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written with Stephan Vladimir Bugaj
We live at a crucial point in history – an incredibly
exciting and frightening point; a point that is stimulating
to the point of excess, intellectually, philosophically,
physically and emotionally. A number of really big technologies
are brewing. Virtual reality, which lets us create synthetic
worlds equal in richness to the physical world, thus making
the Buddhist maxim “reality is illusion” a palpable
technical fact. Biotechnology, allowing us to modify our
bodies in various ways, customizing our genes and jacking
our brains, organs and sense organs into computers and other
devices. Nanotechnology, allowing us to manipulate molecules
directly, creating biological, computational, micromechanical,
and other kinds of systems that can barely be imagined today.
Artificial intelligence, enabling mind, intelligence and
reason to emerge out of computer systems – thinking
machines built by humans. And advances in unified field
theory in physics will in all likelihood join the party,
clarifying the physical foundation of life and mind, and
giving the nanotechnologists new tricks no one has even
speculated about yet.
Even immortality is not completely out of the question.
As Eric Drexler argued in Engines of Creation, nano-scale
robots could swarm through your body repairing your aging
cells. Or, as Hans Moravec depicted in his classic book
Mind Children, brain scan technology combined with AI could
have us uploading our minds into computers once our bodies
wear down. Or genetic engineering could allow us to fuse
with computers, eliminating aging and permitting direct
mind-to-mind communication with other humans and computers
via complex analysis of the brain’s electromagnetic
fields. It sounds like science fiction, but it’s entirely
scientifically plausible: these would be immense engineering
achievements, but wouldn’t violate any known scientific
laws. A lot of seemingly impossible things will soon be
possible.
Bill Joy, Chief Scientist of Sun Microsystems, one of the
leading companies in the current phase of the tech revolution,
recently wrote an article in Wired painting this same kind
of future, but with a markedly dystopian bent. He believes
all this amazing technological development will happen,
and he finds it intensely scary. It’s difficult to
blame him, actually. The potential for abuse of such technologies
is obvious. We have to hope that an ethical evolution comparable
to the technological evolution will occur at the same time,
beautifully synchronized.
This evolving network of long-term possibilities is wonderful
and amazing to think about, but, on the other hand, it’s
almost too big for any one mind or small group of minds
to grapple with. Imagine a bunch of pre-linguistic proto-humans
trying to comprehend what the advent of language was going
to do to them. That’s basically the kind of situation
we’re in! Nevertheless, in spite of the difficulty
intrinsic in foresight and the impossibility of planning
any kind of revolution in advance, least of all the technological
and psychocultural kind, there’s something we can
do beside sit back and watch as history leads us on. We
can focus on particular aspects of the revolution we’re
wreaking, understanding these aspects as part of the whole,
and also focusing hard on the details, remembering that,
historically, some of the subtlest and most profound general
humanistic insights have come from dealing with very particular
issues. In these pages we’re going to view the ongoing
tech revolution through the eyes of biocomputing –
not the only perspective, to be sure, but definitely an
interesting one.
All
these words about the amazing present and future achievements
of technology are almost irrelevant these days. The transformative
power of technology is now pretty much common sense. Any
kid raised on Digimon, Johnny Quest and Dragonball Z knows
supercomputers, virtual reality, intelligent robots like
the back of his hand (and the only reason he knows the back
of his hand is that he sees it sometimes while playing Gameboy!).
Even so, though, the wide acceptance of rapidly improving
tech as an everyday phenomenon, has not translated into
a widespread deep understanding of where the tech explosion
is leading us. Most people would agree, if asked, that technology
is improving at a superexponential rate (after you explained
to them what “superexponential” meant). But
not many people yet seem willing to draw the natural conclusion
of this: that, unless some strange unsuspected limits to
progress are encountered, within 30-100 years, machines
will have outpaced us in nearly all ways, and quite likely
transformed us radically in the process.
The renowned inventor Ray Kurzweil has tried to make this
point clear to the average American in his recent book The
Singularity is Near – “Singularity” being
a term coined by sci-fi writer Vernor Vinge to describe
the point at which technological advance becomes so rapid
that it is essentially instantaneous. He has meticulously
charted the progress of technology in various areas of industry,
and plotted curves showing the approaching Singularity.
Two of his more macro-level observations are given in the
following two charts.
This one shows the mass use of inventions as it has accelerated
over time – a quantitative depiction of the penetration
of technology into everyday life. Of course, there’s
a lot of detail underlying the calculation of such figures,
but Kurzweil seems to have been reasonably careful and scientific
in this regard.
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A
couple more examples of his trend-tracking work are as follows:
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The
same basic picture comes up again and again, in one technology
domain after another. Progress goes faster and faster, and
it grows faster at a faster rate each year.
Kurzweil has done a particularly careful analysis of the
phenomenon of exponential increase in computing power. His
overall conclusion:
• We achieve one Human Brain capability (2 * 10^16
cps) for $1,000 around the year 2023.
• We achieve one Human Brain capability (2 * 10^16
cps) for one cent around the year 2037.
• We achieve one Human Race capability (2 * 10^26
cps) for $1,000 around the year 2049.
• We achieve one Human Race capability (2 * 10^26
cps) for one cent around the year 2059.
The comparisons with human brain power are based on a rough
neural network model of the brain, as will be described
in the following chapter. However, as he points out, an
error of a couple orders of magnitude in estimating human
brain power, will only throw his time estimates off by a
couple years – thus is the power of exponential growth.
