Abstract: Alan Turing draws a firm line between the mental and the physical, between the cognitive and physical sciences. For Turing, following a tradition that went back to D=Arcy Thompson, if not Geoffroy and Lucretius, throws talk of function, intentionality, and final causes from biology as a physical science. He likens Amother nature@ to the earnest A. I. scientist, who may send to school disparate versions of the Achild machine,@ eventually hoping for a test-passer but knowing that the vagaries of his experimental course are history and accident.

Key words: evolution, adaptationism, Turing test, Turing structures, cognitive science, physical science.

Philosophy, Engineering, Biology, and History: A Vindication of Turing=s Views About the Distinction Between the Cognitive and Physical Sciences, Journal of Experimental & Theoretical Artificial Intelligence (14(2002))

I found him [James D. Watson in 1965] the most unpleasant human being I had ever met. ... He arrived with the conviction that biology must be transformed into a science directed at molecules and cells and rewritten in the language of physics and chemistry. What had gone before, Atraditional@ biology C my biology C was infested by stamp collectors who lacked the wit to transform their subject into a modern science. (Wilson 1994, p. 219).

Alan Turing (1912-1954) made foundational contributions to philosophy, mathematics, biology, artificial intelligence, and computer science. He formulated the relevant abstract theory of computability, automatising it in the most minimalist format. Hence, we speak of >Turing Machines= and the >Universal Turing Machine= (this terminology displaced Turing=s own more modest, and more accurate, >Theoretical Computing Engine= and >Universal Theoretical Computing Engine= (Turing 1936)). Turing also, as much as anyone, invented the digital electronic computer and, in two papers, formulated an operationalised goal for cognitive science and suggested in considerable detail all of the methods rediscovered and touted over the past half century for simulating human intelligence, for producing something mentally indistinguishable, under intensive interrogation, from a human person. Hence we speak of the >Turing Test= (replacing Turing=s again more specific term, >imitation game= (Turing 1948, 1950)). These terminological tributes to Turing abet an ahistorical tendency on the part of many scientists (including some philosophers). Literature buffs read classics. Scientists just cite them, having learned what they are supposed to have said from recent text books (from now on I will revert to current terminology).

Turing had pointed out from the beginning that no Universal Turing Machine with literal Turing Machine architecture could possibility be a candidate for an actual, reasonably functional computer. To be absolutely minimalist, Turing gave his theoretical machines a one-base natural number notation; so ten base 1 would be /, 2 would be //, 3 would be /// ... 11 would be /////////// ... 1,000,000 would be a million slashes and so on (it would take a Turing adding machine something like some 30 separate operations to add // and // to get //// (2+2=4)). By several more orders of magnitude such literal architecture could not possibility constitute an actual computer powerful enough to turn it into a real time, reliable Turing Test passer through programming, tweaking connectionist nets, equipping a >child machine= with >the best eyes and ear money can buy= and educating it, or even sending, shades of Mary Shelley=s Frankenstein, a suitably equipped computer-robot into the countryside to educate itself (a step that, Turing suggested, would represent some danger to the human inhabitants (Turing 1948, 1950)). But the change in terminology abetted would be philosophical counterexamples to the Turing Test by Ned Block, John Searle, and many others in which humans enact a literal Universal Turing Machine or something similar. What is patently obvious is that these cockamamy assemblies could not possibly work, could not possibly be reliable, real time Turing Test passers.

