Abstract
This essay was written for the purpose of providing a minimal common ground for discussion. It is, of necessity, an ambitious attempt to give a concise account of the various current ideas on the origin of meaning in living and artificial systems in such a way that it is accessible to an interdisciplinary audience, and yet substantive enough to produce debate among the specialists. I apologize at the outset to both groups for passages that will seem irritatingly simple or too abstruse.
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Notes
This Section owes much to our recent collective work on the neglected history of early cybernetics, self-organization, and cognition, published as Cahiers du CREA N°s 7–9. The only other useful source is S. Heims, John von Neumann and Norbert Wiener, MIT Press, 1980.
The recent book by H. Gardner, The Mind’s New Science: A History of the Cognitive Revolution, Basic Books, 1985, discusses this period only in a superficial way.
The best sources here are the oft-cited Macy Conferences, published as Cybernetics-Circular causal and feedback Mechanisms in Biological and Social Systems, Josiah Macy Jr. Foundation, New York, 5 volumes.
Bulletin of Mathematical Biophysics, 5, 1943. Reprinted in W. McCulloch, Embodiments of Mind, MIT Press, 1965
For an interesting perspective about this historical/conceptual moment see also A. Hodges, Alan Turing: The Enigma of Intelligence, Touchstone, New York, 1984.
See H. Gardner, Alan Turing: The Enigma of Intelligence, Touchstone, New York, 1984 @@@op. cit., Chapter 5 for this period.
This designation is justified in J. Haugland (Ed.), Mind Design, MIT Press, 1981. Other designations used are: computationalism (Fodor) or symbolic processing. For this section I have profited much from D. Andler’ s article in Cahier du CREA N° 9.
For more on this see J. Searle, Intentionality, Cambridge U. P., 1983.
R. Shepard and J. Metzler, Science 171, 701–703 (1971).
S. Kosslyn, Psychol. Rev. 88, 46–66, 1981.
See Beh. Brain Sci. 2, 535–581 (1979).
This is the opening line of a popular textbook in neuroscience: “The brain is an unresting assembly of cells that continually receives information, elaborates and perceives it, and makes decision.” S. Kuffler and J. Nichols, From Neuron to Brain, Sinauer Associates, Boston, 2nd ed., 1984, p. 3.
D. Hubel and T. Wiesel, J. Physiol. 160, 106 (1962). For a recent account of this work see Kuffler and Nichols, op. cit. Ch. 2–4.
H. Barlow, Perception 1, 371–3 92.
F. Rosenblatt, Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms, Spartan Book, 1962.
For more on the complex early origins of self-organization ideas see I. Stengers, Cahier du CREA N° 8, pp. 7–105.
‘The logical geography of computational approaches’, MIT Sloan Conference, 1984.
For extensive discussion on this point of view see P. Dumouchel and J.-P. Dupuy (Eds.), L’Auto-organisation: De la physique au politique, Eds. du Seuil, Paris, 1983.
See for example H. von Foerster (Ed.), Principles of Self-Organization, Pergamon Press, 1962.
An accessible introduction to the modern theory of dynamical systems is: R. Abraham and C. Shaw, Dynamics: The Geometry of Behavior, Aerial Press, Santa Cruz, 3 vols., 1985.
G. Horn and R. Hill, Nature 221, 185–187 (1974).
M. Fishman and C. Michael, Vision Res., 13, 1415 (1973)
and F. Morell, Nature 238, 44–46 (1972).
J. Allman, F. Miezen and E. McGuiness, Ann. Rev. Neuroscien. 8, 407–430 (1985).
F. Varela and W. Singer, Exp. Brain Res. 66, 10–20 (1987).
An interesting collection of examples is: G. Palm and A. Aersten (Eds.), Brain Theory, Springer Verlag, 1986.
The name is proposed in: J. Feldman and D. Ballard, ‘Connectionist models and their properties’, Cognitive Science 6, 205–254 (1982).
For extensive discussion of current work in this direction see: D. Rumelhart and J. McClelland (Eds.), Parallel Distributed Processing: Studies on the Microstructure of Cognition, MIT Press, 1986, 2 vols.
The main idea is due to J. Hopfield, Proc. Natl. Acad. Sci. (U.S.A.), 79, 2554–2556 (1982).
There are many variants associated to these ideas. See in particular: G. Hinton, T. Sejnowsky, and D. Ackley, Cognitive Science 9, 147–163 (1984),
and G. Toulousse, S. Dehaene, and J. Changeaux, Proc. Natl. Acad. Sci. (U.S.A.), 83, 1695–1698 (1986).
The idea is due to D. Rumelhart, G. Hinton, and R. Williams, in: Rumelhart and McClelland, op. cit., Ch. 8.
T. Sejnowski and C. Rosenbaum, ‘NetTalk: A parallel network that learns to read aloud’, TR JHU/EECS-86/01, John Hopkins Univ.
For the distinction between symbolic and emergent description and explanation in biological systems see F. Varela, Principles of Biological Autonomy, North Holland, New York, 1979, Ch. 7,
and more recently S. Oyama, The Ontogeny of Information, Cambridge U. Press, 1985.
