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Edge 80 — January 9, 2001 (34,000 words plus - on the Web) THE
THIRD CULTURE
NATURAL
BORN CYBORGS? "We cannot see ourselves aright until we see ourselves as nature's very own cyborgs: cognitive hybrids who repeatedly occupy regions of design space radically different from those of our biological forbears. The hard task, of course, is now to transform all this from (mere) impressionistic sketch into a balanced scientific account of the extended mind."
THE
REALITY CLUB
Joseph Traub on Quantum Computation Speaking technically, Grover's algorithm show quantum search is only polynomially faster than classical search. Part of my research is solving continuous problems on a quantum computer and here there are problems which can be solved exponentially faster on a quantum computer. THE
THIRD CULTURE
NATURAL BORN CYBORGS?
By Andy Clark Introduction "As our worlds become smarter, and get to know us better and better," writes cognitive scientist Andy Clark, "it becomes harder and harder to say where the world stops and the person begins." Clark's examines the"potent, portable machinery linking the user to an increasingly responsive World Wide Web," as well as "the gradual smartening-up and interconnection of the many everyday objects which populate our homes and offices." But his interest is not primarily in new technology. "Rather," he writes, "it is to talk about us, about our sense of self, and about the nature of the human mind. The point is not to guess at what we might soon become, but to better appreciate what we already are: creatures whose minds are special precisely because they are tailor-made to mix and match neural, bodily and technological ploys." According to Clark, we have to give up the prejudice "that whatever matters about mind must depend solely on what goes on inside the biological skin-bag, inside the ancient fortress of skin and skull." He presents cognitive technologies as "deep and integral parts of the problem-solving systems that constitute human intelligence. They are best seen as proper parts of the computational apparatus that constitutes our minds." – JB ANDY
CLARK is Professor of Philosophy and Cognitive
Science at the University of Sussex, UK. He
was previously Director of the Philosophy/Neuroscience/Psychology
Program at Washington University in St. Louis.
He is the author of Microcognition: Philosophy,
Cognitive Science and Parallel Distributed Processing,
Associative Engines, and Being There:
Putting Brain, Body and World Together Again.
NATURAL BORN CYBORGS? By Andy Clark
My body is an electronic virgin. I incorporate
no silicon chips, no retinal or cochlear implants,
no pacemaker. I don't even wear glasses (though
I do wear clothes). But I am slowly becoming
more and more a Cyborg. So are you. Pretty
soon, and still without the need for wires,
surgery or bodily alterations, we shall be
kin to the Terminator, to Eve 8, to Cable...just
fill in your favorite fictional Cyborg. Perhaps
we already are. For we shall be Cyborgs not
in the merely superficial sense of combining
flesh and wires, but in the more profound
sense of being human-technology symbionts:
thinking and reasoning systems whose minds
and selves are spread across biological brain
and non-biological circuitry.