In the 1950s and 1960s, in awe of computers that did arithmetic operations faster and more accurately than humans, rather different nay sayers argued that it would >a simple task= to produce a Turing Test passer but that this would not prove real intelligence. And, indeed, in those heady days, many artificial intelligence mavens claimed that but a decade or so would see success. No one makes such predictions today. Over the past fifty years computers have grown almost immeasurably in speed and memory capacity, and all the methods Turing suggested have been zealously pursued (except the Frankenstein option), with much inevitably learned about human intelligence. But the goal of Turing Test passage now seems ever more formidable in just the area C human language and the folk psychology it embodies in personal narrative C that the Turing Test makes central. The magnitude of the difficulty is perhaps most dramatically obvious in the presumably much simpler but related task of machine translation between human languages. After a half century of concerted effort by linguists, psycholinguists, programmers and indeed cognitive scientists of all ilks, the best that can be said of current machine translations is that by scanning the absurd muddle for key words, and the very occasional viable phrase or even intelligible sentence, you may be able to guess whether it will be worth while to call in a human translator. Computer success can be better, but only a little, with highly restricted technical writing. Failure is most complete with the words and constructions of what Ludwig Wittgenstein called the >old city=, the core words and narrative structures, and personal knowledge, common to speakers of a natural language. Because common, native, and, like visual perception, its operations largely opaque to conscious introspection, this human competence had seemed apt to computer simulation. We know better now. While computers can simulate or exceed the performance of human experts in narrowly defined areas, they are laughably far from simulating core human competencies most called for in the Turing Test. These core cognitive competencies undoubtedly depend on the four fold leap in brain size from Australopithecines to Homo sapiens. Supposedly, the currently fashionable evolutionary psychologists assure us, such have been sculpted by selection operating on our hunter-gatherer ancestors. In fact, recent allometric and embryological research on primate brain anatomy calls the evolutionary psychologist position into serious question. Barbara Finlay and Richard Darlington, and others, have marshaled evidence to show that, with the trifling exception of the medulla and the olifactory bulb, the human brain is just a scaled up primate and mammalian brain, the proportions among its parts conserved, along with the relative enlargement of the isocortex, all quite predictable on embryological grounds (from the homeobox gene and protein induced segmentation of the neuronal tube and the delayed Abirthday@ of the isocortex forming cells). To quote from a recent Behavioral and Brain Sciences article

How does evolution grow bigger brains? It has been widely assumed that the growth of individual structures and functional systems in response to niche‑specific cognitive challenges is the most plausible mechanism for brain expansion in mammals. Comparison of multiple regressions on allometric data for 131 mammalian species, however, suggests that for 9 of 11 brain structures taxonomic and body size factors are less important than covariance of these major structures with each other. Which structures grow biggest is largely predicted by a conserved order of neurogenesis that can be derived from the basic axial structure of the developing brain. This conserved order of neurogenesis predicts the relative scaling not only of gross brain regions like the isocortex or mesencephalon, but also the level of detail of individual thalamic nuclei. Special selection of particular areas for specific functions does occur, but it is a minor factor compared to the large‑scale covariance of the whole brain. The idea that enlarged isocortex could be a "spandrel," a by product of structural constraints later adapted for various behavior, contrasts with approaches that look to selection of particular brain regions for cognitively advanced behaviors, as commonly assumed in the case of hominid brain evolution. (Finlay, Darlington, Nicastro 2001).

If all nine structures of the primate brain enlarge in lock step from the oldest and smallest brained primates up to humans, it becomes indeterminate which brain structure supposedly experienced selectional pressure for enlargement and which did not.

In a passage often eliminated when the familiar 1950 paper is anthologized, Turing specifically suggests attempting to simulate >the initial state of the mind, say at birth= (Turing 1950, p. 31), and then giving >the child machine an education=. The experimenter is not be likely to happen on an appropriate child machine simulation immediately but would have to try out various possibilities and Turing compares this process with biological evolution through the following equations (anticipating rather similar formulations in Noam Chomsky=s radical reformation of linguistic theory (Chomsky 1957)) and in much subsequent work in modular, computational psychology:

Structure of the child machine = hereditary material

Changes of the child machine = mutations

Judgement of the experimenter = natural selection. (Turing 1950/1963, p. 32)

He imagined that the experimenter could proceed rather more quickly than natural selection, making carefully planned and rapid changes. In his 1948 paper, Turing similarly suggests that a purely >blank tablet at birth= animal would be wholly improbable, so he supposed that the successful >child machine= would have plenty of native structure. Similarly, I hasten to add that, as Turing=s use of the locution >the initial state of the mind, say at birth= clearly suggests, he, as latterly Chomsky, does not mean genes (i.e. DNA) by >hereditary material= but rather the child=s full cognitive apparatus insofar as this is attributable to natural growth and development as opposed to peculiarities of the local environment. While evolutionary biologists sometimes casually suggest that DNA does all the work, it just provides templates which cell protein structures use to make more proteins and join them in more complex configurations, soon creating developing multicellular structures that are the beginnings of organs that now as structured wholes direct differentiation into a couple hundred cell types placed into complex larger structures (the first and master developer is the nervous system, which is globally directing the development of the fetus within a few days after the zygote is firmly attached to the womb. >Say at birth= leaves wiggle room, for Turing of course recognized that the child at birth is by no means through with what Turing called the >morphogens= of development (Turing 1954). Subsequent work makes it much more amply clear that lots of biologically directed growth rather than general purpose learning is needed.