See D. Hillis, ‘Intelligence as emergent behavior’, Daedalus, Winter 1989, and P. Smolesnky, ‘On the proper treatment of connectionism’, Beh. Brain Sci. 11: 1, 1989.
In a very different vein J. Feldman, ‘Neural representation of conceptual knowledge’, U. Rochester TR189 (1986) proposes a middle ground between ‘punctuate’ and distributed systems.
P. Smolesnky in: Rumelhart and McClelland, op. cit., Ch. 6.
This is extensively argued by two noted spokesmen of cognitivism: J. Fodor and S. Pylyshyn, ‘Connectionism and cognitive architecture: A critical review’, Cognition, 1989. For the opposite philosophical position in favor of connectionism see: H. Dreyfus, ‘Making a mind vs. modeling the brain: AI again at the cross-riads’. Daedalus, Winter, 1989.
Most influential in this respect is the work of H. G. Gadamer, Truth and Method, Seabury Press, 1975. For a clear introduction to hermeneutics see Palmer, Hermeneutics, Northwestern Univ. Press, 1979.
The formulation of this section owes a great deal to the influence of F. Flores, see: T. Winnograd and F. Flores Understanding Computers and Cognition: A New Foundation for Design, Ablex, New Jersey, 1986.
The name is far from being an established one. I suggest it here for pedagogical reasons, until a better one is proposed.
H. Dreyfus and S. Dreyfus, Mind over Machine, Free Press/Macmillan, New York, 1986.
For this explicit way of constructing biologically inspired networks see T. Poggio, V. Torre and C. Koch, Nature 317, 314–319 (1986).
For an interesting sample of discussion in AI about these themes see the multiple review of Winnograd and Flores’ s book, in Artif. Intell. (1987).
The main reference points we have in mind here are (in their English versions): M. Heidegger, Being and Time, Harper and Row, 1977;
M. Merleau-Ponty, The Phenomenology of Perception, Routledge and Kegan Paul, 1962;
Michel Foucault, Discipline and Punish: The birth of the prison, Vintage/Random House, 1979.
This is discussed in my contribution to the previous Stanford Symposium, ‘Living ways of sense making: A middle way approach to neuroscience’, in P. Livingston (Ed.), Order and Disorder, Anma Libris, Stanford, 1984.
See for instance P. Watzlawick (Ed.), The Invented Reality: Essays on Constructivism, Norton, New York, 1985.
Most clearly seen in the Vienna school of Konrad Lorenz, as expressed, for example, in Behind the Mirror, Harper and Row, 1979.
See for instance E. Land, Proc. Natl. Acad. Sci. (U.S.A.) 80, 5163–5169 (1983).
P. Gouras and E. Zenner, Progr. Sensory Physiol. 1, 139–179 (1981).
F. Varela et al., Arch. Biol. Med. Exp, 16, 291–303 (1983); E. Thompson, A. Palacios, F. Varela, Beh. Brain Sci. (in press), 1992.
W. Freeman, Mass Action in the Nervous System, Academic Press, 1975.
W. Freeman and C. Skarda, Brain Res. Reviews, 10, 145–175 (1985). Significantly, a section of this article is entitled: ‘A retraction on “representation”’ (p. 169).
This biologically inspired re-interpretation of cognition was presented in H. Maturana and F. Varela, Autopoiesis and Cognition: The realization of the Living, D. Reidel, Boston, 1980, and F. Varela, Principles of Biological Autonomy, op. cit.
For an introductory exposition to this point of view and more recent developments see H. Maturana and F. Varela, The Tree of Knowledge: the Biological Roots of Human Understanding, New Science Library, Boston 1987. The links with language and AI are discussed in Winnograd and Flores, op. cit.
See J. H. Holland, ‘Escaping brittleness’, in: Machine Intelligence, Vol. 2 (1986).
An interesting recent collections of diverse papers in this direction can be found in: Evolution, Games and Learning: Models for Adaptation in Machines and Nature, Physica 22D (1986). Surely, many of the contributors would not agree with our readings of their work. For an explicit example see: F. Varela, ‘Structural coupling and the origin of meaning in a simple cellular automata’, in E. Secarz, (Ed.), The Semiotics of Cellular Communications, Springer-Verlag, New York, 1987.
P. Smolesnky, op. cit., p. 260.
It is worth noting that similar arguments can be applied to evolutionary thinking today. For the parallels between cognitive representationism and evolutionary adaptationism, see F. Varela, in: P. Livingston (Ed.), op. cit. and the Introduction in this volume.
See also the remarks by Roger Schank in AI Magazine, pp. 122–135 (Fall 1985).
This is the trend within the new field of ‘Artificial Life’; see e.g. Ch. Langton (Ed.), Artificial Life, Addison-Wesley, New Jersey, 1990.
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Varela, F.J. (1992). Whence Perceptual Meaning? A Cartography of Current Ideas. In: Varela, F.J., Dupuy, JP. (eds) Understanding Origins. Boston Studies in the Philosophy and History of Science, vol 130. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8054-0_13
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