remembered it more easily than the standard Euclidean proof that depends on properties of parallel lines.

---

---

Note for philosophy teachers
I suggest that, in view of what we now know about life, and the rate at which such knowledge is being extended, teaching philosophy of mind and philosophy of mathematics without teaching any evolutionary and developmental biology is educationally misguided.

References

Chicken embryo development
http://www.poultryhub.org/physiology/body-systems/embryology-of-the-chicken/
Photographs of chick embryo stages (PDF):
http://www.poultryhub.org/wp-content/uploads/2012/05/Poster_Chick_Embryo_Dev_English.pdf
LOCAL COPY FOR LECTURE
http://www.cs.bham.ac.uk/~axs/fig/chicken-egg-devel.jpg
apa-stuff.d/Poster_Chick_Embryo_Dev_English.pdf
DAY 1: Appearance of embryonic tissue.
DAY 2: Tissue development very visible. Appearance of blood vessels.
DAY 3: Heart beats. Blood vessels very visible.
DAY 4: Eye pigmented.
DAY 5: Appearance of elbows and knees.
DAY 6: Appearance of beak. Voluntary movements begin.
DAY 7: Comb growth begins. Egg tooth begins to appear.
DAY 8: Feather tracts seen. Upper and lower beak equal in length.
DAY 9: Embryo starts to look bird-like. Mouth opening occurs.
DAY 10: Egg tooth prominent. Toe nails visible.
DAY 11: Cob serrated. Tail feathers apparent.
DAY 12: Toes fully formed. First few visible feathers.
DAY 13: Appearance of scales. Body covered lightly with feathers.
DAY 14: Embryo turns head towards large end of egg.
DAY 15: Gut is drawn into abdominal cavity.
DAY 16: Feathers cover complete body. Albumen nearly gone.
DAY 17: Amniotic fluid decreases. Head is between legs.
DAY 18: Growth of embryo nearly complete. Yolk sac remains outside of embryo. Head is under right wing.
DAY 19: Yolk sac draws into body cavity. Amniotic fluid gone. Embryo occupies most of space within egg (not in the air cell).
DAY 20: Yolk sac drawn completely into body. Embryo becomes a chick (breathing air with its lungs). Internal and external pipping occurs.

https://www.youtube.com/watch?v=PhOqP_GasVs
Baby Crocs Hone Hunting Skills -- National Geographic

https://www.youtube.com/watch?v=nOkq69T6j7E
Ducklings first feed after hatching. First Swimming baby ducks.
Hatched without mother. (Incubated??)

https://www.youtube.com/watch?v=9jRSgZVhWvw
Baby chicks with hen.

https://www.youtube.com/watch?v=OsoNKlyFtpI
Chimpanzees React to Their Reflections in a Mirror CenterForGreatApes

https://video.nationalgeographic.com/video/00000144-0a34-d3cb-a96c-7b3dd2970000
Mother crocodile takes babies swimming, to hunt for food.

William Bechtel, Adele Abrahamsen and Benjamin Sheredos, (2018), Using diagrams to reason about biological mechanisms, in Diagrammatic representation and inference, Eds. P. Chapman, G. Stapleton, A. Moktefi, S. Perez-Kriz and F. Bellucci, Springer, https://doi.org/10.1007/978-3-319-91376-6_26

Godfrey-Smith, P. (2007). Innateness and Genetic Information. In P. Carruthers, S. Laurence, & S. Stich (Eds.), The Innate Mind Volume 3: Foundations and the Future (pp. 55-105). OUP.
https://petergodfreysmith.com/PGS-InfoAndInnate.pdf

Godfrey-Smith, P. (2017). Other Minds: The Octopus and the Evolution of Intelligent Life, William Collins.

Carl G. Hempel (1945), Geometry and Empirical Science, in American Mathematical Monthly, 52, 1945, also in Readings in Philosophical Analysis eds. H. Feigl and W. Sellars, New York: Appleton-Century-Crofts, 1949, http://www.ditext.com/hempel/geo.html

Kant, Immanuel (1781). Critique of pure reason, (Translated (1929) by Norman Kemp Smith), London: Macmillan. Retrieved from https://archive.org/details/immanuelkantscri032379mbp/page/n10/mode/2up

Piaget, J. (1952). The Child's Conception of Number. London: Routledge & Kegan Paul.

Schrödinger, E. (1944). What is life? Cambridge: CUP.

A. Sloman, (1965) `Necessary', `A Priori' and `Analytic', in Analysis 26, pp. 12--16, http://www.cs.bham.ac.uk/research/projects/cogaff/62-80.html#1965-02

Sloman, A. (2013). Virtual machinery and evolution of mind (part 3) Meta-morphogenesis: Evolution of information-processing machinery. In S. B. Cooper & J. van Leeuwen (Eds.), Alan Turing - His Work and Impact (p. 849-856), Amsterdam: Elsevier. http://www.cs.bham.ac.uk/research/projects/cogaff/11.html#1106d

Aaron Sloman, 2013, Virtual Machinery and Evolution of Mind (Part 3) Meta-Morphogenesis: Evolution of Information-Processing Machinery, in Alan Turing - His Work and Impact, Ed. S. B. Cooper and J. van Leeuwen, pp. 849-856, Elsevier, Amsterdam, 9780123869807,
http://www.cs.bham.ac.uk/research/projects/cogaff/11.html#1106d

A. M. Turing, 1952, The Chemical Basis Of Morphogenesis,
Phil. Trans. R. Soc. London B 237, 237, pp. 37--72,

MORE REFS

https://www.youtube.com/watch?v=hFZFjoX2cGg
Building the Perfect Squirrel Proof Bird Feeder (Failed?)
Also some other animals.

https://www.cs.bham.ac.uk/research/projects/cogaff/movies/apa/videos.txt

https://www.youtube.com/watch?v=9jRSgZVhWvw Hens and chicks
MURGI Hen Harvesting Eggs to Chicks new "BORN" Roosters and Hens Small Birds

https://www.youtube.com/watch?v=QPqcSKhtxKk

Ducklings around the lake. (4.24 starting to paddle)

https://www.youtube.com/watch?v=KBm698UoROs
Newly Hatched Ducklings [2008] -- All waiting for last eggs to hatch.

'Peak hype': why the driverless car revolution has stalled
https://www.youtube.com/watch?v=QPqcSKhtxKk

PYTHAGORAS wikipedia
https://en.wikipedia.org/wiki/Pythagorean_theorem

---

The above is a small sample of references relevant to this talk. More will be added later.

---

Maintained by Aaron Sloman
School of Computer Science
The University of Birmingham