Although virtually all cognitive scientists are familiar with Turing Machines and the Turing Test, and most can easily supply some, often potted, version of them, near all are unaware that Turing is equally famous among biologists for his ground breaking paper, >On the Chemical Basis of Morphogenesis= (Turing 1952). Indeed, this paper, which introduced what biologists inevitably now call >Turing structures=, has received more citations than all the rest of Turing=s works altogether, although not from evolutionary biologists but from embryologists (Saunders 1992, p. xvi). The exemplary chaotic reaction-diffusion models that Turing proposed now have an important role in theoretical biology and recently have been observed experimentally (Castets, V., Duclos, E., Boissonade, J., Kepper, P. 1990). They show how patterns or structures can burst forth in homogeneous mediums, the most specific example of >Turing structures=. (Turing=s paper is so densely mathematical and embryological, and so far ahead of his time, that it earned credit retrospectly. I. Prigogine was initially credited and Nobeled for the notion of dissipative and chaotic biological reactions in his work in the late 1950s and 1960s. Now first credit goes to A. Turing (1952), whose lectures on the topic Prigogine attended, reportedly spending a day in vigorous conversation with Turing (Hodges 1983, p. 564)).

Turing tackles an exemplary aspect of what he saw as the central problem of biology, viz., how the zygotic cell of conception manages, through strictly chemical and physical means, to grow into the immensely larger and enormously complicated structures of the fetus, the baby, and the mature organism, creating all along new information and structure. Turing=s restrictions on biological explanation cast out teleology, evolutionary phylogeny, natural selection, and history (both the final causes of teleology and >origins= or efficient causality in Aristotle=s original sense that would distinguish two chemically identical molecules if one were produced >naturally= and the other in the laboratory, or insist that biological description of a particular organism is crucially incomplete or indeterminate if several selective descent pathways might have led to it, with which one possibly simply an historical accident but nonetheless part of its biological description.). As Turing wrote, modestly asserting the hard-nosed ahistorical, antiteleological biological tradition to which he belonged,

Unless we adopt a vitalistic and teleological conception of living organisms, or make extensive use of the plea that there are important physical laws as yet undiscovered relating to the activities of organic molecules, we must envisage a living organism as a special kind of system to which the general laws of physics and chemistry apply. And because of the prevalence of homologies of organization, we may well suppose, as D=Arcy Thompson has done, that certain physical processes are of very general occurrence... What is novel in [this diffusion reaction] theory is the demonstration that, under suitable conditions, many diffusion reaction systems will eventually give rise to stationary waves; in fact to a patterned distribution of metabolites. (Turing and Wardlaw, C. W. (1953/1992, p. 45)

As Turing put this general project tersely, his new ideas were intended to >defeat the argument from design= (Hodges 1983, p. 431). Turing was, of course, not referring to William Paley=s watchmaker argument for the existence of God, one long before displaced by Darwin (who wholly endorsed Aristotle=s biological work and who had cut his biological teeth in rapt fascination with Paley=s detailed teleology, whose designed-ness designedness in no way wished to dispel from biological descriptions, but only sought to derive them through mother nature=s rather than God=s selections). Turing, rather, endorsed the D=Arcy Thompson (1917) view that the teleological >evolutionary explanations= endemic to Darwinian >adaptationist= biology are non-fundamental, fragile, misdirected, and at best mildly heuristic. >The primary task of the biologist is to discover the set of forms that are likely to appear [for] only then is it worth asking which of them will be selected= (Saunders 1992, xii).