What's more, the use, reach and transformative powers of these cognitive technologies is escalating. New waves of user-sensitive technology may soon bring this ancient process to a climax, as our minds and identities become ever more deeply enmeshed in a non-biological matrix of machines, tools, props, codes and semi-intelligent daily objects. We humans have indeed always been adept at dovetailing our minds and skills to the shape of our current tools and aids. But when those tools and aids start dovetailing back — when our technologies actively, automatically, and continually tailor themselves to us, just as we do to them — then the line between tool and user becomes flimsy indeed. Such technologies will be less like tools and more like part of the mental apparatus of the person. They will remain tools in only the thin and ultimately paradoxical sense in which my own unconsciously operating neural structures (my hippocampus, my posterior parietal cortex) are tools. I do not really "use" my brain. There is no user quite so ephemeral. Rather, the operation of the brain is part of what makes me who and what I am. So too with these new waves of sensitive, interactive technologies. As our worlds become smarter, and get to know us better and better, it becomes harder and harder to say where the world stops and the person begins. What are these technologies? They are many, and various. They include potent, portable machinery linking the user to an increasingly responsive World Wide Web. But they include also, and perhaps ultimately more importantly, the gradual smartening-up and interconnection of the many everyday objects which populate our homes and offices. My immediate goal, however, is not really to talk about new technology. Rather, it is to talk about us, about our sense of self, and about the nature of the human mind. The point is not to guess at what we might soon become, but to better appreciate what we already are: creatures whose minds are special precisely because they are tailor-made to mix and match neural, bodily and technological ploys. Cognitive technologies are best understood as deep and integral parts of the problem-solving systems that constitute human intelligence. They are best seen as proper parts of the computational apparatus that constitutes our minds. If we do not always see this, or if the idea seems outlandish or absurd, that is because we are in the grip of a simple prejudice: the prejudice that whatever matters about mind must depend solely on what goes on inside the biological skin-bag, inside the ancient fortress of skin and skull. But this fortress has been built to be breached. It is a structure whose virtue lies in part in it's capacity to delicately gear its activities to collaborate with external, non-biological sources of order so as (originally) to better solve the problems of survival and reproduction. Thus consider a brief but representative example. Take the familiar process of writing an article for a newspaper, an academic paper, a chapter in a book. Confronted, at last, with the shiny finished product the good materialist may find herself congratulating her brain on its good work. But this is misleading. It is misleading not simply because (as usual) most of the ideas were not our own anyway, but because the structure, form and flow of the final product often depends heavily on the complex ways the brain cooperates with, and depends on, various special features of the media and technologies with which it continually interacts. We tend to think of our biological brains as the point source of the whole final content. But if we look a little more closely what we may often find is that the biological brain participated in some potent and iterated loops through the cognitive technological environment. We began, perhaps, by looking over some old notes, then turned to some original sources. As we read, our brain generated a few fragmentary, on-the-spot responses which were duly stored as marks on the page, or in the margins. This cycle repeats, pausing to loop back to the original plans and sketches, amending them in the same fragmentary, on-the-spot fashion. This whole process of critiquing, re-arranging , streamlining and linking is deeply informed by quite specific properties of the external media, which allow the sequence of simple reactions to become organized and grow (hopefully) into something like an argument. The brain's role is crucial and special. But it is not the whole story. In fact, the true power and beauty of the brain's role is that it acts as a mediating factor in a variety of complex and iterated processes which continually loop between brain, body and technological environment. And it is this larger system which solves the problem. We thus confront the cognitive equivalent of Dawkins' vision of the extended phenotype. The intelligent process just is the spatially and temporally extended one which zigzags between brain, body and world. One useful way to understand the cognitive role of many of our self-created cognitive technologies is as affording complementary operations to those that come most naturally to biological brains. Thus consider the connectionist image of biological brains as pattern-completing engines. Such devices are adept at linking patterns of current sensory input with associated information: you hear the first bars of the song and recall the rest, you see the rat's tail and conjure the image of the rat. Computational engines of that broad class prove extremely good at tasks such as sensorimotor coordination, face recognition, voice recognition, etc. But they are not well-suited to deductive logic, planning, and the typical tasks of sequential reason. They are, roughly speaking, "Good at Frisbee, Bad at Logic:" a cognitive profile that is at once familiar and alien. Familiar, because human intelligence clearly has something of that flavor. Yet alien, because we repeatedly transcend these limits, planning family vacations, running economies, solving complex sequential problems, etc., etc. A powerful hypothesis, which I first encountered in work by David Rumelhart, Paul Smolensky, John McClelland and Geoffrey Hinton, is that we transcend these limits, in large part, by combining the internal operation of a connectionist, pattern-completing device with a variety of external operations and tools which serve to reduce various complex, sequential problems to an ordered set of simpler pattern-completing operations of the kind our brains are most comfortable with. Thus, to borrow their illustration, we may tackle the problem of long multiplication — e.g. 667X999— by using pen, paper and numerical symbols. We then engage in a process of external symbol manipulations and storage so as to reduce the complex problem to a sequence of simple pattern-completing steps that we already command, first multiplying 9 by 7 and storing the result on paper, then 9 by 6, and so on. The cognitive anthropologist Ed Hutchins, in his book Cognition In The Wild depicts the general role of cognitive technologies in similar terms, suggesting that "[Such tools] permit the [users] to do the tasks that need to be done while doing the kinds of things people are good at: recognizing patterns, modeling simple dynamics of the world, and manipulating objects in the environment." This description nicely captures what is best about good examples of cognitive technology: recent word-processing packages, web browsers, mouse and icon systems, etc. (It also suggests, of course, what is wrong with many of our first attempts at creating such tools: the skills needed to use those environments (early VCR's, word-processors, etc.) were precisely those that biological brains find hardest to support, such as the recall and execution of long, essentially arbitrary, sequences of operations.