Of course, Ray Kurzweil is only one among a large and growing
group of trend-tracking Singularity pundits. One of the
early works along these lines was Derek DeSolla Price’s
1963 book Little Science, Big Science and Beyond. More recent
works include Damien Broderick’s 2001 book The Spike
(mostly qualitative, but with some quantitative aspects),
and Johansen and Sornette's 2001 article "Finite Time
Singularity in the Dynamics of the World Population, Economic,
and Financial Indices" (available online at http://xxx.lanl.gov/abs/cond-mat/0002075).
John Smart has started a group called SingularityWatch,
and established himself as perhaps the world’s first
full-time Singularity pundit. His observations in a recent
article on KurzweilAI.net are as follows:
Complementary
to Kurzweil's data on double exponential growth, these
authors note that many other computationally relevant
variables, such as economic output, scientific publications,
and investment capital, have exhibited recent asymptotic
phases. Of course, each particular substrate eventually
saturates—population, economies, etc. never do go
to infinity—but measuring the asymptotic phases
does allow us to better trace the second order computational
trend presently unfolding on the planet in a broad range
of physical-computational domains.
Certainly my best current projected range of 2020-2060
is voodoo like anyone else's, but I'm satisfied that I've
done a good literature search on the topic, and perhaps
a deeper polling of the collective intelligence on this
issue than I've seen elsewhere to date. To me, estimates
much earlier than 2020 are unjustified in their optimism,
and likewise, estimates after 2060 seem oblivious to the
full scope and power of the… processes in the universe.
I
think this kind of overall trend analysis is very valuable
thing. It gives some much-needed quantitative concreteness
to the qualitative observation of exponential tech acceleration.
But one also feels the need for a deeper view, a perspective
that gives a sense of what the Singularity means. Each of
the extrapolatory graphs produced by Kurzweil and others
encapsulates a long, deep story – not just a story
of technical engineering improvements, but a story of conceptual
breakthroughs, of deepening understanding. It is our progressively
deepening understanding of the universe, synergetically
evolving with our creation of new technologies, that will
bring the Singularity about. My focus here will be on the
synergy between deepening understanding and advancing technology
– a synergy that spans scientific disciplines, and
furthermore spans the domains of science, engineering and
philosophy.
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Val Turchin in the early 1990’s |
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While
Kurzweil has created an impressively concrete analysis,
and Vinge’s original writings on the Singularity are
elegant and provocative, perhaps the deepest analysis of
what’s going on was provided by the Russian philosopher-scientist
Valentin Turchin. We will use Turchin’s notion of
the Metasystem Transition as a tool for understanding the
future of biocomputing and its general implications.
Valentin Turchin is a fascinating individual, who holds
a unique position in the history of the Internet. He was
the first of the cyber-gurus: The expansion of computer
and communication networks that he foresaw in his 1970 book
“The Phenomenon of Science” is now a reality;
and the trans-human digital superorganism that he prophesied
to emerge from these networks, is rapidly becoming one.
But unlike most scientists who turn toward philosophy in
mid-life, Turchin was not satisfied to be a grand old theorist.
Now in his 70’s, in spite of an increasingly frustrating
battle with Parkinsonism, he is playing an active role in
making his vision of an Internet superorganism come true,
helping lead an Internet start-up company, Supercompilers
LLC, which applies the same cybernetic principles he used
to study the future of humanity to create computer programs
that rewrite other programs to make them dozens of times
more efficient – and even rewrite themselves.
No one in Turchin’s generation started off their careers
in computer science; rather, it was his generation that
started computer science off. He holds three degrees in
theoretical physics, obtained in the 50’s and early
60’s; and the first decade of his career was devoted
to neutron and solid state physics. But in the 60’s
his attention drifted toward computers, far before computers
became fashionable – especially in Russia. He created
a programming language, REFAL, which became the dominant
language for artificial intelligence in the Soviet bloc.
Apart from any of his later achievements, his work on REFAL
alone would have earned him a position as one of the leaders
of 20’th century computer science.
It was the political situation in the Soviet Union that
drew him out of the domain of pure science, into the world
of philosophy. In the 1960's he became politically active,
and in 1968 he authored "Inertia of Fear and the Scientific
Worldview", a fascinating document combining a scathing
critique of totalitarianism and the rudiments of a new cybernetic
theory of man and society. Not surprisingly, following the
publication of this book in the underground press, Turchin
lost his research laboratory.
His classic "The Phenomenon of Science," published
two years later, enlarged on the theoretical portions of
“Inertia of Fear,” presenting a unified cybernetic
meta-theory of universal evolution. The ideas are deep and
powerful, centered on the notion of a metasystem transition,
a point in the history of evolution of a system where the
whole comes to dominate the parts. Examples are the emergence
of life from inanimate matter; and the emergence of multicellular
life from single-celled components. He used the metasystem
transition concept to provide a global theory of evolution
and a coherent social systems theory, to develop a complete
cybernetic philosophical and ethical system, and to build
a new foundation for mathematics. The future of computer
and communication technology, he saw, would bring about
a metasystem transition in which our computational tools
would lead to a unified emergent artificial mind, going
beyond humanity in its capabilities. The Internet and related
technologies would spawn a unified global superorganism,
acting as a whole with its own desires and wishes, integrating
humans to a degree as yet uncertain.