The anti-teleological, morphological tradition that Turing and Thompson articulate, and Finley, et al., exemplify, goes back to Etienne Geoffroy Saint-Hilaire, who, in a month long debate before the Academie des Sciences in 1830, maintained the unity of type thesis that all structured multicellular animals have the same ground plan (bauplane) against the selectionist demands of existence of Georges Cuvier, whom Charles Darwin called his >idol=. Poet naturalist Johan Wolfgang Goethe also felt party to the debate since he maintained that plant appendages C carpels, stamens, petals, sepals, and leaves C are all metamorphoses of a kind of urleaf. Work by embryological and molecular geneticists in the last decade extravagantly confirm the claims of Geoffroy and Goethe. With one trifling exception C Bryozoa C all 20 odd animal phyla appeared within a few score million years in the great Cambrian >explosion=, as if nature were quick to run through all the basic possibilities of the animal type in less than 5% of the time there have been animals on earth. More substantially, it appears more and more likely that all animal phyla are variations of the same structural plan and use virtually the same homeobox >master genes= and proteins to determine segmentation and segmental identity.

[W]e have accumulated more and more evidence that the same homeobox genes are used in both vertebrates and invertebrates to specify the body plan and that the mechanisms of the genetic control of development are much more universal than anticipated. (Gehring 1998, p. 53).

Parallel results have appeared in the study of plants. Goethe=s fondest hopes have been realized: carpels, stamens, petals, sepals, and leaves are variations on the ur-leaf tripped off by homeobox structural genes and their protein employers (Coen 1999). Unity of type has received an extraordinary, and to evolutionary biologists a most unexpected and devastating confirmation. In the 1970s, Stephen J. Gould gently tried to reintroduce continental morphology and the bauplane into English-speaking evolutionary biology, most controversially in >The Spanrels of San Marco= (Gould & Lewontin 1979). Anglo-American evolutionary biologists greeted Gould=s proposals, and his skepticism about selectionist explanations, with even greater skepticism and scorn for wooly-headed, anti-empirical transcendentalising, a willful blindness possibly motivated by left wing disdain for the hereditarian and selectionist views of E. O. Wilson=s Sociobiology. The shoe is now on the other foot.

The fragility and insubstantial nature of evolutionary explanations received another ample demonstration recently. Since Darwin took it from Paley, the eye has been evolutionary biologists= stock example of analogical development, a device so nifty that nature supposedly has >re-invented= it several times, e.g. in mollusks, insects, and vertebrates. Recently biologists showed that the same Pax-6 DNA makes eyes in squids, fruit flies, and mice, so economical and homological nature apparently >invented= eyes only once (Tomarev, Callaerts, Kos, Zinovieva, Halder, Gehring, and Piatigorsky 1997).)

Based on these substantial differences in morphology and mode development the biologist Ernst Mayr has argued that different types of eyes evolved as many as forty times independently in the animals kingdom. Because the evolution of the prototype eye, at a stage before selection can exert its effect, must be a rare event, the independent evolution of so many prototypes represents a serious problem that is difficult to reconcile with Darwin=s theory... [Our] findings lead to the further conclusions that the prototypic eye may have originated only once, rather than some forty times, and that the large variety of eye types found in the animals kingdom is derived from this prototype by divergent, parallel, and convergent evolution. (Gehring 1998, p. 204-209ff)

Even Darwin=s historical picture of the great tree of life, branching ever outward from the first common ancestor, through the immensely gradual work of natural selection, has been scotched. DNA and RNA evidence commandingly support the view that for more than two-thirds of the existence of life on earth, life was not a tree, in which genetic material is exclusively transferred vertically from ancestor to descendant. No, and importantly, it was a lattice in which genes and gene sets were also exchanged laterally between organisms across species barriers and even across, what are now considered the most basic domains of life, bacteria, archaea, and eukaryota (for a summary see Doolittle 2000, Woese 1998). The phyla of structured multicellular organisms eventually branch forth from a common bauplan in eukaryota in the Cambrian explosion tree, but for the rest of eukaryota, and for bacteria and archaea, the lattice fertilely continues, plastering the earth in and beyond environments hospitable to structured multicellulars and probably exceeding them in biomass. Finally, as for the claim that all evolution of organic complexity occurs through the immensely gradual action of natural selection, most molecular biologists consider that the work of the last few decades decisively supports the view that perhaps the most essential step in the evolution of the eukaryote cell occurred when a large-celled precursor to eukaryota happened to ingest an alpha-proteobacterial cell, which took up a profitable symbiotic relationship with its host, providing the power plant essential to the eukaryote cell. Similarly, the chloroplast organelles vital to plant life stemmed from an ingested cyanobacterium that settled in symbiotically. Given the evolutionary biologists emphasis on gradualism and natural selection, and their view that evolutionary biology was a foundational science whose results were independent of physical and chemical discoveries in molecular and cellular biology, it is perhaps no wonder that the first paper propounding these claims about the origins of mitochondria and chloroplasts received fifteen rejection slips before it was finally published in 1966 (Margulis 1998, p 29). It now appears in standard text books (although they do not repeat Margulis=s saucy, but surely true, claim that both are clear Lamarckian cases of the >inheritance of acquired characteristics= through the direct action of the environment on the organism).