The conjecture, then, is that one large jump
or discontinuity in human cognitive evolution
involves the distinctive way human brains repeatedly
create and exploit various species of cognitive
technology so as to expand and reshape the space
of human reason. We, more than any other creature
on the planet, deploy non-biological elements
(instruments, media, notations) to complement
(but not, typically, to replicate) our basic
biological modes of processing, creating extended
cognitive systems whose computational and problem-solving
profiles are quire different from those of the
naked brain. Human brains maintain an intricate
cognitive dance with an ecologically novel,
and immensely empowering, environment: the world
of symbols, media, formalisms, texts, speech,
instruments and culture. The computational circuitry
of human cognition thus flows both within and
beyond the head. Such
a point is not new, and has been well-made
by a variety of theorists working in many
different traditions. I believe, however,
that the idea of human cognition as subsisting
in a hybrid, extended architecture (one which
includes aspects of the brain and of the cognitive
technological envelope in which our brains
develop and operate) remains vastly underappreciated.
We simply cannot hope to understand what is
special and distinctively powerful about human
thought and reason by merely paying lip-service
to the importance of this web of surrounding
technologies. Instead,
we need to work together towards a much more
detailed understanding of how our brains actively
dovetail their problem-solving activities
to a variety of non-biological resources,
and of how the larger systems thus created
operate, change, interact and evolve. In addition
it may soon be quite important (morally, socially,
and politically) to publicly loosen the bonds
between the very ideas of minds and persons
and the image of the bounds, properties, locations
and limitations of the basic biological organism
.
A proper question to press, however, is this: since no other species on the planet builds as varied, complex and open-ended designer environments as we do (the claim, after all, is that this is why we are special), what is it that allowed this process to get off the ground in our species in such a spectacular way? And isn't that, whatever it is, what really matters? Otherwise put, even if it's the designer environments that make us so intelligent, isn't it some deep biological difference that lets us build-discover-use them in the first place? This is a serious, important and largely unresolved question. Clearly, there must be some (but perhaps quite small) biological difference that lets us get our collective foot in the designer environment door — what can it be? One possible story locates the difference in a biological innovation for widespread cortical plasticity combined perhaps with the extended period of protected learning called "childhood". Thus "neural constructivists" such as Steve Quartz and Terry Sejnowski depicts neural (especially cortical) growth as experience — dependent, and as involving the actual construction of new neural circuitry (synapses, axons, dendrites) rather than just the fine-tuning of circuitry whose basic shape and form is already determined. One upshot is that the learning device itself changes as a result of organism-environmental interactions — learning does not just alter the knowledge base for a fixed computational engine, it alters the internal computational architecture itself. The linguistic and technological environments in which human brains grow and develop are thus poised to function as the anchor points around which such flexible neural resources adapt and fit. Perhaps, then, it is a mistake to posit a biologically fixed "human nature" with a simple "wraparound" of tools and culture. For the tools and culture are indeed as much determiners of our nature as products of it. Ours are (by nature) unusually plastic brains whose biologically proper functioning has always involved the recruitment and exploitation of non-biological props and scaffolds. More so than any other creature on the planet, we humans emerge as natural-born cyborgs, factory tweaked and primed so as to be ready to grow into extended cognitive and computational architectures: ones whose systemic boundaries far exceed those of skin and skull.