By 1973 he had founded the Moscow chapter of Amnesty International
and was working closely with Andrei Sakharov. The Soviet
government made it impossible for him to stay in Russia
much longer. In 1977, persecuted by the KGB and threatened
with imprisonment, he was expelled from the Soviet Union,
taking refuge in the US and joining the Computer Science
faculty of the City University of New York, where he continued
his philosophical and scientific work. Among other projects,
in the mid-1980’s he created the concept of supercompilation,
a novel technique that uses the meta-system transition concept
to rewrite computer programs and make them more efficient.
While Americans tend toward extreme positions about the
future of the cyber-world – Bill Joy taking the pessimist’s
role; Kurzweil, Moravec and others playing the optimist
– Turchin, as he and his team work to advance computer
technology, views the situation with a typically Russian
philosophical depth. He still wonders, as he did in “The
Phenomenon of Science,” whether the human race might
be an evolutionary dead-end, like the ant or the kangaroo,
unsuitable to lead to new forms of organization and consciousness.
As he wrote there, in 1970, “Perhaps life on Earth
has followed a false course from the very beginning and
the animation and spiritualization of the Cosmos are destined
to be realized by some other forms of life.” Digital
life, perhaps? Powered by Java, made possible by the supercompiler
Turchin’s software company is developing?
“The Phenomenon of Science” closes with the
following words: “We have constructed a beautiful
and majestic edifice of science. Its fine-laced linguistic
constructions soar high into the sky. But direct your gaze
to the space between the pillars, arches, and floors, beyond
them, off into the void. Look more carefully, and there
in the distance, in the black depth, you will see someone's
green eyes staring. It is the Secret, looking at you.”
This is the fascination of the Net, and genetic engineering,
and artificial intelligence, and all the other new technologies
spreading around us and – now psychologically, soon
enough physically – within us. It’s something
beyond us, yet in some sense containing us – created
by us, yet creating us. By writing books and supercompilers,
or just sending e-mails and generally living our tech-infused
lives, we unravel the secret bit-by-bit -- but we’ll
never reveal it entirely.
Meeting Turchin in person, after reading his work and admiring
his thinking, was a fascinating experience. He was very
down-to-earth, definitely not spouting phrases such as “fine-laced
linguistic constructions” and “beautiful and
majestic edifice of science” – but of course
this didn’t surprise me; after all, my own conversation
is a lot more informal than my prose. When I brought up
the global brain and the posthuman future, he smiled knowingly,
said a few words, and gently changed the subject. Clearly,
he hadn’t changed his mind about any of that, but
it wasn’t what was occupying most of his time. To
him, all this was old hat. Of course, humans will become
obsolete; of course computer programs will become superintelligent.
Nothing more to say about that really. What was occupying
his mind seemed to be the particular technical problems
he was working on: making a supercompiler that could rewrite
Java programs to make them dozens of times faster, using
advanced logical reasoning; and firming up a theory he’d
developed years before called the “cybernetic foundations
of mathematics,” which grounds mathematical knowledge
in the process of acting in and perceiving the world, using
his programming language Refal as a tool.
I was happy to be able to help him out: I played an instrumental
role in getting his company Supercompilers LLC funded, by
introducing him and his Russian colleagues to a major Chicago
investor. In late 2001 I became even more intensely involved
with this work, joining the Supercompilers team on a part-time
basis, helping them out with shaping their business approach
and defining their direction of research. But by this point,
Turchin is playing only a very “high-level conceptual
guru” sort of role in the business; the main torch
is being carried by his former student Andrei Klimov, a
formidable intellect in his own right. Turchin is working
mainly on the cybernetic foundations of mathematics. I asked
him recently if he had considered cryonics – having
himself frozen after his death, so he could come back 50
or 500 years later and debate with intelligent computers,
post-metasystem-transition, about cybernetic math, global
brains or whatever. He said he had been thinking about this
sort of thing for decades, but hadn’t been aware of
any organization seriously doing it; but the group Alcor
that I pointed out to him (www.alcor.org) impressed him.
We shall see….
I realized, when I met Turchin in person and saw what sorts
of things were preoccupying him, that he was specifically
not on the kind of path that would lead him to become a
well-known “cyber-guru.” To become well-known
in the media as the originator or defender of a certain
idea, you have to spend all your time pushing the idea,
writing book after book about the same thing, giving interviews,
training disciples. Turchin’s way is exactly the opposite
of this. He stated his philosophical views very clearly
in an excellent book and some related articles, and then
in large part went back to technical work, albeit technical
work informed by his philosophy. His ideas have had a huge
influence behind the scenes, through their influence on
countless scientists of my generation. But his disciples,
if one may call them that, are pushing his technical agenda
not his philosophical one. In a way it made me sad to see
that, outside Russia, he simply wasn’t going to get
the acclaim he deserved. But then I realized it didn’t
matter: his goal had never been to get acclaim anyway, it
had been to speak the truth and to spread the truth, and
this goal had been accomplished.
Turchin’s
notion of metaystem transitions provides a powerful overall
framework within which to understand the maelstrom of scientific,
technological and social change that whirls all around us.
It allows us to see the unfolding transitions in humanity
as merely one phase in a longer and larger process –
similar in many ways to other phases, though with its own
unique and fascinating properties, and obviously with a
different personal relevance to us homo sapiens.
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Kurzweil’s
graph depicts the advance toward the Singularity quantitatively.
The vertical access is a measure of technical progress.