You may now perhaps wonder at a possible incoherence in Turing=s views. In his cognitive science papers, Turing is quite happy to offer his equations: the structure of the child machine = hereditary material, changes of the child machine = mutations, judgement of the experimenter = natural selection. But in his biological work, he and the tradition to which he belongs look with suspicion on evolutionary explanations, and talk of purpose or function, that goes beyond purely physical and chemical characterization of organic processes. For Turing part of the explanation lies in the sharp distinction he made between mental traits and physical ones. As Turing did much to show us, very different physical materials arranged in very different architectures, may embody the same real time competencies and folk psychological, personal, and physical knowledge that individual humans exhibit (indeed Turing=s cognitive science is committed to characterising such knowledge and such competencies in a way that is independent of any particular physical realization). We have no clear a priori notion of what intelligence or cognitive competence is: that is to say, what array of theoretical Turing Machines we need to instantiate and coordinate in structured hardware that must astronomically exceed any literal Turing Machine in speed. But we assume that humans have it. So we are set an engineering problem: will any or even all of the approaches he suggests, if diligently and luckily pursued, actually produce a real time passer? He hoped that programming would work because he thought it would be the cheapest, fastest, and most instructive method (he wistfully hoped that the passer would not have to have to store lot of pictorial information because he was only to conscious of how much memory space this would demand). But if building a child machine and giving it eyes and ears, and possibly limbs and hands, and then an education, were necessary, this would certainly be a way of learning something about the specifications for human intelligence.

As Turing envisioned it, research teams might have to work through some accidental and arbitrary number of child machine versions, until possibly coming up with a viable version (if such were found it would literally be one of countless many, although undoubtedly sharing certain abstract properties, a crucial some of which would likely belong to human children). But this accidental and arbitrary history of research would be, well, history, and so essentially irrelevant to the final product, its evaluation, and success or failure (although, of course, historians of science might use features of this product, along with other data, to infer this history). More generally, cognitively speaking, you don=t have to grow or follow any particular procedure in producing a Turing test passer. Whatever does the job, does the job. This is the line, as Turing puts it, in distinguishing the cognitive from the specifically physical and chemical.

Similarly, speaking biologically, when we are concerned with the actual physics and chemistry of human biological development, the teleology and the actual phylogenetic and evolutionary history, are centrally irrelevant and distracting. We can and should characterise embryological development without concern for origins, for the accidental, for the use of intentional/design talk. Undoubtedly, there is a stunningly unique history, doubtless full of sound and fury and unretrodictable butterfly effects, of the careers of all the organisms that ever graced the earth (including human organisms and their precursors). Using the physics and chemistry of Turing=s biology and statistical data about the RNA, DNA, etc., and morphology of current organisms and fossils, we can speculatively sketch some features of this history C that certain organisms and kinds existed over stretches of this history, that there is a more or less determinate branching phylogenetic descent tree for structured, multicellular organisms from the Cambrian era on, undergirded by a descent lattice of one-celled organisms and their colonies that stretches from some three billion years before the Cambrian down to now.

Much more speculatively, we can, anthropomorphically, adapt the intentional and design idiom to further structure our narrative (Darwin also was specifically inspired to adapt the Malthusian competitive, magic hand >political economy= theories of his day to the realm of organisms). Organisms can be described as if they primarily desire to send their genes into the future and, secondarily, to struggle to survive long enough to do so; and their actions are determined by this desire and their beliefs about the surrounding environment. It does not really change the narrative descriptive idiom to say organisms look as if they were designed to reach the goal of sending their genes into the future by suitably reacting to environmental stimuli to optimise their survival chances as a means to that goal. As Turing=s Test clearly suggests, the folk psychological/design idiom that exemplifies our mental life is a cognitive, not a physical idiom. In any case, the vagaries of this folk psychological/design idiom history should not be taken to make any difference to biology as a natural science. Anthropomorphism works best at home: with humans and their artifacts. When we turn around from adaptationist speculative generalizations about mammals to apply them to humans we are only to likely to achieve impoverished and characteristically banal observations.