All this adds interesting complexity to those evolutionary psychological accounts which emphasize our ancestral environments. For we must now take into account an exceptionally plastic evolutionary overlay which yields a constantly moving target, an extended cognitive architecture whose constancy lies mainly in its continual openness to change. Even granting that the biological innovations which got this ball rolling may have consisted only in some small tweaks to an ancestral repertoire, the upshot of this subtle alteration is a sudden, massive leap in cognitive-architectural space. For our cognitive machinery is now intrinsically geared to transformation, technology-based expansion, and a snowballing and self-perpetuating process of computational and representational growth. The machinery of contemporary human reason thus turns out to be rooted in a biologically incremental progression while simultaneously existing on the far side of a precipitous cliff in cognitive-architectural space. In sum, the project of understanding human thought and reason is easily and frequently misconstrued. It is misconstrued as the project of understanding what is special about the human brain. No doubt there is something special about our brains. But understanding our peculiar profiles as reasoners, thinkers and knowers of our worlds requires an even broader perspective: one that targets multiple brains and bodies operating in specially constructed environments replete with artifacts, external symbols, and all the variegated scaffoldings of science, art and culture. Understanding what is distinctive about human reason thus involves understanding the complementary contributions of both biology and (broadly speaking) technology, as well as the dense, reciprocal patterns of causal and co-evolutionary influence that run between them. We cannot see ourselves aright until we see ourselves as nature's very own cyborgs: cognitive hybrids who repeatedly occupy regions of design space radically different from those of our biological forbears. The hard task, of course, is now to transform all this from (mere) impressionistic sketch into a balanced scientific account of the extended mind. THE
REALITY CLUB From:
Joseph
Traub
Two
recent
Edge
postings,
"Time
Loops:
a Talk
with Paul
Davies"
and Phil
Anderson's
response
to Jaron
Lanier's
"One-Half
a Manifesto"
are rich
in stimulating
ideas.
However,
when they
touch
on quantum
computation,
they both
make statements
that I
question. What is known about searching large databases on a quantum computer? Grover(1996) discovered a quantum algorithm for finding a single item in an unsorted database with N items in time proportional to the square root of N. The same problem takes time N to solve on a classical computer. For example, if there are 10 to the 100 items in the database (thats 1 followed by 100 zeros) it would take time 10 to the 100 on a classical computer and time about 1 to the 50 (thats 1 followed by 50 zeros) on a quantum computer. I would not call that "searching enormous databases with extraordinary efficiency". Speaking technically, Grover's algorithm show quantum search is only polynomially faster than classical search. Part of my research is solving continuous problems on a quantum computer and here there are problems which can be solved exponentially faster on a quantum computer. Grover (1997) shows that one can find an item in one step on a quantum computer, provided that the query is sufficiently complicated, but i don't think that this theoretical result would help Paul, since we wouldn't know how to frame the query. I'll turn to Phil's remarks. He says "Why does the quantum computer do new things? Why is complexity theory such a poor quide to the real world of problems?" I infer from the juxtaposition of these two sentences that Phil believes that computational complexity theory is incorrect for quantum computation. I surmise that Phil is thinking of complexity theory for a classical computer. But complexity theory always depends on the model of computation which states what operations are permitted and how much they cost. Think of it as the rules of the game. The model of computation for a quantum computer is ofcourse different than for a classical computer. Thus Phil's two sentences form a non sequitor. JOSEPH F. TRAUB is the Edwin Howard Armstrong Professor of Computer Science at Columbia University and External Professor at the Santa Fe Institute. He was founding Chairman of the Computer Science Department at Columbia University from 1979 to 1989, and founding chair of the Computer Science and Telecommunications Board of the National Academy of Sciences from 1986 to 1992. From 1971 to 1979 he was Head of the Computer Science Department at Carnegie-Mellon University. Traub is the founding editor of the Journal of Complexity and an associate editor of Complexity. A Festschrift in celebration of his sixtieth birthday was recently published. He is the author of nine books including the recently published Complexity and Information. |
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John Brockman, Editor and Publisher Copyright
© 2001 by Edge Foundation, Inc |
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