As Kurzweil puts it, “The paradigm shift rate (i.e.,
the overall rate of technical progress) is currently doubling
(approximately) every decade; that is, paradigm shift times
are halving every decade (and the rate of acceleration is
itself growing exponentially). So, the technological progress
in the twenty-first century will be equivalent to what would
require (in the linear view) on the order of 200 centuries.
In contrast, the twentieth century saw only about 25 years
of progress (again at today's rate of progress) since we
have been speeding up to current rates. So the twenty-first
century will see almost a thousand times greater technological
change than its predecessor.”
The metasystem transition notion gives a conceptual picture
to go with this graph.
Let’s begin at the beginning: According to current
physics theories, there was a metasystem transition in the
early universe, when the primordial miasma of disconnected
particles cooled down and settled into atoms. All of a sudden
the atom was the thing, and individual stray particles weren’t
the key tool to use in modeling the universe. Once particles
are inside atoms, the way to understand what particles are
doing is to understand the structure of the atom. And then
there was another transition from atoms to molecules, leading
to the emergence, within the first few instants after the
Big Bang, of the Periodic Table of Elements.
There was another metasystem transition on earth around
four billion years ago, when the steaming primordial seas
caused inorganic chemicals to clump together in groups capable
of reproduction and metabolism. Unicellular life emerged,
and once chemicals are embedded in life-forms, the way to
understand them is not in terms of chemistry alone, but
rather, in terms of concept like fitness, evolution, sex,
and hunger. Concepts like desire and intention are not far
off, even with paramecia: Does the paramecium desire its
food? Maybe not … but it comes a lot closer than a
rock does to desiring to roll down a hill….
And there was another metasystem transition when multicellular
life burst forth – suddenly the cell is no longer
an autonomous life form, but rather a component in a life
form on a higher level. The Cambrian explosion, immediately
following this transition, was the most amazing flowering
of new patterns and structures ever seen on Earth –
even we humans haven’t equaled it yet. 95% of the
species that arose at this time are now extinct, and paleontologists
are slowly reconstructing them so we can learn their lessons.
Note that the metasystem transition is not an antireductionist
concept, not in the strict sense. The idea isn’t that
multicellular lifeforms have cosmic emergent properties
that can’t be explained from the properties of cells.
Of course, if you had enough time and superhuman patience,
you could explain what happens in a human body in terms
of the component cells. The question is one of naturalness
and comprehensibility, or in other words, efficiency of
expression. Once you have a multicellular lifeform, it’s
much easier to discuss and analyze the properties of this
lifeform by reference to the emergent level than by going
down to the level of the component cells. In a puddle full
of paramecia, on the other hand, the way to explain observed
phenomena is usually by reference to the individual cells,
rather than the whole population – the population
has less wholeness, fewer interesting properties, than the
individual cells.
The
metasystem transition idea is important in its clear depiction
of the overall patterns of system evolution; and I have
also found it useful in my own research work on AI. In the
domain of mind, there are also a couple levels of metasystem
transition. The first one is what one might call the emergence
of “mind modules.” The second is the emergence
of mind from a conglomeration of interconnected, intensely
interacting mind modules. Since 1997 I have been leading
a team working towards building a “real AI”
– a software program with human-level general intelligence
– with a major focus on achieving this second metasystem
transition. I’ll talk about this work in a little
more detail in Chapter 3.
The first metasystem transition on the way toward mind occurs
when a huge collection of basic mind components –
cells, in a biological brain; “software objects”
in a computer mind – all come together in a unified
structure to carry out some complex function. The whole
is greater than the sum of the parts: the complex functions
that the system performs aren’t really implicit in
any of the particular parts of the system, rather they come
out of the coordination of the parts into a coherent whole.
The various parts of the human visual system are wonderful
examples of this. Billions of cells firing every which way,
all orchestrated together to do one particular thing: map
visual output from the retina into a primitive map of lines,
shapes and colors, to be analyzed by the rest of the brain.
The best current AI systems are also examples of this. In
fact, computer systems that haven’t passed this transition
I’d be reluctant to call “AI” in any serious
sense.
There are some so-called AI systems that haven’t even
reached this particular transition – they’re
really just collections of rules, and each behavior in the
whole system can be traced back to one particular rule.
But consider a sophisticated natural language system like
LexiQuest – which tries to answer human questions,
asked in ordinary language, based on information from databases
or extracted from texts. In a system like this, we do have
mind module emergence. When the system parses a sentence
and tries to figure out what question it represents, it’s
using hundreds of different rules for parsing, for finding
out what various parts of the sentences mean. The rules
are designed to work together, not in isolation. The control
parameters of each part of the system are tuned so as to
give maximal overall performance. LexiQuest isn’t
a mind, but it’s a primitive mind module, with its
own, albeit minimal, holistic emergence. The same is true
of other current high-quality systems for carrying out language
processing, computer vision, industrial robotics, and so
forth. For an example completely different from LexiQuest,
look at the MIT autonomous robots built under the direction
of Rodney Books. These robots seem to exhibit some basic
insect-level intelligence, roaming around the room trying
to satisfy their goals, displaying behavior patterns that
surprise their programmers. They’re action-reaction
modules, not minds, but they have holistic structures and
dynamics all their own.
On roughly the same level as LexiQuest and Brooks’
robots, we find computational neural networks, which carry
out functions like vision or handwriting recognition or
robot locomotion using hundreds up to hundreds of thousands
of chunks of computer memory emulating biological neurons.