I end on a more personal, narrational, and historical note.

Sometime around 1965 I recall remarking to Professor NN that Norman Mailer provided a truer account of what went on at a recent presidential political convention than might be provided by a number of social scientists observing, taking polls, or whatever, abstracting from folk- psychologically-phrased public opinions folk psychological banalities. Professor NN was genuinely shocked by my lese majesty against Ascience.@ Mailer=s masterful narrative of the return of capital punishment to the United States through the crime and punishment of Gary Gilmore, The Song of the Executioner, would have been an even better example, a profound wedding of historical and artistic truth. About the same time, Professor Walter Kaufmann, in introducing his translations of Nietzsche, boasted that Nietzsche still exercised a profound influence on philosophy and literature, cited Paul Tillich=s claim that Marx, Nietzsche, and Freud were the greatest modern AProtestants.@ Kaufmann also claimed Nietzsche as a great psychologist, citing Sigmund Freud remarks that Nietzsche=s Apremonitions and insights often agree in the most amazing manner with the laborious results of psychoanalysis...[H]e had a more penetrating knowledge of himself than any other man who ever lived or was likely to live@ (Kaufmann 1966, x-xi). Kaufmann also adds, perhaps taking Freud down a peg, that AAlfred Adler=s modification of Freud=s theories ... is even closer to Nietzsche=s psychology of the will to power than Freudianism.@ Indeed, the various schools of psychology and psychotherapy that bestrew the 20^th century have insisted that human behavior stems from a hierarchy of instinctive drives, only making individual survival, power, actualization, etc., more important than they loom in the libido powered Freudian scheme. In this last respect Freud is one with the evolutionary biologists of the last few decades, who insist that mere individual fitness, survival without progeny, is an evolutionary dead end; what is wanted is Ainclusive fitness,@ with the Aselfish genes@ propelling animals unwittingly to reproduce with the reproductively fit at some or even fatal damage to their individual fitness (Freud took for granted Darwin=s vision of the primal horde, jealously dominated by a polygynous male, who instinctively and unconsciously acted to maximize his fertility, whatever his proximal conscious rationalizations might be; Schopenhauer anticipated Darwin, Freud, and evolutionary psychologists by vehemently insisting that men are relentlessly driven to maximize their contribution to the preservation of the species by fighting to fertilize the most fecund females, while doltishly imagining that they are sparked by unique grace, vivacity, goodness, and beauty).

Kaufmann also adds that AOnce it was fashion to link Nietzsche with Darwin and evolutionary thought, but his reputation did not pass with this [Darwinian] fashion ... The same goes with later vogues@ (Kaufmann 1966, xii). Today=s fashions find Freud a literary and cultural more than scientific power, his famous five case studies perhaps comparable to Mailer=s Executioner=s Song C insightful and haunting narratives of particular real people C while Darwinism is once more fashionable, particularly with E. O. Wilson=s 1975 Asociobiology@ transformed into Aevolutionary psychology,@ an updating that some find more cosmetic and politic than theoretical. Evolutionary psychology books and papers reiterate Wilson=s arrogant claim that the banalities of his evolutionary biology provide the only legitimate foundation for the cognitive, psychological, and social sciences. There is, of course, nothing wrong with stamp collecting. Stephen Jay Gould C and Darwin for that matter C are masters of this art (Gould, who plays on both sides of the fence, has also published several hundred papers in the Thompson-Turing-Watson biological tradition as well, in journals such as Organic Chemistry). But stamp collecting is a specific, descriptive, historical, and folk psychological art that loses determinacy and comprehension when it moves from the particular to the general, from the historical, accidental, and individual to the dateless, essential, and stereotypic, from specific human narratives to banal just-so animal stories.

Justin Leiber, Philosophy Department, Florida State University, Tallahassee, Fl 32306, jleiber@mailer.fsu.edu

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