As in the brain, the interesting behavior isn’t in
any one neuron, it’s in the whole network of neurons,
the integrative system. There are dozens of spin-offs from
the neural network concepts, such as the Bayesian networks
used in products like Autonomy and the Microsoft Help system.
Bayesian networks are networks of rules capable of making
decisions such as "If the user asks about ‘spreadsheet’,
activate the Excel help system". The programmer of
such a system never enters a statement where the rule "if
the word spreadsheet occurs, activate the help system"
appears -- rather this rule emerges from the dynamics of
the network. However, the programmer sets up the network
in a way that fairly rigidly controls what kinds of rules
can emerge. So while the system can discover new patterns
of input behavior that seem to indicate what actions should
be taken, it is unable to discover new kinds of actions
which can be taken – that is, it can only discover
new instances of information, not new types of information.
It’s not autonomous, not alive.
As I noted above, my own AI work has centered around creating
systems that embody a metasystem transition beyond this
“mind module” level. First, at Webmind Inc.,
my R&D team and I built a system called the Webmind
AI Engine (or simply “Webmind”). Since Webmind
Inc. folded in early 2001, a smaller group has been collaborating
with me on a successor system called Novamente, with the
same conceptual principles but a different mathematical
underpinning and software design.
Novamente, like Webmind, is a multimodular AI. Each module
of the Novamente system has roughly the same level of sophistication
as one of these bread-and-butter AI programs. There has
modules that carry out reasoning, language processing, numerical
data analysis, financial prediction, learning, short-term
memory, and so forth. All the modules are all built of the
same components, C++ software objects called “nodes”
and “relationships”. They arrange these components
in different ways, so that each module achieves its own
emergent behavior, each module realizing a metasystem transition
on its own.
But mind modules aren’t real intelligence, not in
the sense that we mean it: Intelligence as the ability to
carry out complex goals in complex environments. Each mind
module only does one kind of thing, requiring inputs of
a special type to be fed to it, unable to dynamically adapt
to a changing environment. Intelligence itself requires
one more metasystem transition: the coordination of a collection
of mind modules into a whole mind, each module serving the
whole and fully comprehensible only in the context of the
whole. This is a domain that AI research has basically not
confronted yet – it it’s not mere egotism to
assert that the Webmind/Novamente systems are almost unique
in this regard. It takes a lot of man-hours, a lot of thinking,
and a lot of processing power to build a single mind module,
let alone to build a bunch of them – and even more
to build a bunch of them in such a way as to support an
integrative system passing the next metasystem transition.
We’re just barely at the point now, computer-hardware-wise,
that we can seriously consider doing such a thing. But even
being just barely there is a pretty exciting thing.
Novamente allows the interoperation of these intelligent
modules within the context of a shared semantic representation
– nodes, links and so forth. Through the shared semantic
representation these different intelligent components can
interact and thus evolve a dynamical state which is not
possible within any one of the modules. Like a human brain,
each specialized sub-system is capable of achieving certain
complex perceptual (such as reading a page of text) or cognitive
(such as inferring causal relations) goals which in themselves
seem impressive - but when they are integrated, truly exciting
new possibilities emerge. Taken in combination, these intelligent
modules embodying systems such as reasoning, learning and
natural language processing, etc. undergo a metasystem transition
to become a mind capable of achieving complex goals worthy
of comparison to human abilities. The resulting mind can
not be described merely as a pipeline of AI process modules,
rather it has its own dynamical properties which emerge
from the interactions of these component parts, creating
new and unique patterns which were not present in any of
the sub-systems.
Such a metasystem transition from modules to mind is a truly
exciting emergence. A system such as Novamente can autonomously
adapt to changes in more complex environments than their
single-module predecessors, and can be trained in a manner
which is more like training a human than programming a computer.
This kind of a system theoretically can be adapted to any
task for which it is able to perceive input, and while the
initial Novamente system operates an a world of text and
numerical files only, integrating it with visual and auditory
systems, and perhaps a robot body, would allow it to have
some facility to perform in the physical world as well.
Applications of even the text and data constrained system
are quite varied and exciting, such as autonomous financial
analysis, conversational information retrieval, true knowledge
extraction from text and data, etc.
While there are other systems that can find some interesting
patterns in input data, a mind can determine the presence
of previously unknown types of patterns and make judgments
that are outside the realm of previous experience. An example
of this can be seen in financial market analysis. Previously
unknown market forces, such as the Internet, can impact
various financial instruments in ways which prevent successful
trading using traditional market techniques. A computer
mind can detect this new pattern of behavior, and develop
a new technique based on inferring how the current situation
relates to, but also differs from, from previous experience.
The Webmind Market Predictor product already did this, to
a limited extent, through the emergence of new behaviors
from the integration of only a few intelligent modules.
As more modules are integrated the system becomes more intelligent.
Currently the Webmind Market Predictor can create trading
strategies in terms of long, short, and hold positions on
instruments, detect changes in the market environment (using
both numerical indicators and by reading news feeds), and
develop new strategies based on these changes.
For another short-term, real-world example of the promise
of computational mind, let’s return to the area of
information retrieval. What we really want isn’t a
search engine – we want a digital assistant, with
an understanding of context and conversational give-and-take
like a human assistant provides. AskJeeves tries to provide
this, but ultimately it’s just a search engine/ chat-bot
hybrid. It’s amusing enough, but quite far from the
real possibilities in this area. A mind-based conversational
search tool, as will be possible using a completed Novamente
system, will be qualitatively different. When an ambiguous
request is made of a mind, it does not blindly return some
information pulled out of a database; a mind asks questions
to resolve ambiguous issues, using its knowledge of your
mind as well as the subject area to figure out what questions
to ask. When you ask a truly intelligent system “find
me information about Java”, it will ask back a question
such as “do you want information about the island,
the coffee, or the computer programming language?”
But if it knows you’re a programmer, it should ask
instead “Do you want to know about JVM’s or
design patterns or what?” Like a human, a machine
which has no exposure to the information that there is an
island called Java, for example, might only ask about coffee
and computers, but the ability to make a decision to resolve
the ambiguity in the first place, in a context-appropriate
way, is a mark of intelligence. An intelligent system will
use its background knowledge and previous experience to
include similar information (Java, J++, JVM, etc.), omit
misleading information (JavaScript, a totally different
programming language from Java), and analyze the quality
of the information. Information retrieval segues into information
creation, when a program infers new information by combining
the information available in the various documents it reads,
providing users with this newly created information as well
as reiterating what humans have written.
These practical applications are important, but it’s
worth remembering that the promise of digital mind goes
beyond these simple short-term considerations. Consider,
for example, the fact that digital intelligences have the
ability to acquire new perception systems during the course
of their lives. For instance, an intelligent computer system
to be attached to a bubble chamber and given the ability
to directly observe elementary particle interactions. Such
a system could greatly benefit particle physics research,
as the system would be able to think directly about the
particle world, without having to resort to metaphorical
interpretations of instrument readings as humans must do.
Similar advantages are available to computers in terms of
understanding financial and economic data, and recognizing
trends in vast bodies of text.
The
metasystem transition from mind modules to mind is the one
that I have mulled over the most, due to its connection
with my AI work. But it’s by no means the end of the
story. When Turchin formulated the metasystem transition
concept, he was actually thinking about something quite
different – the concept of the global brain, an emergent
system formed from humans and AI systems both, joined together
by the Internet and other cutting-edge communication technologies.
It’s a scary idea, but a potent one, and with a concrete
reality that shouldn’t be ignored.
Communication technology makes the world smaller each day
– will it eventually make it so small that the network
of people has more intrinsic integrity than any individual
person? Shadows of the sci-fi notion of a “hive mind”
arise here… images of the Borg Collective from Star
Trek. But what Turchin is hoping for is something much more
benign: a social structure that permits us our autonomy,
but channels our efforts in more productive directions,
guided by the good of the whole.
As noted above, Turchin himself is somewhat pessimistic
about the long-term consequences of all this, but not in
quite the alarmist vein of Bill Joy -- more in the spirit
of a typically Russian ironic doubt in human nature. In
other words, Bill Joy believes that high tech may lead us
down the road to hell, so we should avoid it; whereas Turchin
sees human nature itself as the really dangerous thing,
leading us to possible destruction through nuclear, biological,
or chemical warfare, or some other physical projection of
our intrinsic narrow-mindedness and animal hostility. He
hopes that technological advancement will allow us to overcome
some of the shortcomings of human nature and thus work toward
the survival and true mental health of our race.
Through the Principia Cybernetica project, co-developed
with Francis Heylighen (of the Free University of Brussels)
and Cliff Joslyn (of Los Alamos National Labs in the US),
Turchin has sought to develop a philosophical understanding
to go with the coming tech revolution, grounded on the concept
of the metasystem transition. As he says, the goal with
this is “to develop -- on the basis of the current
state of affairs in science and technology -- a complete
philosophy to serve as the verbal, conceptual part of a
new consciousness.” But this isn’t exactly being
done with typical American technological optimism. Rather,
as Turchin puts it, “My optimistic scenario is that
a major calamity will happen to humanity as a result of
the militant individualism; terrible enough to make drastic
changes necessary, but, hopefully, still mild enough not
to result in a total destruction. Then what we are trying
to do will have a chance to become prevalent. But possible
solutions must be carefully prepared.”
As I see it, the path from the Net that we have today to
the global brain that envelops humans and machines in a
single overarching superorganism involves not one but several
metasystem transitions. The first one is the emergence of
the global web mind – the transformation of the Internet
into a coherent organism. Currently the best way to explain
what happens on the Net is to talk about the various parts
of the Net: particular Websites, e-mail viruses, shopping
bots, and so forth. But there will come a point when this
is no longer the case, when the Net has sufficient high-level
dynamics of its own that the way to explain any one part
of the Net will be by reference to the whole. This will
come about largely through the interactions of AI systems
– intelligent programs acting on the behalf of various
Websites, Web users, corporations, and governments will
interact with each other intensively, forming something
halfway between a society of AI’s and an emergent
mind whose lobes are various AI agents serving various goals.
The traditional economy will be dead, replaced by a chaotically
dynamical hypereconomy (a term coined by the late transhumanist
theorist Alexander Chislenko) in which there are no intermediaries
except for information intermediaries: producers and consumers
(individually or in large aggregates created by automatic
AI discovery of affinity groups) negotiate directly with
each other to establish prices and terms, using information
obtained from subtle AI prediction and categorization algorithms.
How far off this is we can’t really tell, but it would
be cowardly not to give an estimate: I’m betting no
more than 10-30 years.
The advent of this system will be gradual. Initially when
only a few AI systems are deployed on the Web, they will
be individual systems which are going to be overwhelmed
with their local responsibilities. As more agents are added
to the Net, there will be more interaction between them.
Systems which specialize will refer questions to each other.
For example, a system that specialized in (had a lot of
background knowledge and evolved and inferred thinking processes
about) financial analysis may refer questions about political
activities to political analyst systems, and then combine
this information with its own knowledge to synthesize information
about the effects of political events on market activity.
This hypereconomic system of Internet agents will dynamically
establish the social and economic value of all information
and activities within the system, through interaction amongst
all agents in the system. As these interactions become more
complex, agent interconnections become more prevalent and
more dynamic, and agents become more interdependent the
network will become more of a true shared semantic space:
a global integrated mind-organism. Individual systems will
start to perform activities which have no parallel in the
existing natural world. One AI mind will directly transfer
knowledge to another by literally sending it a “piece
of its mind”; an AI mind will be able to directly
sense activities in many geographical locations and carry
on multiple context-separated conversations simultaneously;
a single global shared-memory will emerge allowing explicit
knowledge sharing in a collective consciousness. Across
the millions, someday billions, of machines on the Internet,
this global Web mind will function as a single collective
thought space, allowing individual agents to transcend their
individual limitations and share directly in a collective
consciousness, extending their capabilities far beyond their
individual means.
All this is fabulous enough – collective consciousness
among AI systems; the Net as a self-organizing intelligent
information space. But yet, it’s after this metasystem
transition – from Internet to global hypereconomic
Web mind -- that the transition envisioned by Turchin and
his colleages at Principia Cybernetica can take place: the
effective fusion of the global Web mind and the humans interacting
with it. It will be very interesting to see where biotech-enabled
virtual reality technology is at this point. At what point
will we really be jacking our brains into the global AI
matrix, as in Gibson’s novel Neuromancer? At what
point will we supercompile and improve our own cognitive
functions, or be left behind by our constantly self-reprogramming
AI compatriots? But we don’t even need to go that
far. Putting these more science-fictional possibilities
aside and focusing solely on Internet AI technology, it’s
clear that more and more of our interactions will be mediated
by the global emergent intelligent Net – every appliance
we use will be jacked into the matrix; every word that we
say potentially transmitted to anyone else on the planet
using wearable cellular telephony or something similar;
every thought that we articulate entered into an AI system
that automatically elaborates it and connects it with things
other humans and AI agents have said and thought elsewhere
in the world – or things other humans and AI agents
are expected to say based on predictive technology….
The Internet Supermind is not the end of the story –
it’s only the initial phase; the seed about which
will crystallize a new order of mind, culture and technology.
Is this going to be an instrument of fascist control, or
factional terrorism? It’s possible, but certainly
not inevitable – and the way to avoid this is for
as many people as possible to understand what’s happening,
what’s likely to happen, and how they can participate
in the positive expansion of this technology.
Imagine: human and machine identities joined into the collective
mind, creating a complex network of individuals from which
emerges the dynamics of a global supermind, with abilities
and boundaries far greater than would be possible for any
individual mind, human or artificial – or any community
consisting of humans or AI’s alone. As Francis Heylighen
has said, “Such a global brain will function as a
nervous system for the social superorganism, the integrated
system formed by the whole of human society.” Through
this global human-digital emergent mind, we will obtain
a unique perspective on the world, being able to simultaneously
sense and think in many geographical locations and potentially
across many perceptual media (text, sound, images, and various
sensors on satellites, cars, bubble chambers, etc.) The
cliché “let’s put our minds together
on this problem” will become a reality, allowing people
and machines to pool their respective talents directly to
solve tough problems in areas ranging from theoretical physics
to social system stabilization, and to create interesting
new kinds of works in literature and the arts.
Weird? Scary? To be sure. Exciting? Amazing? To be sure,
as well. Inevitable? An increasing number of techno-visionaries
think so. Some, like Bill Joy, have retreated into neo-Ludditism,
believing that technology is a big danger and advocating
careful legal control of AI, nanotech, biotech and related
things. Turchin is progressing ahead as fast as possible,
building the technology needed for the next phase of the
revolution, careful to keep an eye on the ethical issues
as he innovates, hoping his pessimism about human nature
will be proved wrong. As for us, we tend to be optimists.
Life isn’t perfect, plants and animals aren’t
perfect, humans aren’t perfect, computers aren’t
perfect – but yet, the universe has a wonderful way
of adapting to its mistakes and turning even ridiculous
errors into wonderful new forms.
The dark world of tyranny and fear described in the writings
of cyberpunk authors like William Gibson and Bruce Sterling,
and in films such as The Matrix and Blade Runner, is certainly
a possibility. But there’s also the possibility of
less troubling relationships between humans and their machine
counterparts, such as we see in the writings of transrealist
authors like Rudy Rucker and Stanislaw Lem, and in film
characters like Star Trek’s Data and Star Wars’
R2-D2 and C3P0. We believe, through ethical treatment of
humans, machines, and information, that a mutually beneficial
human-machine union within a global society of mind can
be achieved. The ethical and ontological issues of identity,
privacy, and selfhood are every bit as interesting and challenging
as the engineering issues of AI, and we need to avoid the
tendency to set them aside because they’re so difficult
to think about. But these things are happening – right
now we’re at the beginning, not the end, of this revolution;
and the potential rewards are spectacular -- enhanced perception,
greater memory, greater cognitive capacity, and the possibility
of true cooperation among all intelligent beings on earth.
In thinking about such wild and amazing transitions, it
pays to remember: we’ve been riding the rollercoaster
of universal evolution all along. The metasystem transitions
that gave rise to human bodies and human intelligence were
important steps along the path, but there will be other
steps, improving and incorporating humanity and ultimately
going beyond it.
Having
glimpsed such a glorious, ambitious, multifariously intricate
futuristic vision – having bathed oneself in this
vision for years, as I have -- where does one go next?
One can write science fiction stories or metaphysical poems
exulting in the wonder of it all. And why not? I must admit
I have succumbed to this urge now and then – and for
some reason it is often followed by the urge to cruise down
the highway in my 4Runner at 85 miles an hour with Yngwie
Malmsteen, Deep Purple or Steve Morse cranked up on the
stereo….
One can sit back and relax and enjoy oneself, waiting for
the Singularity. Unlike Waiting for Godot, one of my favorite
pieces of writing, which is all about empty spaces, this
wait is full of entertainment, constant changes and advances.
Or one can plunge into the details. And there sure are a
lot of them. The tech revolution and the impending Singularity
are too big a topic for any single book to treat them with
reasonable richness. In these pages I’ll plunge into
the details of the biological aspects of the great unfolding
story.
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Some
of my intellectual colleagues, deep into Singularitarian
thinking, view biocomputing as a sideshow. The real story,
they believe, will be in advanced AI, rapidly modifying
its own sourcecode until it’s 5000 times more intelligent
than humans and effortlessly reconfigures all the matter
in the solar system ever 15 seconds or so. In the long run
they may well be right. But I hope that John Maynard Keynes’
famous quip “In the long run, we’ll all be dead”
turns out not to be right. A future populated by superintelligent
AI systems is far more palatable to me than some other possibilities,
such as, say, a future in which all life and intelligence
in Earth are wiped out by nuclear weapons. But just as I’m
glad bugs still exist alongside us more intelligent beasts,
I’m happiest thinking about a future in which humans
persist no matter how far technology advances. In fact I
tend to think this is likely… though the humans of
the future may not look, act or think exactly like we do.
Some people like the idea of growing old and dying. There
is a spiritual completeness associated with death, a oneness
with nature. This is fine, for them. Some of us, on the
other hand, prefer the notion of existing as long as possible,
perhaps as long as the universe itself – or longer,
if advanced physics shows us how to escape into other universes.
This is a modification of current humanity that bioscience
seems very likely to provide. Apoptosis, the aging of cells,
will one day become as obsolete as smallpox.
Some people don’t like video games, or computers,
or electronic musical instruments. Personally, I have a
fanatical hatred of television. Again – no worries
– diversity of taste is a good thing. But we are going
to see advances beyond current human-computer interfaces,
which make the difference between parchment and e-mail seem
microscopic. Already quadriplegics can control their computers
directly using their brain waves. Once we can scan brain-states
better in real-time, we’ll be able to project our
thoughts directly into computers, and perhaps back out of
computers into others’ brains. Virtual reality technology
has been overhyped so far, but eventually it really will
happen – there are no fundamental obstacles, “just”
engineering difficulties and thorny neuroscience, of a type
that we humans have proved ourselves rather adept at solving.
Genetic engineering scares people – and the downside
is indeed dangerous. I don’t particularly want to
see, for instance, the government outlawing genes that have
been found to correlate with civil disobedience, or the
writing of unpatriotic literature. But how bad would it
be to see genes correlated with serial killing or profound
retardation or multiple personality syndrome filtered out
of the population? And how bad would it be if genetic engineering
could modify the brain-encoding genes, producing people
twice as good at math and physics as Einstein, or five times
as skilled at pragmatic social compassion than Gandhi or
Mother Teresa? Balancing the plusses and minuses of genetic
engineering seems to me to be an unsolvable ethical puzzle.
But I don’t think that mulling over this puzzle is
a terribly high priority, because I don’t believe
the technology could be squelched even if there were a 90%
universal will to do so. And I don’t think that waiting
to develop the technology is going to help anything –
a 20 or 50 or 100 year delay is not going to make humans
any more consistently ethical (the only thing that could
do that would be genetic engineering itself!). I think that
the best thing those concerned about the ethical implications
of genetic engineering can do is to become geneticists themselves
and work hard on positive applications. Let’s breed
a more compassionate and ethical race before someone breeds
a race of superintelligent psychopaths.
The interface between genetic engineering and human-computer
interfacing and AI is going to be particularly exciting.
Eventually we’ll be able to manipulate the genetic
code in such a way as to create humans who are especially
well-suited to interface with virtual worlds and artificial
intelligences. Sure, it’s wild and crazy sci-fi --
just like TV, submarines, airplanes and spacecraft once
were … ask your great-grandfather. What I’m
going to tell you about in these pages is why these ideas
aren’t so totally science-fictional after all. I’ll
lead you through the real-world science of today as it pertains
to the fantastic dreams of tomorrow. Turchin may not live
to see the metasystem transition in which networked AI comes
about, let alone the one in which genetically modified humans
and AI’s interact in virtual worlds, forming a whole
new kind of virtual mind/society/organism. On the other
hand, born in 1966 as I was, now age 35 in 2002, I might
just make it. And if Turchin avails himself of cryonic technology,
and has his body frozen shortly after death, he may be defrosted
into a whole new world….
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